MODEL DIRECTORY / ENGLISH
Models in the public snapshot
579 model IDs, 80 publishers. Context, output limit, official list price in CNY, and how many relay sites listed the model in the 2026-10-26 catalog snapshot.
Prices are CNY per 1M tokens from the directory snapshot. A provider's own page may quote USD. Relay coverage is a listing, not a detection result.
| Model | Publisher | Context | Max output | Input / 1M | Output / 1M | Sites |
|---|---|---|---|---|---|---|
| Jamba Large jamba-large | AI21实验室 | 256K | 4.096K | ¥13.37 | ¥53.48 | — |
| Jamba Mini jamba-mini | AI21实验室 | 256K | 4.096K | ¥1.34 | ¥2.67 | — |
| Claude Fable 5 claude-fable-5 | Anthropic | 1M | 128K | ¥66.85 | ¥334.24 | 24 |
| Claude Fable 5.1 claude-fable-5.1 | Anthropic | — | — | — | — | 24 |
| Claude Haiku 3 claude-3-haiku-20240307 | Anthropic | 200K | 4.096K | — | — | 5 |
| Claude Haiku 3.5 claude-3-5-haiku-20241022 | Anthropic | 200K | 8.192K | — | — | 5 |
| Claude Haiku 4.5 claude-haiku-4-5 | Anthropic | 200K | 64K | ¥6.68 | ¥33.42 | 24 |
| Claude Haiku 5.5 claude-haiku-5-5 | Anthropic | 1M | 128K | ¥0.67 | ¥3.34 | 24 |
| Claude Mythos 5 claude-mythos-5 | Anthropic | 1M | 128K | — | — | 3 |
| Claude Mythos 5.1 claude-mythos-5-1 | Anthropic | 1M | 128K | — | — | 2 |
| Claude Opus 4 claude-opus-4-0 | Anthropic | 200K | 32K | — | — | 13 |
| Claude Opus 4.1 claude-opus-4-1 | Anthropic | 200K | 32K | — | — | 14 |
| Claude Opus 4.5 claude-opus-4-5 | Anthropic | 200K | 64K | ¥33.42 | ¥167.12 | 24 |
| Claude Opus 4.6 claude-opus-4-6 | Anthropic | 1M | 128K | ¥33.42 | ¥167.12 | 24 |
| Claude Opus 4.7 claude-opus-4-7 | Anthropic | 1M | 128K | ¥33.42 | ¥167.12 | 24 |
| Claude Opus 4.8 claude-opus-4-8 | Anthropic | 1M | 128K | ¥33.42 | ¥167.12 | 24 |
| Claude Opus 5.5 claude-opus-5-5 | Anthropic | 1M | 128K | — | — | — |
| Claude Sonnet 3.5 v2 claude-3-5-sonnet-20241022 | Anthropic | 200K | 8.192K | — | — | 4 |
| Claude Sonnet 3.7 claude-3-7-sonnet-20250219 | Anthropic | 200K | 64K | — | — | 8 |
| Claude Sonnet 4 claude-sonnet-4-0 | Anthropic | 200K | 64K | — | — | 16 |
| Claude Sonnet 4.5 claude-sonnet-4-5 | Anthropic | 200K | 64K | ¥20.05 | ¥100.27 | 24 |
| Claude Sonnet 4.6 claude-sonnet-4-6 | Anthropic | 1M | 64K | ¥20.05 | ¥100.27 | 24 |
| Claude Sonnet 5 claude-sonnet-5 | Anthropic | 1M | 128K | ¥13.37 | ¥66.85 | 24 |
| Claude Sonnet 5.5 claude-sonnet-5-5 | Anthropic | 1M | 128K | — | — | — |
| Opus 5 claude-opus-5 | Anthropic | 1M | 128K | ¥33.42 | ¥167.12 | 24 |
| Doubao Seed 2.0 Lite doubao-seed-2.0-lite | ByteDance | — | — | — | — | 2 |
| Doubao Seed 2.1 Turbo doubao-seed-2.1-turbo | ByteDance | — | — | — | — | 3 |
| Doubao-Seedance-1.5-pro doubao-seedance-1.5-pro | ByteDance | — | — | — | — | 3 |
| Doubao-Seedance-2.0 doubao-seedance-2.0 | ByteDance | — | — | — | — | 13 |
| Doubao-Seedance-2.0-fast doubao-seedance-2.0-fast | ByteDance | — | — | — | — | 7 |
| Seed 1.6 seed-1-6 | ByteDance | 256K | 64K | ¥0.79 | ¥7.94 | 3 |
| Seed 1.6 Flash seed-1-6-flash | ByteDance | 256K | 32K | ¥0.15 | ¥1.49 | 3 |
| Seed 1.6 Vision seed-1-6-vision | ByteDance | 256K | 32K | ¥0.79 | ¥7.94 | 3 |
| Seed 1.8 seed-1-8 | ByteDance | 256K | 64K | ¥0.79 | ¥7.94 | 3 |
| Seed 2.0 Code seed-2.0-code | ByteDance | 262.144K | 131.072K | ¥3.18 | ¥15.88 | 6 |
| Seed 2.0 Lite seed-2.0-lite | ByteDance | 256K | 32K | ¥0.6 | ¥3.57 | 4 |
| Seed 2.0 Mini seed-2.0-mini | ByteDance | 256K | 32K | ¥0.2 | ¥1.98 | 7 |
| Seed 2.0 Pro seed-2.0-pro | ByteDance | 256K | 128K | ¥3.18 | ¥15.88 | 7 |
| Seed 2.1 Pro seed-2.1-pro | ByteDance | 256K | 256K | ¥5.95 | ¥29.77 | 5 |
| Seed 2.1 Turbo seed-2.1-turbo | ByteDance | 256K | 256K | ¥2.98 | ¥14.88 | 4 |
| Seed Character seed-character | ByteDance | 256K | 256K | ¥0.79 | ¥1.98 | 2 |
| Seed Evolving seed-evolving | ByteDance | 256K | 256K | ¥5.95 | ¥29.77 | 2 |
| Seed-OSS-36B-Instruct seed-oss-36b-instruct | ByteDance | 524.288K | 524.288K | — | — | — |
| Composer 2.5 composer-2.5 | Cursor | — | — | — | — | 4 |
| DeepSeek Chat deepseek-chat | DeepSeek | 1M | 384K | — | — | 3 |
| DeepSeek OCR 2 deepseek-ocr-2 | DeepSeek | 8.192K | 8.192K | — | — | — |
| DeepSeek R1 0528 deepseek-r1-0528 | DeepSeek | 163.84K | 32.768K | — | — | 3 |
| DeepSeek R1 0528 Qwen3 8B deepseek-r1-0528-qwen3-8b | DeepSeek | 131.072K | 32K | — | — | — |
| DeepSeek Reasoner deepseek-reasoner | DeepSeek | 1M | 384K | — | — | 6 |
| DeepSeek V3 0324 deepseek-chat-v3-0324 | DeepSeek | 163.84K | 147.456K | — | — | — |
| DeepSeek V3 0324 deepseek-v3-0324 | DeepSeek | 163.84K | 163.84K | — | — | 3 |
| DeepSeek V3.1 deepseek-chat-v3.1 | DeepSeek | 163.84K | 32.768K | — | — | — |
| DeepSeek V3.2 deepseek-v3.2 | DeepSeek | 128K | 64K | — | — | 9 |
| DeepSeek V4 Flash deepseek-v4-flash | DeepSeek | 1M | 384K | ¥1 | ¥2 | 24 |
| DeepSeek V4 Flash 0423 deepseek-v4-flash-0423 | DeepSeek | 1M | 384K | — | — | — |
| DeepSeek V4 Flash 0731 deepseek-v4-flash-0731 | DeepSeek | 1M | 384K | — | — | 24 |
| DeepSeek V4 Flash Vision Exp deepseek-v4-flash-vision-exp | DeepSeek | 1M | 384K | ¥1 | ¥4.01 | 11 |
| DeepSeek V4 Pro deepseek-v4-pro | DeepSeek | 1M | 384K | — | — | — |
| DeepSeek V4 Pro 0423 deepseek-v4-pro-0423 | DeepSeek | 1M | 384K | — | — | — |
| DeepSeek V4 Pro 0813 deepseek-v4-pro-0813 | DeepSeek | 1M | 384K | ¥4.41 | ¥13.24 | 24 |
| DeepSeek V4.1 Flash deepseek-v4.1-flash | DeepSeek | 1M | 384K | — | — | — |
| DeepSeek V4.1 Flash 1017 deepseek-v4.1-flash-1017 | DeepSeek | 1M | 384K | ¥1 | ¥4.01 | 17 |
| DeepSeek-R1 deepseek-r1 | DeepSeek | 128K | 32.768K | — | — | 5 |
| DeepSeek-R1-Distill-Qwen-32B deepseek-r1-distill-qwen-32b | DeepSeek | 131.072K | 32.768K | — | — | 2 |
| DeepSeek-V3 deepseek-v3 | DeepSeek | 131.072K | 8.192K | — | — | 5 |
| DeepSeek-V3.1 deepseek-v3.1 | DeepSeek | 131.072K | 8.192K | — | — | 6 |
| Deep Research Max Preview deep-research-max-preview-04-2026 | 1.04858M | 65.536K | ¥13.37 | ¥80.22 | — | |
| DiffusionGemma 26B A4B IT diffusiongemma-26b-a4b-it | 262.144K | 32.768K | — | — | — | |
| Gemini 2.0 Flash gemini-2.0-flash | 1.04858M | 8.192K | — | — | 3 | |
| Gemini 2.0 Flash-Lite gemini-2.0-flash-lite | 1.04858M | 8.192K | — | — | 2 | |
| Gemini 2.5 Computer Use Preview gemini-2.5-computer-use-preview-10-2025 | 128K | 64K | ¥8.36 | ¥66.85 | 2 | |
| Gemini 2.5 Flash gemini-2.5-flash | 1.04858M | 65.536K | ¥2.01 | ¥16.71 | 24 | |
| Gemini 2.5 Flash Preview 05-20 gemini-2.5-flash-preview-05-20 | 1.04858M | 65.536K | — | — | — | |
| Gemini 2.5 Flash TTS gemini-2.5-flash-tts | 32.768K | 16.384K | — | — | 2 | |
| Gemini 2.5 Flash-Lite gemini-2.5-flash-lite | 1.04858M | 65.536K | ¥0.67 | ¥2.67 | 24 | |
| Gemini 2.5 Flash-Lite Preview 06-17 gemini-2.5-flash-lite-preview-06-17 | 1.04858M | 65.536K | — | — | — | |
| Gemini 2.5 Flash-Lite Preview 09-2025 gemini-2.5-flash-lite-preview-09-2025 | 1.04858M | 65.536K | — | — | 2 | |
| Gemini 2.5 Pro gemini-2.5-pro | 1.04858M | 65.536K | ¥8.36 | ¥66.85 | 24 | |
| Gemini 2.5 Pro Preview 06-05 gemini-2.5-pro-preview | 1.04858M | 65.536K | — | — | — | |
| Gemini 2.5 Pro TTS gemini-2.5-pro-tts | 32.768K | 16.384K | — | — | 2 | |
| Gemini 3 Flash gemini-3-flash | — | — | — | — | 24 | |
| Gemini 3 Flash Preview gemini-3-flash-preview | 1.04858M | 65.536K | ¥3.34 | ¥20.05 | 24 | |
| Gemini 3 Pro Preview gemini-3-pro-preview | 1.04858M | 65.536K | — | — | 24 | |
| Gemini 3.1 Flash Lite gemini-3.1-flash-lite | 1.04858M | 65.536K | ¥1.67 | ¥10.03 | 24 | |
| Gemini 3.1 Flash Lite Preview gemini-3.1-flash-lite-preview | 1.04858M | 65.536K | ¥1.67 | ¥10.03 | 22 | |
| Gemini 3.1 Flash Live Preview gemini-3.1-flash-live-preview | 131.072K | 65.536K | ¥5.01 | ¥30.08 | 1 | |
| Gemini 3.1 Flash TTS Preview gemini-3.1-flash-tts-preview | 8.192K | 16.384K | ¥6.68 | ¥133.7 | 4 | |
| Gemini 3.1 Pro gemini-3.1-pro-preview | 1.04858M | 65.536K | ¥13.7 | ¥82.2 | 24 | |
| Gemini 3.1 Pro Preview gemini-3.1-pro | — | — | ¥13.7 | ¥82.2 | 17 | |
| Gemini 3.1 Pro Preview Custom Tools gemini-3.1-pro-preview-customtools | 1.04858M | 65.536K | ¥13.37 | ¥80.22 | 5 | |
| Gemini 3.5 Flash gemini-3.5-flash | 1.04858M | 65.536K | ¥10.5 | ¥63 | 24 | |
| Gemini 3.5 Flash Lite gemini-3.5-flash-lite | 1.04858M | 65.536K | ¥2.01 | ¥16.71 | 24 | |
| Gemini 3.5 Live Translate Preview gemini-3.5-live-translate-preview | 131.072K | 65.536K | ¥23.4 | ¥140.38 | 1 | |
| Gemini 3.6 Flash gemini-3.6-flash | 1.04858M | 65.536K | ¥5.01 | ¥25.07 | 24 | |
| Gemini 3.7 Flash gemini-3.7-flash | 1.04858M | 65.536K | ¥5.4 | ¥27 | 24 | |
| Gemini 3.8 Flash gemini-3.8-flash | 1.04858M | 65.536K | — | — | — | |
| Gemini 4 Argon gemini-4-argon | 1.04858M | 65.536K | — | — | — | |
| Gemini Deep Research Preview deep-research-preview-04-2026 | 1.04858M | 65.536K | ¥13.37 | ¥80.22 | — | |
| Gemini Embedding 001 gemini-embedding-001 | 2.048K | 1 | ¥1 | ¥0 | 4 | |
| Gemini Embedding 2 gemini-embedding-2 | 8.192K | 3.072K | ¥1.34 | ¥0 | 5 | |
| Gemini Flash Latest gemini-flash-latest | 1.04858M | 65.536K | ¥5.01 | ¥25.07 | 2 | |
| Gemini Flash-Lite Latest gemini-flash-lite-latest | 1.04858M | 65.536K | ¥2.01 | ¥16.71 | 4 | |
| Gemini Omni 1.1 Flash gemini-omni-1.1-flash | 1.04858M | 57.92K | — | — | 2 | |
| Gemini Omni Flash Preview gemini-omni-flash-preview | 1.04858M | 57.92K | ¥10.03 | ¥116.99 | 4 | |
| Gemini Robotics-ER 1.6 Preview gemini-robotics-er-1.6-preview | 131.072K | 65.536K | — | — | 2 | |
| Gemma 2 27B gemma-2-27b-it | 8.192K | 2.048K | — | — | — | |
| Gemma 2 2B IT gemma-2-2b-it | 8.192K | 8.192K | — | — | — | |
| Gemma 3 12B IT gemma-3-12b-it | 131.072K | 131.072K | — | — | — | |
| Gemma 3 27B IT gemma-3-27b-it | 131.072K | 131.072K | — | — | — | |
| Gemma 3 4B IT gemma-3-4b-it | 131.072K | 131.072K | — | — | — | |
| Gemma 3n E2B IT gemma-3n-e2b-it | 32.768K | 32.768K | — | — | — | |
| Gemma 3n E4B IT gemma-3n-e4b-it | 32.768K | 32.768K | — | — | — | |
| Gemma 4 12B IT gemma-4-12b-it | 262.144K | 32.768K | — | — | — | |
| Gemma 4 26B A4B IT gemma-4-26b-a4b-it | 262.144K | 32.768K | — | — | — | |
| Gemma 4 31B IT gemma-4-31b-it | 262.144K | 32.768K | — | — | 2 | |
| Gemma 4 E2B IT gemma-4-e2b-it | 131.072K | 8.192K | — | — | — | |
| Gemma 4 E4B IT gemma-4-e4b-it | 131.072K | 8.192K | — | — | — | |
| Lyria 3 Clip Preview lyria-3-clip-preview | 131.072K | 65.536K | ¥0 | ¥0 | 2 | |
| Lyria 3 Pro Preview lyria-3-pro-preview | 131.072K | 8.192K | ¥0 | ¥0 | 2 | |
| Nano Banana gemini-2.5-flash-image | 32.768K | 32.768K | ¥2.01 | ¥200.55 | 15 | |
| Nano Banana 2 gemini-3.1-flash-image | 131.072K | 32.768K | ¥3.34 | ¥401.09 | 24 | |
| Nano Banana 2 Lite gemini-3.1-flash-lite-image | 65.536K | 4.096K | ¥1.67 | ¥200.55 | 12 | |
| Nano Banana 2.1 gemini-nano-banana-2.1 | 131.072K | 32.768K | — | — | 24 | |
| Nano Banana Pro gemini-3-pro-image | 65.536K | 32.768K | ¥13.37 | ¥802.18 | 24 | |
| Nano Banana Pro Preview gemini-3-pro-image-preview | 65.536K | 32.768K | ¥13.37 | ¥802.18 | 24 | |
| NanoBanana 2 gemini-3.1-flash-image-preview | 65.536K | 65.536K | ¥3.34 | ¥401.09 | 24 | |
| Veo 3.1 Fast Preview veo-3.1-fast-generate-preview | 1.024K | — | — | — | 3 | |
| Veo 3.1 Preview veo-3.1-generate-preview | 1.024K | 1 | — | — | 3 | |
| Ling 3.0 Flash ling-3.0-flash | InclusionAI | 262.144K | 32.768K | — | — | — |
| Ling 3.0 Flash Fin ling-3.0-flash-fin | InclusionAI | 262.144K | 32.768K | — | — | — |
| Ling 3.0 Flash Sante ling-3.0-flash-sante | InclusionAI | 262.144K | 32.768K | — | — | — |
| Ling 3.0 Flash VL ling-3.0-flash-vl | InclusionAI | 262.144K | 32.768K | — | — | — |
| Ling 3.1 Flash ling-3.1-flash | InclusionAI | 262.144K | 32.768K | — | — | — |
| Llama 3.2 1B Instruct llama-3.2-1b-instruct | Meta | 131.072K | 32K | — | — | 3 |
| Llama 3.2 3B Instruct llama-3.2-3b-instruct | Meta | 131.072K | 131.072K | — | — | 3 |
| Llama 4 Maverick 17B Instruct llama-4-maverick-17b-instruct | Meta | 1M | 16.384K | — | — | — |
| Llama 4 Scout 17B Instruct llama-4-scout-17b-instruct | Meta | 10M | 16.384K | — | — | — |
| Llama Guard 4 12B llama-guard-4-12b | Meta | 163.84K | 163.84K | — | — | — |
| Llama Prompt Guard 2 22M llama-prompt-guard-2-22m | Meta | 512 | 512 | — | — | — |
| Llama Prompt Guard 2 86M llama-prompt-guard-2-86m | Meta | 512 | 512 | — | — | — |
| Llama-3.1-70B-Instruct llama-3.1-70b-instruct | Meta | 128K | 4.096K | — | — | 3 |
| Llama-3.1-8B-Instruct llama-3.1-8b-instruct | Meta | 128K | 4.096K | — | — | 3 |
| Llama-3.2-11B-Vision-Instruct llama-3.2-11b-vision-instruct | Meta | 128K | 4.096K | — | — | 3 |
| Llama-3.2-1B llama-3.2-1b | Meta | 131.072K | 8.192K | — | — | 3 |
| Llama-3.2-3B llama-3.2-3b | Meta | 131.072K | 8.192K | — | — | 3 |
| Llama-3.2-90B-Vision-Instruct llama-3.2-90b-vision-instruct | Meta | 128K | 4.096K | — | — | 3 |
| Llama-3.3-70B-Instruct llama-3.3-70b-instruct | Meta | 128K | 4.096K | — | — | 3 |
| Llama-Guard-3-8B llama-guard-3-8b | Meta | 128K | 4.096K | — | — | — |
| Muse Glimmer 30B muse-glimmer-30b | Meta | 131.072K | 131.072K | — | — | — |
| Muse Spark 1.1 muse-spark-1.1 | Meta | 1.04858M | 131.072K | ¥8.36 | ¥28.41 | 3 |
| Muse Spark 1.2 muse-spark-1.2 | Meta | 1.04858M | 131.072K | ¥8.36 | ¥28.41 | 4 |
| Muse Spark 1.3 muse-spark-1.3 | Meta | 1.04858M | 131.072K | ¥8.36 | ¥28.41 | 8 |
| Muse Spark Open muse-spark-open | Meta | 1.04858M | 131.072K | — | — | — |
| Muse Wonder muse-wonder-1.0 | Meta | 1.04858M | 131.072K | ¥26.74 | ¥133.7 | 3 |
| MiniMax H3 minimax-h3 | MiniMax | — | — | — | — | 11 |
| MiniMax M1 80K minimax-m1-80k | MiniMax | 1M | 80K | — | — | 3 |
| MiniMax M2.5 minimax-m2.5 | MiniMax | 204.8K | 131.072K | ¥2.01 | ¥8.02 | 16 |
| MiniMax M2.7 minimax-m2.7 | MiniMax | 204.8K | 131.072K | ¥2.1 | ¥8.4 | 23 |
| MiniMax M3 minimax-m3 | MiniMax | 1.04858M | 512K | ¥2.01 | ¥8.02 | 24 |
| MiniMax Text 01 (MiniMax) minimax-text-01 | MiniMax | 1M | 131.072K | — | — | — |
| MiniMax-M2 minimax-m2 | MiniMax | 204.8K | 131.072K | ¥2.01 | ¥8.02 | 4 |
| MiniMax-M2 Her minimax-m2-her | MiniMax | 65.536K | 2.048K | — | — | — |
| MiniMax-M2.1 minimax-m2.1 | MiniMax | 204.8K | 131.072K | ¥2.01 | ¥8.02 | 5 |
| MiniMax-M2.5-highspeed minimax-m2.5-highspeed | MiniMax | 204.8K | 131.072K | ¥4.01 | ¥16.04 | 5 |
| MiniMax-M2.7-highspeed minimax-m2.7-highspeed | MiniMax | 204.8K | 131.072K | ¥4.01 | ¥16.04 | 9 |
| MiniMax-M3.1-Flash minimax-m3.1-flash | MiniMax | 1M | 512K | ¥1 | ¥4.01 | 14 |
| MiniMax-M3.1-Flash-Preview minimax-m3.1-flash-preview | MiniMax | 1M | 512K | — | — | — |
| Mistral Large 3 mistral.mistral-large-3-675b-instruct | Mistral | 262.144K | 8.192K | — | — | — |
| Toast 1 toast-1 | Mixedbread | 131K | 4K | — | — | — |
| Kimi K3 kimi-k3 | Moonshot | 1.04858M | 131.072K | — | — | — |
| GPT 6 Luna gpt-6-luna | OpenAI | 1.05M | 128K | ¥0.67 | ¥3.34 | 24 |
| GPT Image 2.5 Flare gpt-image-2.5-flare | OpenAI | — | — | — | — | 24 |
| GPT Image 2.5 Sunburst gpt-image-2.5-sunburst | OpenAI | — | — | — | — | 24 |
| GPT OSS 120B gpt-oss-120b | OpenAI | 131.072K | 32.768K | — | — | 6 |
| GPT OSS 20B gpt-oss-20b | OpenAI | 131.072K | 32.768K | — | — | 3 |
| GPT OSS Safeguard 120B gpt-oss-safeguard-120b | OpenAI | 131.072K | 32.768K | — | — | — |
| GPT OSS Safeguard 20B gpt-oss-safeguard-20b | OpenAI | 131.072K | 131.072K | — | — | — |
| GPT Realtime Whisper gpt-realtime-whisper | OpenAI | 16K | 2K | — | — | — |
| GPT-3.5-turbo gpt-3.5-turbo | OpenAI | 16.385K | 4.096K | ¥3.34 | ¥10.03 | 11 |
| GPT-4 gpt-4 | OpenAI | 8.192K | 8.192K | ¥200.55 | ¥401.09 | 8 |
| GPT-4 Turbo gpt-4-turbo | OpenAI | 128K | 4.096K | ¥66.85 | ¥200.55 | 9 |
| GPT-4.1 gpt-4.1 | OpenAI | 1.04758M | 32.768K | ¥13.37 | ¥53.48 | 12 |
| GPT-4.1 mini gpt-4.1-mini | OpenAI | 1.04758M | 32.768K | ¥2.67 | ¥10.7 | 12 |
| GPT-4.1 nano gpt-4.1-nano | OpenAI | 1.04758M | 32.768K | ¥0.67 | ¥2.67 | 12 |
| GPT-4o gpt-4o | OpenAI | 128K | 16.384K | ¥16.71 | ¥66.85 | 14 |
| GPT-4o (2024-05-13) gpt-4o-2024-05-13 | OpenAI | 128K | 4.096K | ¥33.42 | ¥100.27 | 10 |
| GPT-4o (2024-08-06) gpt-4o-2024-08-06 | OpenAI | 128K | 16.384K | ¥16.71 | ¥66.85 | 10 |
| GPT-4o (2024-11-20) gpt-4o-2024-11-20 | OpenAI | 128K | 16.384K | ¥16.71 | ¥66.85 | 11 |
| GPT-4o mini gpt-4o-mini | OpenAI | 128K | 16.384K | ¥1 | ¥4.01 | 12 |
| GPT-5 gpt-5 | OpenAI | 400K | 128K | ¥8.36 | ¥66.85 | 14 |
| GPT-5 Chat gpt-5-chat-latest | OpenAI | 400K | 128K | — | — | 7 |
| GPT-5 Image gpt-5-image | OpenAI | 400K | 128K | — | — | — |
| GPT-5 Image Mini gpt-5-image-mini | OpenAI | 400K | 128K | — | — | — |
| GPT-5 mini gpt-5-mini | OpenAI | 400K | 128K | ¥1.67 | ¥13.37 | 12 |
| GPT-5 Nano gpt-5-nano | OpenAI | 400K | 128K | ¥0.33 | ¥2.67 | 10 |
| GPT-5 Pro gpt-5-pro | OpenAI | 400K | 272K | ¥100.27 | ¥802.18 | 10 |
| GPT-5-Codex gpt-5-codex | OpenAI | 400K | 128K | — | — | 8 |
| GPT-5.1 gpt-5.1 | OpenAI | 400K | 128K | ¥8.36 | ¥66.85 | 13 |
| GPT-5.1 Chat gpt-5.1-chat-latest | OpenAI | 128K | 16.384K | — | — | 6 |
| GPT-5.1 Codex gpt-5.1-codex | OpenAI | 400K | 128K | — | — | 9 |
| GPT-5.1 Codex Max gpt-5.1-codex-max | OpenAI | 400K | 128K | — | — | 6 |
| GPT-5.1 Codex mini gpt-5.1-codex-mini | OpenAI | 400K | 128K | — | — | 9 |
| GPT-5.2 gpt-5.2 | OpenAI | 400K | 128K | ¥11.7 | ¥93.59 | 24 |
| GPT-5.2 Chat gpt-5.2-chat-latest | OpenAI | 128K | 16.384K | ¥11.7 | ¥93.59 | 11 |
| GPT-5.2 Codex gpt-5.2-codex | OpenAI | 400K | 128K | — | — | 12 |
| GPT-5.2 Pro gpt-5.2-pro | OpenAI | 400K | 128K | ¥140.38 | ¥1123.06 | 10 |
| GPT-5.3 Chat gpt-5.3-chat-latest | OpenAI | 128K | 16.384K | ¥11.7 | ¥93.59 | 5 |
| GPT-5.3 Codex gpt-5.3-codex | OpenAI | 400K | 128K | ¥11.7 | ¥93.59 | 24 |
| GPT-5.3 Codex Spark gpt-5.3-codex-spark | OpenAI | 128K | 32K | ¥11.7 | ¥93.59 | 19 |
| GPT-5.4 gpt-5.4 | OpenAI | 1.05M | 128K | ¥16.71 | ¥100.27 | 24 |
| GPT-5.4 Image 2 gpt-5.4-image-2 | OpenAI | 272K | 128K | — | — | — |
| GPT-5.4 Mini gpt-5.4-mini | OpenAI | 400K | 128K | ¥5.01 | ¥30.08 | 24 |
| GPT-5.4 nano gpt-5.4-nano | OpenAI | 400K | 128K | ¥1.34 | ¥8.36 | 15 |
| GPT-5.4 Pro gpt-5.4-pro | OpenAI | 1.05M | 128K | ¥200.55 | ¥1203.28 | 10 |
| GPT-5.5 gpt-5.5 | OpenAI | 1.05M | 128K | ¥33.42 | ¥200.55 | 24 |
| GPT-5.5 Instant gpt-5.5-instant | OpenAI | 400K | 128K | — | — | 4 |
| GPT-5.5 Pro gpt-5.5-pro | OpenAI | 1.05M | 128K | ¥200.55 | ¥1203.28 | 6 |
| GPT-5.6 Cyber gpt-5.6-cyber | OpenAI | 400K | 128K | ¥83.56 | ¥501.36 | 2 |
| GPT-5.6 Luna gpt-5.6-luna | OpenAI | 1.05M | 128K | ¥1.34 | ¥8.02 | 24 |
| GPT-5.6 Sol gpt-5.6-sol | OpenAI | 1.05M | 128K | — | — | — |
| GPT-6 Astra gpt-6-astra | OpenAI | 1.05M | 128K | — | — | — |
| GPT-6 Astra (Fast) gpt-6-astra-fast | OpenAI | 1.05M | 128K | — | — | 2 |
| GPT-6 Sol gpt-6-sol | OpenAI | 1.05M | 128K | — | — | — |
| GPT-6.1 Sol gpt-6.1-sol | OpenAI | 1.05M | 128K | — | — | — |
| GPT-6.1 Terra gpt-6.1-terra | OpenAI | 1.05M | 128K | — | — | — |
| GPT-Image-1 gpt-image-1 | OpenAI | — | — | — | — | 16 |
| GPT-Image-1.5 gpt-image-1.5 | OpenAI | — | — | — | — | 16 |
| GPT-Realtime-2.1 gpt-realtime-2.1 | OpenAI | 128K | 32K | ¥26.74 | ¥160.44 | 3 |
| o1 o1 | OpenAI | 200K | 100K | ¥100.27 | ¥401.09 | 10 |
| o1-pro o1-pro | OpenAI | 200K | 100K | ¥1002.73 | ¥4010.92 | 4 |
| o3 o3 | OpenAI | 200K | 100K | ¥13.37 | ¥53.48 | 11 |
| o3-deep-research o3-deep-research | OpenAI | 200K | 100K | — | — | 4 |
| o3-mini o3-mini | OpenAI | 200K | 100K | ¥7.35 | ¥29.41 | 11 |
| o3-pro o3-pro | OpenAI | 200K | 100K | ¥133.7 | ¥534.79 | 8 |
| o4-mini o4-mini | OpenAI | 200K | 100K | ¥7.35 | ¥29.41 | 11 |
| o4-mini-deep-research o4-mini-deep-research | OpenAI | 200K | 100K | — | — | 4 |
| Whisper 3 Large whisper-large-v3 | OpenAI | 448 | 4.096K | — | — | — |
| Whisper Large v3 Turbo whisper-large-v3-turbo | OpenAI | 448 | 448 | — | — | — |
| MiniCPM-V 4.7 1B minicpm-v-4.7-1b | OpenBMB | 262.144K | 262.144K | — | — | — |
| MiniCPM-V 4.7 35B-A3B minicpm-v-4.7-35b-a3b | OpenBMB | 262.144K | 262.144K | — | — | — |
| MiniCPM5-1B minicpm5-1b | OpenBMB | 131.072K | 131.072K | — | — | — |
| MiniCPM5-2B minicpm5-2b | OpenBMB | 131.072K | 131.072K | — | — | — |
| Fugu Max fugu-max | Sakana AI | 1M | 128K | — | — | — |
| Fugu Ultra fugu-ultra | Sakana AI | 1M | — | ¥33.42 | ¥200.55 | — |
| Fugu Ultra v2 fugu-ultra-v2 | Sakana AI | 1M | 128K | — | — | — |
| Sakana Namazu sakana-namazu | Sakana AI | 262.144K | 65.536K | ¥6.35 | ¥26.74 | — |
| SOLAR 10.7B Instruct v1.0 solar-10.7b-instruct-v1.0 | Upstage | 4.096K | 4.096K | — | — | — |
| Solar Mini 4 solar-mini4 | Upstage | 524.288K | 131.072K | ¥0.67 | ¥2.67 | — |
| Solar Pro 2 solar-pro2 | Upstage | 65.536K | 8.192K | ¥1.67 | ¥1.67 | — |
| Solar Pro 3 solar-pro3 | Upstage | 131.072K | 8.192K | ¥1.67 | ¥1.67 | — |
| Solar Pro 4 solar-pro4 | Upstage | 524.288K | 131.072K | ¥2.01 | ¥8.02 | — |
| Grok 4.1 Fast grok-4.1-fast | xAI | 2M | 30K | — | — | 3 |
| Grok 4.1 Fast (Reasoning) grok-4.1-fast-reasoning | xAI | 2M | 30K | — | — | 3 |
| Grok 4.20 (Non-Reasoning) grok-4.20-0309-non-reasoning | xAI | 1M | 30K | ¥8.36 | ¥16.71 | 12 |
| Grok 4.20 (Reasoning) grok-4.20-0309-reasoning | xAI | 1M | 30K | ¥8.36 | ¥16.71 | 12 |
| Grok 4.3 grok-4.3 | xAI | 1M | 30K | ¥8.36 | ¥16.71 | 11 |
| Grok 4.5 grok-4.5 | xAI | 500K | 500K | ¥13.7 | ¥41.1 | 24 |
| Grok 4.6 grok-4.6 | xAI | 500K | 500K | ¥14.4 | ¥43.2 | 24 |
| Grok 4.7 grok-4-7 | xAI | 524.288K | 500K | — | — | — |
| Grok Build 0.1 grok-build-0.1 | xAI | 256K | 256K | ¥6.68 | ¥13.37 | 11 |
| Grok Code Fast 1 grok-code-fast-1 | xAI | 256K | 10K | — | — | 2 |
| Grok Imagine Image grok-imagine-image | xAI | 16K | — | — | — | 21 |
| Grok Imagine Image 2.0 grok-imagine-image-2.0 | xAI | 64K | — | — | — | 21 |
| Grok Imagine Image Quality grok-imagine-image-quality | xAI | 16K | — | — | — | 18 |
| Grok Imagine Video 1.5 grok-imagine-video-1.5 | xAI | 1.024K | — | — | — | 12 |
| Grok TTS grok-tts | xAI | 15K | 15K | — | — | 2 |
| Grok Voice STT 1.0 grok-voice-stt-1.0 | xAI | 15K | 15K | — | — | 1 |
| Grok Voice TTS 1.0 grok-voice-tts-1.0 | xAI | 15K | 15K | — | — | 1 |
| X-Ai/Grok-4-Fast-Non-Reasoning grok-4-fast-non-reasoning | xAI | 2M | 2M | — | — | 3 |
| X-Ai/Grok-4-Fast-Reasoning grok-4-fast-reasoning | xAI | 2M | 2M | — | — | 3 |
| GLM-5.3 glm-5.3 | Zhipu | 1M | 131.072K | — | — | — |
| Nova 2 Lite nova-2-lite | 亚马逊 | 1M | 65.536K | — | — | — |
| Nova Lite nova-lite | 亚马逊 | 300K | 10K | — | — | — |
| Nova Lite 1.0 nova-lite-v1 | 亚马逊 | 300K | 5.12K | — | — | — |
| Nova Micro nova-micro | 亚马逊 | 128K | 10K | — | — | — |
| Nova Micro 1.0 nova-micro-v1 | 亚马逊 | 128K | 5.12K | — | — | — |
| Nova Premier nova-premier | 亚马逊 | 1M | 10K | — | — | — |
| Nova Pro nova-pro | 亚马逊 | 300K | 10K | — | — | — |
| Nova Pro 1.0 nova-pro-v1 | 亚马逊 | 300K | 5.12K | — | — | — |
| Perceptron Mk1 perceptron-mk1 | 佩尔塞普特龙 | 32.768K | 8.192K | — | — | — |
| Perceptron Mk1.5 perceptron-mk1.5 | 佩尔塞普特龙 | 36.864K | 8.192K | — | — | — |
| LFM2 24B A2B lfm2-24b-a2b | 利奎德因弗伦斯 | 32.768K | 32.768K | — | — | — |
| Orpheus Arabic Saudi orpheus-arabic-saudi | 卡诺皮实验室 | 4K | 50K | — | — | — |
| Orpheus V1 English orpheus-v1-english | 卡诺皮实验室 | 4K | 50K | — | — | — |
| Mercury 2 mercury-2 | 因塞普申 | 128K | 50K | — | — | — |
| Mercury 2.5 mercury-2.5 | 因塞普申 | 260K | 65.536K | — | — | — |
| Mercury 3 mercury-3 | 因塞普申 | 1M | 131.072K | — | — | — |
| Mercury Edit 2 mercury-edit-2 | 因塞普申 | 32K | 8.192K | — | — | — |
| Schematron V2 Small schematron-v2-small | 因弗伦斯-内特 | 128K | 4.096K | — | — | — |
| Schematron V2 Turbo schematron-v2-turbo | 因弗伦斯-内特 | 128K | 8.192K | — | — | — |
| Granite 4.2 8B granite-4.2-8b | 国际商业机器公司 | 131.072K | 117.964K | — | — | — |
| Granite-4.0-H-Micro granite-4-h-micro | 国际商业机器公司 | 131.072K | 131.072K | — | — | — |
| Granite-4.0-H-Small granite-4-h-small | 国际商业机器公司 | 131.072K | 131.072K | — | — | — |
| Aion-2.0 aion-2.0 | 埃昂实验室 | 131.072K | 32.768K | — | — | — |
| Aion-3.0 aion-3.0 | 埃昂实验室 | 131.072K | 32.768K | — | — | — |
| Aion-3.0-Mini aion-3.0-mini | 埃昂实验室 | 131.072K | 32.768K | — | — | — |
| Aion-RP 1.0 (8B) aion-rp-llama-3.1-8b | 埃昂实验室 | 32.768K | 29.491K | — | — | — |
| Rnj-1 Instruct rnj-1-instruct | 埃森舍尔人工智能 | 32.768K | 32.768K | — | — | — |
| Nex-N2-Pro nex-n2-pro | 奈克斯人工智能 | 262.144K | 262.144K | — | — | — |
| Arrow 2 arrow-2 | 奎弗人工智能 | 131.072K | 65.536K | — | — | — |
| Arrow 2 Telos arrow-2-telos | 奎弗人工智能 | 1.05M | 65.536K | — | — | — |
| Pareto pareto | 安比艾斯 | 262.144K | 131.072K | — | — | — |
| Magnum v4 72B magnum-v4-72b | 安瑟拉赛特-奥格 | 32.768K | 4.096K | — | — | — |
| MiMo V2 Omni mimo-v2-omni | 小米 | 262.144K | 131.072K | ¥0.94 | ¥1.87 | 3 |
| MiMo V2 Pro mimo-v2-pro | 小米 | 1.04858M | 131.072K | ¥2.91 | ¥5.82 | 4 |
| MiMo-V2-Flash mimo-v2-flash | 小米 | 262.144K | 65.536K | ¥0.94 | ¥1.87 | 3 |
| MiMo-V2-TTS mimo-v2-tts | 小米 | 8.192K | 8.192K | — | — | 2 |
| MiMo-V2.5 mimo-v2.5 | 小米 | 1.04858M | 131.072K | ¥0.94 | ¥1.87 | 15 |
| MiMo-V2.5-Pro mimo-v2.5-pro | 小米 | 1.04858M | 131.072K | ¥2.91 | ¥5.82 | 17 |
| MiMo-V2.5-Pro-UltraSpeed mimo-v2.5-pro-ultraspeed | 小米 | 1.04858M | 131.072K | ¥8.72 | ¥17.45 | — |
| MiMo-V2.5-TTS mimo-v2.5-tts | 小米 | 8.192K | 8.192K | — | — | 2 |
| MiMo-V2.5-TTS-VoiceClone mimo-v2.5-tts-voiceclone | 小米 | 8.192K | 8.192K | — | — | 2 |
| MiMo-V2.5-TTS-VoiceDesign mimo-v2.5-tts-voicedesign | 小米 | 8.192K | 8.192K | — | — | 3 |
| MiMo-V2.6-Flash mimo-v2.6-flash | 小米 | 1.04858M | 131.072K | ¥0.94 | ¥1.87 | 19 |
| MiMo-V2.6-Pro mimo-v2.6-pro | 小米 | 1.04858M | 131.072K | ¥2.91 | ¥5.82 | 18 |
| MiMo-V2.6-Pro-UltraSpeed mimo-v2.6-pro-ultraspeed | 小米 | 1.04858M | 131.072K | ¥29.08 | ¥58.16 | 3 |
| MAI-Code-1-Flash mai-code-1-flash | 微软 | 256K | 128K | — | — | — |
| MAI-Code-1.1-Flash mai-code-1.1-flash | 微软 | 256K | 128K | — | — | — |
| Phi-4-mini phi-4-mini | 微软 | 128K | 4.096K | — | — | — |
| Phi-4-multimodal-instruct phi-4-multimodal-instruct | 微软 | 131.072K | 131.072K | — | — | — |
| WizardLM 2 8x22B wizardlm-2-8x22b | 微软 | 65.536K | 8K | — | — | — |
| Cydonia 24B V4.1 cydonia-24b-v4.1 | 德拉默 | 131.072K | 117.964K | — | — | — |
| Skyfall 36B V2 skyfall-36b-v2 | 德拉默 | 32.768K | 29.491K | — | — | — |
| UnslopNemo 12B unslopnemo-12b | 德拉默 | 1.024M | 819.2K | — | — | — |
| Inkling inkling | 思考机器 | 1.04858M | 1.04858M | ¥12.5 | ¥31.29 | 2 |
| Inkling Small inkling-small | 思考机器 | 1.04858M | 1.04858M | ¥3.88 | ¥9.63 | — |
| ReMM SLERP 13B remm-slerp-l2-13b | 恩迪95 | 6.144K | 5.529K | — | — | — |
| Gemma-SEA-LION-v4-27B-IT gemma-sea-lion-v4-27b-it | 新加坡人工智能 | 128K | 128K | — | — | — |
| Macaron V1 Tall macaron-v1-tall | 明德实验室 | 262.144K | 32.768K | — | — | — |
| Macaron V1 Venti macaron-v1-venti | 明德实验室 | 1.04858M | 131.072K | — | — | — |
| Laguna M.1 laguna-m.1 | 普尔赛德 | 262.144K | 32.768K | — | — | — |
| Laguna S 2.1 laguna-s-2.1 | 普尔赛德 | 1.04858M | 32.768K | — | — | — |
| Laguna XS 2.1 laguna-xs-2.1 | 普尔赛德 | 262.144K | 32.768K | — | — | — |
| Laguna XS.2 laguna-xs.2 | 普尔赛德 | 262.144K | 32.768K | — | — | — |
| AutoGLM Phone 9B Multilingual autoglm-phone-9b-multilingual | 智谱 | 65.536K | 65.536K | — | — | — |
| GLM 5.1 glm-5.1 | 智谱 | 200K | 131.072K | ¥6 | ¥24 | 24 |
| GLM 5.2 glm-5.2 | 智谱 | 1M | 131.072K | ¥8 | ¥10 | 24 |
| GLM-4.5 glm-4.5 | 智谱 | 131.072K | 98.304K | ¥4.01 | ¥14.71 | 5 |
| GLM-4.5-Air glm-4.5-air | 智谱 | 131.072K | 98.304K | ¥1.34 | ¥7.35 | 7 |
| GLM-4.5-Flash glm-4.5-flash | 智谱 | 131.072K | 98.304K | ¥0 | ¥0 | — |
| GLM-4.5V glm-4.5v | 智谱 | 64K | 16.384K | ¥4.01 | ¥12.03 | 3 |
| GLM-4.6 glm-4.6 | 智谱 | 204.8K | 131.072K | ¥4.01 | ¥14.71 | 6 |
| GLM-4.6V glm-4.6v | 智谱 | 128K | 32.768K | ¥2.01 | ¥6.02 | 3 |
| GLM-4.6V-Flash glm-4.6v-flash | 智谱 | 128K | 32.768K | ¥0 | ¥0 | — |
| GLM-4.7 glm-4.7 | 智谱 | 204.8K | 131.072K | ¥4.01 | ¥14.71 | 8 |
| GLM-4.7-Flash glm-4.7-flash | 智谱 | 200K | 131.072K | ¥0 | ¥0 | 2 |
| GLM-4.7-FlashX glm-4.7-flashx | 智谱 | 200K | 131.072K | ¥0.47 | ¥2.67 | 2 |
| GLM-5 glm-5 | 智谱 | 204.8K | 131.072K | ¥6.68 | ¥21.39 | 14 |
| GLM-5 Turbo glm-5-turbo | 智谱 | 200K | 131.072K | ¥8.02 | ¥26.74 | 8 |
| GLM-5V-Turbo glm-5v-turbo | 智谱 | 200K | 131.072K | ¥8.02 | ¥26.74 | 6 |
| Weaver (alpha) weaver | 曼瑟 | 8K | 6K | — | — | — |
| Kimi 2.6 kimi-k2.6 | 月之暗面 | 262.144K | 262.144K | ¥6.5 | ¥27 | 24 |
| Kimi K2 0711 kimi-k2 | 月之暗面 | 131.072K | 98.304K | — | — | 5 |
| Kimi K2 Instruct kimi-k2-instruct | 月之暗面 | 131.072K | 32.768K | — | — | 2 |
| Kimi K2 Instruct 0905 kimi-k2-0905 | 月之暗面 | 262.144K | 98.304K | — | — | 2 |
| Kimi K2 Thinking kimi-k2-thinking | 月之暗面 | 262.144K | 262.144K | — | — | 3 |
| Kimi K2 Thinking Turbo kimi-k2-thinking-turbo | 月之暗面 | 262.144K | 262.144K | — | — | 2 |
| Kimi K2.5 kimi-k2.5 | 月之暗面 | 262.144K | 262.144K | — | — | 17 |
| Kimi K2.7 Code kimi-k2.7-code | 月之暗面 | 262.144K | 262.144K | ¥6.35 | ¥26.74 | 24 |
| Kimi K2.7 Code Highspeed kimi-k2.7-code-highspeed | 月之暗面 | 262.144K | 262.144K | ¥12.7 | ¥53.48 | 5 |
| Kimi K2.8 Preview kimi-k2.8-preview | 月之暗面 | 1.04858M | — | — | — | 6 |
| Kimi K3.1 Pro kimi-k3.1-pro | 月之暗面 | 1.04858M | 131.072K | ¥13.37 | ¥66.85 | 24 |
| MythoMax L2 13B mythomax-l2-13b | 格里菲 | 4.096K | 3.2K | — | — | — |
| ALLaM-2-7b allam-2-7b | 沙特数据与人工智能管理局 | 4.096K | 4.096K | — | — | — |
| Ember-1 ember-1 | 烟花人工智能 | 1.04858M | 131.072K | — | — | — |
| Sonar sonar | 珀普莱克西蒂 | 128K | 4.096K | ¥6.68 | ¥6.68 | — |
| Sonar Deep Research sonar-deep-research | 珀普莱克西蒂 | 128K | 32.768K | ¥13.37 | ¥53.48 | — |
| Sonar Pro sonar-pro | 珀普莱克西蒂 | 200K | 8.192K | ¥20.05 | ¥100.27 | — |
| Sonar Reasoning Pro sonar-reasoning-pro | 珀普莱克西蒂 | 128K | 4.096K | ¥13.37 | ¥53.48 | — |
| Flint flint | 瑞克西夫 | 262.144K | 262.144K | — | — | — |
| Apertus 70B apertus-70b | 瑞士人工智能 | 65.536K | 8.192K | — | — | — |
| Apertus 8B apertus-8b | 瑞士人工智能 | 65.536K | 8.192K | — | — | — |
| Beam 1.0 501B A23B beam-1.0-501b-a23b | 瑞弗莱克申 | 1.04858M | 131.072K | — | — | — |
| Relace Apply 3 relace-apply-3 | 瑞莱斯 | 256K | 128K | — | — | — |
| Relace Search relace-search | 瑞莱斯 | 256K | 128K | — | — | — |
| Baichuan M2 32B baichuan-m2-32b | 百川智能 | 131.072K | 131.072K | — | — | — |
| CoBuddy cobuddy | 百度 | 131.072K | 65.536K | — | — | — |
| ERNIE 4.5 21B A3B ernie-4.5-21b-a3b | 百度 | 131.072K | 8K | — | — | — |
| ERNIE 4.5 300B A47B ernie-4.5-300b-a47b | 百度 | 131.072K | 12K | — | — | — |
| ERNIE 4.5 VL 424B A47B ernie-4.5-vl-424b-a47b | 百度 | 123K | 16K | — | — | — |
| Aya Expanse 32B c4ai-aya-expanse-32b | 科希尔 | 128K | 4K | ¥3.34 | ¥10.03 | 2 |
| Aya Expanse 8B c4ai-aya-expanse-8b | 科希尔 | 8K | 4K | — | — | 2 |
| Aya Vision 32B c4ai-aya-vision-32b | 科希尔 | 16K | 4K | — | — | 2 |
| Aya Vision 8B c4ai-aya-vision-8b | 科希尔 | 16K | 4K | — | — | 2 |
| Command A command-a | 科希尔 | 256K | 8.192K | — | — | — |
| Command A command-a-03-2025 | 科希尔 | 256K | 8K | ¥16.71 | ¥66.85 | 2 |
| Command A Plus command-a-plus-05-2026 | 科希尔 | 128K | 64K | ¥16.71 | ¥66.85 | — |
| Command A Reasoning command-a-reasoning-08-2025 | 科希尔 | 256K | 32K | ¥16.71 | ¥66.85 | — |
| Command A Translate command-a-translate-08-2025 | 科希尔 | 8K | 8K | ¥16.71 | ¥66.85 | — |
| Command A Vision command-a-vision-07-2025 | 科希尔 | 128K | 8K | ¥16.71 | ¥66.85 | — |
| Command R command-r-08-2024 | 科希尔 | 128K | 4K | ¥1 | ¥4.01 | 2 |
| Command R+ command-r-plus-08-2024 | 科希尔 | 128K | 4K | ¥16.71 | ¥66.85 | 2 |
| Command R7B command-r7b-12-2024 | 科希尔 | 128K | 4K | ¥0.25 | ¥1 | 2 |
| Command R7B Arabic command-r7b-arabic-02-2025 | 科希尔 | 128K | 4K | ¥0.25 | ¥1 | — |
| North Mini Code north-mini-code-1-0 | 科希尔 | 256K | 64K | ¥0 | ¥0 | — |
| North Small Translate north-small-translate-1-0 | 科希尔 | 16K | 16K | ¥0 | ¥0 | — |
| Tiny Aya Earth tiny-aya-earth | 科希尔 | 8K | 8K | — | — | — |
| Tiny Aya Fire tiny-aya-fire | 科希尔 | 8K | 8K | — | — | — |
| Tiny Aya Global tiny-aya-global | 科希尔 | 8K | 8K | — | — | — |
| Tiny Aya Water tiny-aya-water | 科希尔 | 8K | 8K | — | — | — |
| Dracarys Llama 3.1 70B Instruct dracarys-llama-3.1-70b-instruct | 算盘人工智能 | 131.072K | 131.072K | — | — | — |
| Codestral codestral-latest | 米斯特拉尔AI | 256K | 4.096K | ¥2.01 | ¥6.02 | — |
| Codestral 25.08 codestral-2508 | 米斯特拉尔AI | 128K | 8.192K | ¥2.01 | ¥6.02 | — |
| Codestral-22B-v0.1 codestral-22b-v0.1 | 米斯特拉尔AI | 32.768K | 8.192K | — | — | — |
| Devstral 2 devstral-2512 | 米斯特拉尔AI | 262.144K | 262.144K | ¥2.67 | ¥13.37 | — |
| Devstral Medium devstral-medium-2507 | 米斯特拉尔AI | 128K | 128K | ¥2.67 | ¥13.37 | — |
| Devstral Small devstral-small-2507 | 米斯特拉尔AI | 128K | 128K | ¥0.67 | ¥2.01 | — |
| Devstral Small 2 devstral-small-2 | 米斯特拉尔AI | 262.144K | 262.144K | — | — | — |
| Magistral Medium magistral-medium-latest | 米斯特拉尔AI | 128K | 16.384K | ¥13.37 | ¥33.42 | — |
| Magistral Small magistral-small-2506 | 米斯特拉尔AI | 131.072K | 8.192K | — | — | — |
| Magistral Small 1.2 magistral-small-2509 | 米斯特拉尔AI | 131.072K | 131.072K | — | — | — |
| Ministral 14B ministral-14b | 米斯特拉尔AI | 262.144K | 262.144K | — | — | — |
| Ministral 3 14B ministral-3-14b-instruct-2512 | 米斯特拉尔AI | 262.144K | 262.144K | ¥1.34 | ¥1.34 | — |
| Ministral 3 14B 2512 ministral-14b-2512 | 米斯特拉尔AI | 262.144K | 209.715K | ¥1.34 | ¥1.34 | — |
| Ministral 3 3B ministral-3-3b-instruct-2512 | 米斯特拉尔AI | 262.144K | 262.144K | ¥0.67 | ¥0.67 | — |
| Ministral 3 3B 2512 ministral-3b-2512 | 米斯特拉尔AI | 131.072K | 104.857K | ¥0.67 | ¥0.67 | — |
| Ministral 3 8B ministral-3-8b-instruct-2512 | 米斯特拉尔AI | 262.144K | 262.144K | ¥1 | ¥1 | — |
| Ministral 3 8B 2512 ministral-8b-2512 | 米斯特拉尔AI | 262.144K | 209.715K | ¥1 | ¥1 | — |
| Ministral 3B ministral-3b | 米斯特拉尔AI | 128K | 8.192K | — | — | — |
| Ministral 8B Instruct ministral-8b-instruct-2410 | 米斯特拉尔AI | 131.072K | 8.192K | — | — | — |
| Mistral 7B Instruct v0.3 mistral-7b-instruct-v0.3 | 米斯特拉尔AI | 32.768K | 32.768K | — | — | — |
| Mistral Embed mistral-embed | 米斯特拉尔AI | 8K | 3.072K | ¥0.67 | ¥0 | — |
| Mistral Large mistral-large | 米斯特拉尔AI | 128K | 102.4K | — | — | — |
| Mistral Large mistral-large-latest | 米斯特拉尔AI | 262.144K | 262.144K | ¥3.34 | ¥10.03 | 2 |
| Mistral Large 2.1 mistral-large-2411 | 米斯特拉尔AI | 131.072K | 16.384K | ¥13.37 | ¥40.11 | — |
| Mistral Large 2407 mistral-large-2407 | 米斯特拉尔AI | 131.072K | 104.857K | — | — | — |
| Mistral Large 3 mistral-large-2512 | 米斯特拉尔AI | 262.144K | 262.144K | ¥3.34 | ¥10.03 | — |
| Mistral Large 4 mistral-large-4 | 米斯特拉尔AI | 1.04858M | 262.144K | ¥9.09 | ¥27.94 | — |
| Mistral Medium mistral-medium-latest | 米斯特拉尔AI | 262.144K | 262.144K | ¥10.03 | ¥50.14 | — |
| Mistral Medium 3 mistral-medium-2505 | 米斯特拉尔AI | 131.072K | 131.072K | ¥2.67 | ¥13.37 | — |
| Mistral Medium 3.1 mistral-medium-3.1 | 米斯特拉尔AI | 131.072K | 104.857K | — | — | — |
| Mistral Medium 3.5 mistral-medium-2604 | 米斯特拉尔AI | 262.144K | 262.144K | ¥10.03 | ¥50.14 | — |
| Mistral Nemo mistral-nemo | 米斯特拉尔AI | 128K | 128K | ¥1 | ¥1 | — |
| Mistral Small mistral-small-latest | 米斯特拉尔AI | 256K | 256K | ¥1 | ¥4.01 | — |
| Mistral Small 3 mistral-small-24b-instruct-2501 | 米斯特拉尔AI | 32.768K | 16.384K | — | — | — |
| Mistral Small 3.1 24B mistral-small-3-1-24b-instruct-2503 | 米斯特拉尔AI | 128K | 16.384K | — | — | — |
| Mistral Small 3.2 mistral-small-2506 | 米斯特拉尔AI | 128K | 16.384K | ¥0.67 | ¥2.01 | — |
| Mistral Small 3.2 24B mistral-small-3.2-24b-instruct | 米斯特拉尔AI | 256K | 16.384K | — | — | — |
| Mistral Small 4 mistral-small-2603 | 米斯特拉尔AI | 256K | 256K | ¥1 | ¥4.01 | — |
| Mixtral 8x22B Instruct mixtral-8x22b-instruct | 米斯特拉尔AI | 65.536K | 52.428K | — | — | — |
| Mixtral 8x7B Instruct v0.1 mixtral-8x7b-instruct-v0.1 | 米斯特拉尔AI | 32.768K | 32.768K | — | — | — |
| Pixtral 12B pixtral-12b | 米斯特拉尔AI | 128K | 128K | ¥1 | ¥1 | — |
| Pixtral Large pixtral-large-latest | 米斯特拉尔AI | 128K | 128K | ¥13.37 | ¥40.11 | — |
| Pixtral Large (25.02) pixtral-large-2502 | 米斯特拉尔AI | 128K | 8.192K | — | — | — |
| Saba mistral-saba | 米斯特拉尔AI | 32.768K | 26.214K | — | — | — |
| Voxtral Mini 3B 2507 voxtral-mini-3b-2507 | 米斯特拉尔AI | 32.768K | 32.768K | — | — | — |
| Voxtral Small voxtral-small-latest | 米斯特拉尔AI | 32K | 32K | ¥0.67 | ¥2.67 | — |
| Voxtral Small 24B 2507 voxtral-small-24b-2507 | 米斯特拉尔AI | 32.768K | 32.768K | — | — | — |
| Viv Fast viv-fast | 维夫格里德 | 1M | 256K | — | — | — |
| Vision Large vision-large | 维斯帕克 | 1M | 65.536K | ¥49.27 | ¥147.8 | — |
| Vision Medium vision-medium | 维斯帕克 | 1M | 65.536K | ¥28.14 | ¥84.43 | — |
| Vision Small vision-small | 维斯帕克 | 1M | 65.536K | ¥7.02 | ¥21.12 | — |
| LongCat-2.0 longcat-2.0 | 美团 | 1M | 131.072K | — | — | 3 |
| LongCat-2.5-Preview longcat-2.5-preview | 美团 | 1M | 131.072K | — | — | 1 |
| Hy-MT2-1.8B hy-mt2-1.8b | 腾讯 | 8.192K | 4.096K | — | — | — |
| Hy-MT2-30B-A3B hy-mt2-30b-a3b | 腾讯 | 8.192K | 4.096K | — | — | — |
| Hy-MT2-7B hy-mt2-7b | 腾讯 | 8.192K | 4.096K | — | — | — |
| Hy3 hy3 | 腾讯 | 256K | 128K | — | — | 20 |
| Hy3 preview hy3-preview | 腾讯 | 256K | 64K | — | — | 3 |
| Hy4 Preview hy4-preview | 腾讯 | 1.024M | 64K | — | — | 20 |
| Llama 3.1 Nemotron 70B Instruct llama-3.1-nemotron-70b-instruct | 英伟达 | 128K | 8.192K | — | — | — |
| Llama 3.1 Nemotron Safety Guard 8B v3 llama-3.1-nemotron-safety-guard-8b-v3 | 英伟达 | 128K | 4.096K | — | — | — |
| Llama 3.1 Nemotron Ultra 253B llama-3.1-nemotron-ultra-253b | 英伟达 | 128K | 8.192K | — | — | — |
| Llama 3.3 Nemotron Super 49B v1 llama-3.3-nemotron-super-49b-v1 | 英伟达 | 131.072K | 131.072K | — | — | — |
| Llama 3.3 Nemotron Super 49B v1.5 llama-3.3-nemotron-super-49b-v1.5 | 英伟达 | 131.072K | 131.072K | — | — | — |
| Llama Nemotron Embed 1B v2 llama-nemotron-embed-1b-v2 | 英伟达 | 8.192K | 2.048K | — | — | — |
| Llama Nemotron Embed VL 1B v2 llama-nemotron-embed-vl-1b-v2 | 英伟达 | 10.24K | 2.048K | — | — | — |
| Llama Nemotron Rerank VL 1B v2 llama-nemotron-rerank-vl-1b-v2 | 英伟达 | 10.24K | 4.096K | — | — | — |
| Mistral Nemotron mistral-nemotron | 英伟达 | 128K | 8.192K | — | — | — |
| Nemotron 3 Content Safety nemotron-3-content-safety | 英伟达 | 128K | 4.096K | — | — | — |
| Nemotron 3 Nano 30B A3B nemotron-3-nano-30b-a3b | 英伟达 | 262.144K | 262.144K | — | — | — |
| Nemotron 3 Nano Omni 30B A3B Reasoning nemotron-3-nano-omni-30b-a3b-reasoning | 英伟达 | 256K | 65.536K | — | — | — |
| Nemotron 3 Super 120B A12B nemotron-3-super-120b-a12b | 英伟达 | 262.144K | 262.144K | — | — | — |
| Nemotron 3 Ultra 550B A55B nemotron-3-ultra-550b-a55b | 英伟达 | 1M | 128K | — | — | — |
| Nemotron 3.5 Content Safety nemotron-3.5-content-safety | 英伟达 | 128K | 8.192K | — | — | — |
| Nemotron 3.5 Lightning 30B A3B nemotron-3.5-lightning | 英伟达 | 262.144K | 262.144K | — | — | — |
| Nemotron 3.5 Super 120B A12B nemotron-3.5-super-120b-a12b | 英伟达 | 1.04858M | 131.072K | — | — | — |
| Nemotron 3.5 Super VL 120B A12B nemotron-3.5-super-vl-120b-a12b | 英伟达 | 1.04858M | 8.192K | — | — | — |
| Nemotron Cascade 2 30B A3B nemotron-cascade-2-30b-a3b | 英伟达 | 256K | 32.768K | — | — | — |
| Nemotron Content Safety Reasoning 4B nemotron-content-safety-reasoning-4b | 英伟达 | 128K | 4.096K | — | — | — |
| Nemotron Mini 4B Instruct nemotron-mini-4b-instruct | 英伟达 | 128K | 8.192K | — | — | — |
| Nemotron Nano 12B v2 VL nemotron-nano-12b-v2-vl | 英伟达 | 128K | 128K | — | — | — |
| Nemotron Nano 9B v2 nemotron-nano-9b-v2 | 英伟达 | 131.072K | 131.072K | — | — | — |
| Nemotron VoiceChat nemotron-voicechat | 英伟达 | 128K | 8.192K | — | — | — |
| Morph V3 Fast morph-v3-fast | 莫夫 | 81.92K | 38K | — | — | — |
| Morph V3 Large morph-v3-large | 莫夫 | 262.144K | 131.072K | — | — | — |
| Motif 3 motif-3 | 莫蒂夫科技 | 262.144K | 262.144K | — | — | — |
| Palmyra X4 palmyra-x4 | 莱特 | 128K | 4.096K | — | — | — |
| Palmyra X5 palmyra-x5 | 莱特 | 1M | 8.192K | — | — | — |
| LightOnOCR-3 0.8B lightonocr-3-0.8b | 莱顿人工智能 | 262.144K | 16.384K | — | — | — |
| Llama 3 8B Lunaris l3-lunaris-8b | 萨奥10K | 8.192K | 7.372K | — | — | — |
| Llama 3.1 Euryale 70B v2.2 l3.1-euryale-70b | 萨奥10K | 131.072K | 16.384K | — | — | — |
| Llama 3.3 Euryale 70B l3.3-euryale-70b | 萨奥10K | 131.072K | 16.384K | — | — | — |
| Sarvam 105B sarvam-105b | 萨尔瓦姆人工智能 | 131.072K | 131.072K | — | — | — |
| Sarvam 30B sarvam-30b | 萨尔瓦姆人工智能 | 128K | 128K | — | — | — |
| Sarvam-M sarvam-m | 萨尔瓦姆人工智能 | 32.768K | 32.768K | — | — | — |
| Uncensored dolphin-mistral-24b-venice-edition | 认知计算 | 128K | 8.192K | — | — | — |
| Hermes 2 Pro Llama 3 8B hermes-2-pro-llama-3-8b | 诺斯研究 | 8.192K | 8.192K | — | — | — |
| Hermes 3 405B Instruct hermes-3-llama-3.1-405b | 诺斯研究 | 131.072K | 16.384K | — | — | — |
| Hermes 3 70B Instruct hermes-3-llama-3.1-70b | 诺斯研究 | 131.072K | 16.384K | — | — | — |
| Hermes 4 405B hermes-4-405b | 诺斯研究 | 131.072K | 117.964K | — | — | — |
| Step 3.5 Flash step-3.5-flash | 阶跃星辰 | 256K | 256K | ¥0.67 | ¥2.01 | 1 |
| Step 3.5 Flash 2603 step-3.5-flash-2603 | 阶跃星辰 | 256K | 256K | ¥0.67 | ¥2.01 | — |
| Step 3.7 Flash step-3.7-flash | 阶跃星辰 | 256K | 256K | ¥1.34 | ¥7.69 | 3 |
| Step 5 Preview step-5-preview | 阶跃星辰 | 1M | 1M | ¥6.68 | ¥18.05 | 5 |
| Apodex 1.1 Mini apodex-1.1-mini | 阿波德克斯 | 262.144K | 262.144K | — | — | — |
| Trinity Large Preview trinity-large-preview | 阿西人工智能 | 524.288K | 262.144K | — | — | — |
| Trinity Large Thinking trinity-large-thinking | 阿西人工智能 | 524.288K | 262.144K | — | — | — |
| Trinity Mini trinity-mini | 阿西人工智能 | 131.072K | 131.072K | — | — | — |
| Trinity Nano Preview trinity-nano-preview | 阿西人工智能 | 131.072K | 131.072K | — | — | — |
| Qwen 3.8 Max Prime qwen3.8-max-prime | 阿里云 | 1M | 131.072K | — | — | — |
| Qwen Flash qwen-flash | 阿里云 | 1M | 32.768K | ¥0.33 | ¥2.67 | 4 |
| Qwen Max qwen-max | 阿里云 | 32.768K | 8.192K | ¥10.7 | ¥42.78 | 6 |
| Qwen MT Plus qwen-mt-plus | 阿里云 | 16.384K | 8.192K | ¥16.44 | ¥49.27 | 3 |
| Qwen Plus qwen-plus | 阿里云 | 1M | 32.768K | ¥2.67 | ¥8.02 | 5 |
| Qwen Turbo qwen-turbo | 阿里云 | 1M | 16.384K | ¥0.33 | ¥1.34 | 3 |
| Qwen-Image-2.1 qwen-image-2.1 | 阿里云 | 8.192K | — | — | — | 2 |
| Qwen-Omni Turbo qwen-omni-turbo | 阿里云 | 32.768K | 2.048K | ¥0.47 | ¥1.8 | 2 |
| Qwen-VL Max qwen-vl-max | 阿里云 | 131.072K | 8.192K | ¥5.35 | ¥21.39 | 3 |
| Qwen-VL Plus qwen-vl-plus | 阿里云 | 131.072K | 8.192K | ¥1.4 | ¥4.21 | 2 |
| Qwen2.5 7B Instruct qwen2.5-7b-instruct | 阿里云 | 131.072K | 8.192K | — | — | 3 |
| Qwen2.5-Coder-0.5B qwen2.5-coder-0.5b | 阿里云 | 32.768K | 8.192K | — | — | — |
| Qwen2.5-Coder-32B-Instruct qwen2.5-coder-32b-instruct | 阿里云 | 131.072K | 8.192K | — | — | 2 |
| Qwen2.5-VL 72B Instruct qwen2-5-vl-72b-instruct | 阿里云 | 131.072K | 8.192K | ¥18.72 | ¥56.15 | — |
| Qwen3 235B-A22B qwen3-235b-a22b | 阿里云 | 131.072K | 16.384K | ¥4.68 | ¥18.72 | 4 |
| Qwen3 235B-A22B Instruct 2507 qwen3-235b-a22b-instruct-2507 | 阿里云 | 262.144K | 16.384K | — | — | 3 |
| Qwen3 235B-A22B Thinking 2507 qwen3-235b-a22b-thinking-2507 | 阿里云 | 262.144K | 81.92K | — | — | 2 |
| Qwen3 30B A3B qwen3-30b-a3b | 阿里云 | 131.072K | 16.384K | — | — | 4 |
| Qwen3 30B-A3B Instruct 2507 qwen3-30b-a3b-instruct-2507 | 阿里云 | 262.144K | 16.384K | — | — | 3 |
| Qwen3 32B qwen3-32b | 阿里云 | 131.072K | 16.384K | ¥4.68 | ¥18.72 | 3 |
| Qwen3 8B qwen3-8b | 阿里云 | 32.768K | 32.768K | ¥1.2 | ¥4.68 | 3 |
| Qwen3 Coder Flash qwen3-coder-flash | 阿里云 | 1M | 65.536K | ¥2.01 | ¥10.03 | 4 |
| Qwen3 Coder Next qwen3-coder-next | 阿里云 | 262.144K | 65.536K | — | — | 3 |
| Qwen3 Coder Plus qwen3-coder-plus | 阿里云 | 1.04858M | 65.536K | ¥6.68 | ¥33.42 | 4 |
| Qwen3 Max qwen3-max | 阿里云 | 262.144K | 65.536K | ¥8.02 | ¥40.11 | 6 |
| Qwen3 Max Preview qwen3-max-preview | 阿里云 | 262.144K | 32.768K | — | — | 3 |
| Qwen3 Omni 30B A3B Thinking qwen3-omni-30b-a3b-thinking | 阿里云 | 65.536K | 16.384K | — | — | — |
| Qwen3 VL 235B A22B Instruct qwen3-vl-235b-a22b-instruct | 阿里云 | 131.072K | 32.768K | — | — | 3 |
| Qwen3 VL 235B A22B Thinking qwen3-vl-235b-a22b-thinking | 阿里云 | 131.072K | 32.768K | — | — | 3 |
| Qwen3 VL 30B A3B Instruct qwen3-vl-30b-a3b-instruct | 阿里云 | 262.144K | 32.768K | — | — | 2 |
| Qwen3 VL Flash (Alibaba Cloud) qwen3-vl-flash | 阿里云 | 262.144K | 32.768K | — | — | 5 |
| Qwen3-Coder 30B-A3B Instruct qwen3-coder-30b-a3b-instruct | 阿里云 | 262.144K | 65.536K | ¥3.01 | ¥15.04 | 2 |
| Qwen3-Coder 480B-A35B Instruct qwen3-coder-480b-a35b-instruct | 阿里云 | 262.144K | 65.536K | ¥10.03 | ¥50.14 | 3 |
| Qwen3-Next 80B-A3B (Thinking) qwen3-next-80b-a3b-thinking | 阿里云 | 262.144K | 32.768K | ¥3.34 | ¥40.11 | 3 |
| Qwen3-Next 80B-A3B Instruct qwen3-next-80b-a3b-instruct | 阿里云 | 262.144K | 32.768K | ¥3.34 | ¥13.37 | 3 |
| Qwen3-VL Plus qwen3-vl-plus | 阿里云 | 262.144K | 32.768K | ¥1.34 | ¥10.7 | 5 |
| Qwen3.5 0.8B qwen3.5-0.8b | 阿里云 | 262.144K | 81.92K | — | — | — |
| Qwen3.5 122B-A10B qwen3.5-122b-a10b | 阿里云 | 262.144K | 65.536K | ¥2.67 | ¥21.39 | 6 |
| Qwen3.5 27B qwen3.5-27b | 阿里云 | 262.144K | 65.536K | ¥2.01 | ¥16.04 | 6 |
| Qwen3.5 2B qwen3.5-2b | 阿里云 | 262.144K | 81.92K | — | — | — |
| Qwen3.5 35B-A3B qwen3.5-35b-a3b | 阿里云 | 262.144K | 65.536K | ¥1.67 | ¥13.37 | 6 |
| Qwen3.5 35B-A3B Base qwen3.5-35b-a3b-base | 阿里云 | 262.144K | 65.536K | — | — | — |
| Qwen3.5 397B-A17B qwen3.5-397b-a17b | 阿里云 | 262.144K | 65.536K | ¥4.01 | ¥24.07 | 6 |
| Qwen3.5 4B qwen3.5-4b | 阿里云 | 262.144K | 81.92K | — | — | — |
| Qwen3.5 9B qwen3.5-9b | 阿里云 | 262.144K | 65.536K | — | — | — |
| Qwen3.5 9B Base qwen3.5-9b-base | 阿里云 | 262.144K | 65.536K | — | — | — |
| Qwen3.5 Flash qwen3.5-flash | 阿里云 | 1M | 65.536K | ¥0.67 | ¥2.67 | 7 |
| Qwen3.5 Plus qwen3.5-plus | 阿里云 | 1M | 65.536K | ¥2.67 | ¥16.04 | 10 |
| Qwen3.6 27B qwen3.6-27b | 阿里云 | 262.144K | 65.536K | ¥4.01 | ¥24.07 | 6 |
| Qwen3.6 35B A3B qwen3.6-35b-a3b | 阿里云 | 262.144K | 65.536K | ¥2.51 | ¥15.04 | 6 |
| Qwen3.6 Flash qwen3.6-flash | 阿里云 | 1M | 65.536K | ¥1.67 | ¥10.03 | 6 |
| Qwen3.6 Max Preview qwen3.6-max-preview | 阿里云 | 262.144K | 65.536K | ¥8.69 | ¥52.14 | 5 |
| Qwen3.6 Plus qwen3.6-plus | 阿里云 | 1M | 65.536K | ¥3.34 | ¥20.05 | 12 |
| Qwen3.7 Flash qwen3.7-flash | 阿里云 | 1M | 131.072K | ¥0.2 | ¥0.87 | 4 |
| Qwen3.7 Max qwen3.7-max | 阿里云 | 1M | 131.072K | ¥12 | ¥36 | 24 |
| Qwen3.7 Plus qwen3.7-plus | 阿里云 | 1M | 64K | ¥2.67 | ¥10.7 | 17 |
| Qwen3.8 2.4T A95B qwen3.8-2.4t-a95b | 阿里云 | 262.144K | 131.072K | — | — | — |
| Qwen3.8 27B qwen3.8-27b | 阿里云 | 262.144K | 32.768K | — | — | 4 |
| Qwen3.8 Flash qwen3.8-flash | 阿里云 | 1M | 131.072K | ¥1 | ¥3.14 | 24 |
| Qwen3.8 Flash Next qwen3.8-flash-next | 阿里云 | 262.144K | 131.072K | — | — | 3 |
| Qwen3.8 Max qwen3.8-max | 阿里云 | 1M | 131.072K | ¥13.37 | ¥40.11 | 24 |
| Qwen3.8 Max 0902 qwen3.8-max-0902 | 阿里云 | 1M | 131.072K | — | — | 5 |
| Qwen3.8 Max Preview qwen3.8-max-preview | 阿里云 | 1M | 131.072K | — | — | 3 |
| Qwen3.8 Omni Flash qwen3.8-omni-flash | 阿里云 | 1M | 131.072K | ¥1 | ¥3.14 | 3 |
| QwQ 32B qwq-32b | 阿里云 | 131.072K | 8.192K | — | — | 3 |
| QwQ Plus qwq-plus | 阿里云 | 131.072K | 8.192K | ¥5.35 | ¥16.04 | 2 |
| Reka Edge reka-edge | 雷卡人工智能 | 16.384K | 14.745K | — | — | — |
| Reka Flash 3 reka-flash-3 | 雷卡人工智能 | 65.536K | 58.982K | — | — | — |
| PaddleOCR VL paddleocr-vl | 飞桨 | 131.072K | 16.384K | — | — | — |
Missing values mean the snapshot does not record them; they are not zero. To check whether a relay actually serves a model, use the seven-check detection. The Chinese directory is the source of record: 模型库.