제공자 · 2026-06-29
vercel
| 모델 | 입력 / 1M | 출력 / 1M | 컨텍스트 | 제공자 | 태그 |
|---|---|---|---|---|---|
| Nova Micro | $0.035 | $0.140 | 128K | 1 | tools |
| Trinity Mini | $0.045 | $0.150 | 131K | 1 | — |
| Nova Lite | $0.060 | $0.240 | 300K | 1 | tools · vision |
| Trinity Large Thinking | $0.250 | $0.900 | 262K | 1 | tools · reasoning · open-weights |
| Trinity Large Preview | $0.250 | $1.00 | 131K | 1 | tools |
| Nova 2 Lite | $0.300 | $2.50 | 1M | 1 | reasoning · vision |
| Nova Pro | $0.800 | $3.20 | 300K | 1 | tools · vision |
| Interfaze Beta | $1.50 | $3.50 | 1M | 1 | reasoning · vision |
| Fugu Ultra | $5.00 | $30.00 | 1M | 1 | tools · reasoning · vision |
| Arrow 1.1 | 미공개 | 미공개 | 131K | 1 | — |
| Flux Schnell | 미공개 | 미공개 | 512 | 1 | — |
| Kling v2.5 Turbo Image-to-Video | 미공개 | 미공개 | Unknown | 1 | — |
| Kling v2.5 Turbo Text-to-Video | 미공개 | 미공개 | Unknown | 1 | — |
| Kling v2.6 Image-to-Video | 미공개 | 미공개 | Unknown | 1 | — |
| Kling v2.6 Motion Control | 미공개 | 미공개 | Unknown | 1 | — |
| Kling v2.6 Text-to-Video | 미공개 | 미공개 | Unknown | 1 | — |
| Kling v3.0 Image-to-Video | 미공개 | 미공개 | Unknown | 1 | — |
| Kling v3.0 Motion Control | 미공개 | 미공개 | Unknown | 1 | — |
| Kling v3.0 Text-to-Video | 미공개 | 미공개 | Unknown | 1 | — |
| Titan Text Embeddings V2 | 미공개 | 미공개 | 8K | 1 | — |
| Ministral 3B (latest)파생 | $0.040 | $0.040 | 128K | 1 | tools · open-weights |
| Ministral 8B (latest)파생 | $0.100 | $0.100 | 128K | 1 | tools · open-weights |
| Qwen3-14B파생 | $0.120 | $0.240 | 41K | 1 | tools · reasoning |
| Devstral Small 1.1파생 | $0.100 | $0.300 | 128K | 1 | tools |
| Devstral Small 2파생 | $0.100 | $0.300 | 256K | 1 | tools · vision |
| Ministral 14B파생 | $0.200 | $0.200 | 256K | 1 | vision |
| Mistral Small (latest)파생 | $0.100 | $0.300 | 32K | 1 | tools · vision · open-weights |
| Qwen3-30B-A3B파생 | $0.120 | $0.500 | 41K | 1 | tools · reasoning |
| Nvidia Nemotron Nano 12B V2 VL파생 | $0.200 | $0.600 | 131K | 1 | tools · reasoning · vision |
| Qwen 3.32B파생 | $0.160 | $0.640 | 128K | 1 | tools · reasoning |
| Qwen3 235B A22B Instruct 2507파생 | $0.220 | $0.880 | 262K | 1 | tools · reasoning |
| Codestral (latest)파생 | $0.300 | $0.900 | 256K | 1 | tools · open-weights |
| Mistral Large 3파생 | $0.500 | $1.50 | 256K | 1 | vision |
| Qwen3 VL Instruct파생 | $0.400 | $1.60 | 131K | 1 | tools · vision · open-weights |
| Seed 1.6파생 | $0.250 | $2.00 | 256K | 1 | tools · reasoning · vision |
| Seed 1.8파생 | $0.250 | $2.00 | 256K | 1 | tools · reasoning · vision |
| Mistral Medium 3.1파생 | $0.400 | $2.00 | 128K | 1 | tools · vision |
| Devstral 2파생 | $0.400 | $2.00 | 256K | 1 | tools |
| MiniMax M2.1 Lightning파생 | $0.300 | $2.40 | 205K | 1 | tools · reasoning |
| GPT-Realtime mini파생 | $0.600 | $2.40 | Unknown | 1 | — |
| Gemini 3.1 Flash Image (Nano Banana 2)파생 | $0.500 | $3.00 | 131K | 1 | reasoning · vision |
| Grok 4.20 Beta Non-Reasoning파생 | $1.25 | $2.50 | 2M | 1 | tools · vision |
| Grok 4.20 Multi Agent Beta파생 | $1.25 | $2.50 | 2M | 1 | tools · reasoning · vision |
| Grok 4.20 Beta Reasoning파생 | $1.25 | $2.50 | 2M | 1 | tools · reasoning · vision |
| Qwen3 VL Thinking파생 | $0.400 | $4.00 | 131K | 1 | tools · reasoning · vision · open-weights |
| Qwen3 235B A22B Thinking 2507파생 | $0.400 | $4.00 | 131K | 1 | tools · reasoning · vision |
| Magistral Medium (latest)파생 | $2.00 | $5.00 | 128K | 1 | tools · reasoning · open-weights |
| Pixtral Large (latest)파생 | $2.00 | $6.00 | 128K | 1 | tools · vision · open-weights |
| Qwen 3.6 Max Preview파생 | $1.30 | $7.80 | 240K | 1 | tools · reasoning · open-weights |
| GPT 5.1 Thinking파생 | $1.25 | $10.00 | 400K | 1 | tools · reasoning · vision |
| GPT-5.1 Instant파생 | $1.25 | $10.00 | 128K | 1 | tools · vision |
| GLM 5.2 Fast파생 | $3.00 | $10.25 | 1M | 1 | tools · reasoning |
| Nano Banana Pro (Gemini 3 Pro Image)파생 | $2.00 | $12.00 | 66K | 1 | — |
| GPT-Realtime-1.5파생 | $4.00 | $16.00 | Unknown | 1 | — |
| gpt-realtime-2파생 | $4.00 | $24.00 | Unknown | 1 | — |
| Codestral Embed파생 | 미공개 | 미공개 | 8K | 1 | — |
| Cohere Rerank 3.5파생 | 미공개 | 미공개 | 4K | 1 | — |
| Cohere Rerank 4 Fast파생 | 미공개 | 미공개 | 32K | 1 | — |
| Cohere Rerank 4 Pro파생 | 미공개 | 미공개 | 32K | 1 | — |
| Embed v4.0파생 | 미공개 | 미공개 | 128K | 1 | — |
| Gemini Embedding 2파생 | 미공개 | 미공개 | Unknown | 1 | — |
| GPT-4o mini Transcribe파생 | $1.25 | $5.00 | Unknown | 1 | — |
| GPT-4o Transcribe파생 | $2.50 | $10.00 | Unknown | 1 | — |
| Grok Imagine Video 1.5파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Grok Imagine Video 1.5 Preview파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Grok STT파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Grok TTS파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Grok Voice Think Fast 1.0파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Imagen 4파생 | 미공개 | 미공개 | 480 | 1 | — |
| Imagen 4 Fast파생 | 미공개 | 미공개 | 480 | 1 | — |
| Imagen 4 Ultra파생 | 미공개 | 미공개 | 480 | 1 | — |
| Seedance 2.0파생 | 미공개 | 미공개 | Unknown | 1 | vision |
| Seedance 2.0 Fast파생 | 미공개 | 미공개 | Unknown | 1 | vision |
| Seedance v1.0 Pro파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Seedance v1.0 Pro Fast파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Seedance v1.5 Pro파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Seedream 4.0파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Seedream 4.5파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Seedream 5.0 Lite파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Text Embedding 005파생 | 미공개 | 미공개 | 8K | 1 | — |
| Text Multilingual Embedding 002파생 | 미공개 | 미공개 | 8K | 1 | — |
| TTS-1파생 | 미공개 | 미공개 | Unknown | 1 | — |
| TTS-1 HD파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Veo 3.0파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Veo 3.0 Fast Generate파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Veo 3.1파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Veo 3.1 Fast Generate파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Wan v2.5 Text-to-Video Preview파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Wan v2.6 Image-to-Video파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Wan v2.6 Image-to-Video Flash파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Wan v2.6 Reference-to-Video파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Wan v2.6 Reference-to-Video Flash파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Wan v2.6 Text-to-Video파생 | 미공개 | 미공개 | Unknown | 1 | — |
| Whisper파생 | 미공개 | 미공개 | Unknown | 1 | — |
Frequently asked questions
How many AI models does vercel offer?
We track 20 canonical vercel models plus 74 community fine-tunes / derivatives (excluded from the main table). The list is recomputed daily.
Which vercel model is the cheapest?
Nova Micro is currently the lowest-priced vercel model, at $0.035 per 1M input tokens and $0.140 per 1M output tokens. For the full apples-to-apples list, see /pricing/cheapest-llm-api.
Which vercel model has the largest context window?
Nova 2 Lite leads at 1M tokens. This is the total of prompt + completion.
Which vercel models support tool calling?
Multiple vercel models support tool calling, with Nova Micro being a popular pick. The capability column in the table above marks every model with vercel tool-calling support.
Which vercel models accept image input?
Nova Lite accepts image input. Other vision-capable vercel models are tagged 'vision' in the table above. See /capabilities/vision for a cross-vendor comparison.
What are the best alternatives to vercel?
Depends on the use case. For raw cost savings, look at /pricing/cheapest-llm-api. For agent-oriented workloads, /best/best-ai-model-for-agents. For long-document workflows, /best/best-long-context-llm.
How fresh is this vercel pricing data?
Daily. Our pipeline syncs every morning and rebuilds these pages on data change, so list-price moves and new model releases land within roughly 24 hours.
Explore more
Top vercel models
- Nova Micro$0.04 in / $0.14 out
- Trinity Mini$0.04 in / $0.15 out
- Nova Lite$0.06 in / $0.24 out
- Trinity Large Thinking$0.25 in / $0.90 out
- Trinity Large Preview$0.25 in / $1.00 out
Browse by use case
Browse by capability
마지막 업데이트:
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.