> ## Documentation Index
> Fetch the complete documentation index at: https://docs.together.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Available models

> Browse the catalog of available models for instant inference.

Serverless models are the fastest way to run inference on Together. You call any supported model through a shared per-token API, with no provisioning, no replicas to size, and no minimum cost. Pay only for the tokens you process.

## Models

If you're not sure which model to use, see [Recommended models](/docs/inference/recommended-models) for our picks by use case.

<Columns cols={4}>
  <Card title="Chat" icon="message-circle" horizontal href="#chat-models" />

  <Card title="Image" icon="photo" horizontal href="#image-models" />

  <Card title="Vision" icon="eye" horizontal href="#vision-models" />

  <Card title="Video" icon="video" horizontal href="#video-models" />

  <Card title="Audio" icon="volume" horizontal href="#audio-models" />

  <Card title="Embedding" icon="vector-bezier-2" horizontal href="#embedding-models" />

  <Card title="Rerank" icon="arrows-sort" horizontal href="#rerank-models" />

  <Card title="Moderation" icon="shield-check" horizontal href="#moderation-models" />
</Columns>

<Note>
  Serverless and dedicated model inference support different sets of models. See the [dedicated model inference catalog](/docs/dedicated-endpoints/models) for details.
</Note>

For rate limits and pricing, see the [Serverless overview](/docs/serverless/overview).

## Chat models

| Organization | Model name | API model string | Context length | Input pricing (per 1M tokens) | Cached input pricing (per 1M tokens) | Output pricing (per 1M tokens) | Quantization | Function calling | Structured outputs |
| :- | :- | :- | :- | :- | :- | :- | :- | :- | :- |
| Thinking Machines | Inkling | thinkingmachines/Inkling | 524288 | \$1.00 | \$0.17 | \$4.05 | NVFP4 | Yes | Yes |
| Minimax | Minimax M3 | MiniMaxAI/MiniMax-M3 | 524288 | \$0.30 | \$0.06 | \$1.20 | FP4 | Yes | Yes |
| Qwen | Qwen3.8-2.4T-A95B | Qwen/Qwen3.8-2.4T-A95B | - | \$2.00 | \$0.50 | \$6.00 | FP4 | - | - |
| Qwen | Qwen3.7 Max | Qwen/Qwen3.7-Max | - | \$1.50 | \$0.50 | \$4.50 | - | - | - |
| Qwen | Qwen3.6 Plus | Qwen/Qwen3.6-Plus | 1000000 | \$0.50 | - | \$3.00 | - | - | - |
| Qwen | Qwen3.5 9B | Qwen/Qwen3.5-9B | 262144 | \$0.17 | - | \$0.25 | FP8 | Yes | Yes |
| Moonshot | Kimi K3 | moonshotai/Kimi-K3 | 1048576 | \$3.00 | \$0.30 | \$15.00 | - | Yes | Yes |
| Z.ai | GLM-5.3 | zai-org/GLM-5.3 | 1048575 | \$1.40 | \$0.26 | \$4.40 | FP4 | Yes | Yes |
| Z.ai | GLM-5.3 Flash | zai-org/GLM-5.3-Flash | 1048575 | \$0.15 | \$0.03 | \$0.50 | FP8 | Yes | Yes |
| Z.ai | GLM-5.2 | zai-org/GLM-5.2 | 1048575 | \$1.40 | \$0.26 | \$4.40 | FP4 | Yes | Yes |
| OpenAI | GPT-OSS 120B | openai/gpt-oss-120b | 131072 | \$0.15 | - | \$0.60 | MXFP4 | Yes | Yes |
| DeepSeek | DeepSeek-V4-Flash-0731 | deepseek-ai/DeepSeek-V4-Flash-0731 | 1048576 | \$0.14 | \$0.03 | \$0.28 | FP4 | Yes | Yes |
| DeepSeek | DeepSeek V4 Pro 0813 | deepseek-ai/DeepSeek-V4-Pro-0813 | 1048576 | \$1.32 | \$0.13 | \$3.96 | NVFP4 | Yes | Yes |
| Meta | Llama 3.3 70B Instruct Turbo | meta-llama/Llama-3.3-70B-Instruct-Turbo | 131072 | \$1.04 | - | \$1.04 | FP8 | Yes | Yes |
| Qwen | Qwen3.7 Plus | Qwen/Qwen3.7-Plus | 1000000 | \$0.32 | - | \$1.28 | - | - | - |
| Prism ML | Ternary Bonsai 27B | Prism-ML/Ternary-Bonsai-27B | 262144 | Free | - | Free | - | - | - |
| Meta | Muse Glimmer 30B | meta-models/Muse-Glimmer-30B | 131072 | \$0.35 | \$0.04 | \$1.50 | FP8 | - | - |
| Qwen | Qwen3.8 Flash | Qwen/Qwen3.8-Flash | 1000000 | \$0.09 | - | \$0.282 | - | - | - |
| DeepSeek | DeepSeek V4.1 Flash | deepseek-ai/DeepSeek-V4.1-Flash | 1000000 | \$0.30 | \$0.006 | \$1.20 | FP8 | Yes | Yes |
| Together AI | Tev1 4B Experimental | together/Tev1-4B-experimental | 32768 | \$0.042 | - | Free | - | - | - |

**Chat model examples**

* [PDF to chat app](https://www.pdftochat.com/): Chat with your PDFs (blogs, textbooks, papers).
* [Open deep research notebook](https://github.com/togethercomputer/together-cookbook/blob/main/agents/Together_Open_Deep_Research_CookBook.ipynb): Generate long form reports using a single prompt.
* [Fine-tuning chat models notebook](https://github.com/togethercomputer/together-cookbook/blob/main/fine-tuning/Finetuning_Guide.ipynb): Tune language models for conversation.
* [Building agents](https://github.com/togethercomputer/together-cookbook/tree/main/agents): Agent workflows with language models.

## Image models

Use our [Images](/reference/post-images-generations) endpoint for image models. Calling image models requires a positive credit balance.

<Note>
  Prices for models billed by `image` are estimates, not rates. These models pass through the provider's own per-request charge, which varies with the resolution, quality, and other parameters you send. Models billed by `megapixel` use the [formula below](#per-megapixel-cost-formula). For more details, see [How image models bill](/docs/serverless/overview#how-image-models-bill).
</Note>

| Organization | Model name | Model string for API | Unit | Price | Output per \$1 |
| :- | :- | :- | :- | :- | :- |
| Google | Flash Image 2.5 (Nano Banana) | google/flash-image-2.5 | `image` | \$0.039+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 26 images |
| Google | Gemini 3 Pro Image (Nano Banana Pro) | google/gemini-3-pro-image | `image` | \$0.134 at 1K or 2K ([varies](/docs/serverless/overview#how-image-models-bill)) | 7.5 images |
| Black Forest Labs | Flux1.1 \[pro] | black-forest-labs/FLUX.1.1-pro | `megapixel` | \$0.04 | 25 megapixels |
| Black Forest Labs | Flux.1 Kontext \[pro] | black-forest-labs/FLUX.1-kontext-pro | `megapixel` | \$0.04 | 25 megapixels |
| Black Forest Labs | Flux.1 Kontext \[max] | black-forest-labs/FLUX.1-kontext-max | `megapixel` | \$0.08 | 12 megapixels |
| Black Forest Labs | FLUX.2 \[pro] | black-forest-labs/FLUX.2-pro | `image` | \$0.03+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 33 images |
| Black Forest Labs | FLUX.2 \[dev] | black-forest-labs/FLUX.2-dev | `image` | \$0.0154+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 65 images |
| Black Forest Labs | FLUX.2 \[flex] | black-forest-labs/FLUX.2-flex | `image` | \$0.03+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 33 images |
| ByteDance | Seedream 3.0 | ByteDance-Seed/Seedream-3.0 | `image` | \$0.018+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 56 images |
| ByteDance | Seedream 4.0 | ByteDance-Seed/Seedream-4.0 | `image` | \$0.03+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 33 images |
| ByteDance | Seedream 5.0 Lite | ByteDance/Seedream-5.0-lite | `image` | \$0.035+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 29 images |
| Qwen | Qwen Image | Qwen/Qwen-Image | `image` | \$0.0058+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 172 images |
| RunDiffusion | Juggernaut Pro Flux | RunDiffusion/Juggernaut-pro-flux | `image` | \$0.0049+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 204 images |
| RunDiffusion | Juggernaut Lightning Flux | Rundiffusion/Juggernaut-Lightning-Flux | `image` | \$0.0017+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 588 images |
| Ideogram | Ideogram 3.0 | ideogram/ideogram-3.0 | `image` | \$0.06+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 17 images |
| Stability AI | SD XL | stabilityai/stable-diffusion-xl-base-1.0 | `image` | \$0.0019+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 526 images |
| Black Forest Labs | FLUX.2 \[max] | black-forest-labs/FLUX.2-max | `megapixel` | \$0.07 at 50 steps | 14 megapixels |
| Google | Gemini 3.1 Flash Image (Nano Banana 2) | google/flash-image-3.1 | `image` | \$0.04657 at 512×512 ([varies](/docs/serverless/overview#how-image-models-bill)) | 21 images |
| OpenAI | GPT Image 1.5 | openai/gpt-image-1.5 | `image` | \$0.034+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 29 images |
| Qwen | Qwen Image 2.0 | Qwen/Qwen-Image-2.0 | `image` | \$0.035+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 29 images |
| Qwen | Qwen Image 2.0 Pro | Qwen/Qwen-Image-2.0-Pro | `image` | \$0.075+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 13 images |
| Wan-AI | Wan 2.6 Image | Wan-AI/Wan2.6-image | `image` | \$0.03+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 33 images |
| ideogram | Ideogram 4.0 | ideogram/ideogram-4.0 | `image` | \$0.06+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 17 images |
| OpenAI | GPT Image 2 | openai/gpt-image-2 | `image` | \$0.053+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 19 images |
| Google | Gemini 3.1 Flash-Lite Image (Nano Banana 2 Lite) | google/flash-image-3.1-lite | `image` | \$0.069+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 14 images |
| Pruna AI | P-Image-Ideogram | prunaai/p-image-ideogram | `image` | \$0.00225+ ([varies](/docs/serverless/overview#how-image-models-bill)) | 444 images |

### **Image model examples**

* [Blinkshot.io](https://www.blinkshot.io/): A realtime AI image playground built with Flux Schnell.
* [Logo creator](https://www.logo-creator.io/): A logo generator that creates professional logos in seconds using Flux Pro 1.1.
* [PicMenu](https://www.picmenu.co/): A menu visualizer that takes a restaurant menu and generates nice images for each dish.

### Per-megapixel cost formula

This applies only to models whose **Unit** column reads `megapixel`. It does not describe how the others are billed.

For these models, cost depends on the size of the generated image in megapixels and on the number of steps used, if that number exceeds the default steps shown alongside the unit.

* **Default pricing:** The listed price is the rate for one megapixel at the default number of steps.
* **Using more or fewer steps:** Costs are adjusted based on the number of steps used **only if you go above the default steps**. If you use more steps, the cost increases proportionally using the formula below. If you use fewer steps, the cost *does not* decrease and is based on the default rate.

Here's a formula to calculate cost:

Cost = MP × Price per MP × (Steps ÷ Default Steps)

Where:

* MP = (Width × Height ÷ 1,000,000).
* Price per MP = the value in the **Price** column.
* Steps = The number of steps used for the image generation. This is only factored in if going above default steps.

Resolution dominates that formula. At \$0.04 per megapixel, a 1024×1024 image (1.05 MP) costs about \$0.042, while a 4096×4096 image (16.8 MP) costs about \$0.67.

### **Gemini 3 Pro Image** pricing

Gemini 3 Pro Image's cost tracks the resolution you request. The catalog above quotes the 1K and 2K estimate of about \$0.134 per image. At 4K it is about \$0.24 per image.

Supported dimensions: 1K: 1024×1024 (1:1), 1264×848 (3:2), 848×1264 (2:3), 1200×896 (4:3), 896×1200 (3:4), 928×1152 (4:5), 1152×928 (5:4), 768×1376 (9:16), 1376×768 (16:9), 1548×672 or 1584×672 (21:9).

2K: 2048×2048 (1:1), 2528×1696 (3:2), 1696×2528 (2:3), 2400×1792 (4:3), 1792×2400 (3:4), 1856×2304 (4:5), 2304×1856 (5:4), 1536×2752 (9:16), 2752×1536 (16:9), 3168×1344 (21:9).

4K: 4096×4096 (1:1), 5096×3392 or 5056×3392 (3:2), 3392×5096 or 3392×5056 (2:3), 4800×3584 (4:3), 3584×4800 (3:4), 3712×4608 (4:5), 4608×3712 (5:4), 3072×5504 (9:16), 5504×3072 (16:9), 6336×2688 (21:9).

## Vision models

If you're not sure which vision model to use, start with **Qwen3.5 9B** (`Qwen/Qwen3.5-9B`). For model-specific rate limits, see [Rate limits](/docs/serverless/rate-limits).

| Organization | Model name | API model string | Context length | Input pricing (per 1M tokens) | Output pricing (per 1M tokens) |
| :- | :- | :- | :- | :- | :- |
| Qwen | Qwen3.5 9B | Qwen/Qwen3.5-9B | 262144 | \$0.17 | \$0.25 |
| Minimax | Minimax M3 | MiniMaxAI/MiniMax-M3 | 524288 | \$0.30 | \$1.20 |
| Moonshot | Kimi K3 | moonshotai/Kimi-K3 | 1048576 | \$3.00 | \$15.00 |

### **Vision model examples**

* [LlamaOCR](https://llamaocr.com/): A tool that takes documents (like receipts) and outputs markdown.
* [Wireframe to code](https://www.napkins.dev/): A wireframe to app tool that takes in a UI mockup of a site and gives you React code.
* [Extracting structured data from images](https://github.com/togethercomputer/together-cookbook/blob/main/inference/vision/Structured_Text_Extraction_from_Images.ipynb): Extract information from images as JSON.

## Video models

| Organization | Model name | Model string for API | Price per video | Resolution / duration |
| :- | :- | :- | :- | :- |
| MiniMax | MiniMax 01 Director | minimax/video-01-director | \$0.28 | 720p / 5s |
| MiniMax | MiniMax Hailuo 02 | minimax/hailuo-02 | \$0.49 | 768p / 10s |
| ByteDance | Seedance 1.0 Pro | ByteDance/Seedance-1.0-pro | \$0.57 | 1080p / 5s |
| PixVerse | PixVerse v5 | pixverse/pixverse-v5 | \$0.30 | 1080p / 5s |
| Vidu | Vidu Q1 | vidu/vidu-q1 | \$0.22 | 1080p / 5s |
| PixVerse | PixVerse v5.6 | pixverse/pixverse-v5.6 | \$0.1326 | - |
| Wan-AI | Wan 2.7 T2V | Wan-AI/wan2.7-t2v | \$0.10 | - |
| Vidu | Vidu Q3 | vidu/vidu-q3 | \$0.0975 | - |
| Vidu | Vidu Q3 Turbo | vidu/vidu-q3-turbo | \$0.195 | - |
| Wan-AI | Wan 2.7 I2V | Wan-AI/wan2.7-i2v | \$0.10 | - |
| Wan-AI | Wan 2.7 R2V | Wan-AI/wan2.7-r2v | \$0.10 | - |
| PixVerse | PixVerse v6 | pixverse/pixverse-v6 | \$0.09 | - |
| Alibaba | HappyHorse 1.0 T2V | alibaba/happyhorse-1.0-t2v | \$0.24 | - |
| ByteDance | Seedance 2.0 | ByteDance/Seedance-2.0 | \$0.16 | - |
| Alibaba | HappyHorse 1.0 I2V | alibaba/happyhorse-1.0-i2v | \$0.24 | - |
| Alibaba | HappyHorse 1.0 R2V | alibaba/happyhorse-1.0-r2v | \$0.24 | - |
| Google | Veo 3.1 | google/veo-3.1 | \$0.08 | - |
| Google | Veo 3.1 Lite | google/veo-3.1-lite | \$0.05 | - |
| Alibaba | HappyHorse 1.1 I2V | alibaba/happyhorse-1.1-i2v | \$0.14 | - |
| Alibaba | HappyHorse 1.1 R2V | alibaba/happyhorse-1.1-r2v | \$0.14 | - |
| Alibaba | HappyHorse 1.1 T2V | alibaba/happyhorse-1.1-t2v | \$0.14 | - |
| Black Forest Labs | FLUX 3 | black-forest-labs/FLUX-3 | \$0.17 | - |
| ByteDance | Seedance 2.5 | ByteDance/Seedance-2.5 | \$0.115 | - |
| ByteDance | Seedance 1.0 Lite | ByteDance/Seedance-1.0-lite | \$0.143 | 720p / 5s |
| MiniMax | MiniMax H3 | MiniMaxAI/MiniMax-H3 | \$0.1391 | 2k / 1s |

## Audio models

Use our [Audio](/reference/audio-speech) endpoint for text-to-speech models. For speech-to-text models see [Transcription](/reference/audio-transcriptions) and [Translations](/reference/audio-translations).

| Organization | Modality | Model name | Model string for API | Pricing |
| :- | :- | :- | :- | :- |
| Canopy Labs | Text-to-Speech | Orpheus 3B | canopylabs/orpheus-3b-0.1-ft | \$15.00 per 1M chars |
| Kokoro | Text-to-Speech | Kokoro | hexgrad/Kokoro-82M | \$4.00 per 1M chars |
| Cartesia | Text-to-Speech | Cartesia Sonic 3 | cartesia/sonic-3 | \$65.00 per 1M chars |
| Cartesia | Text-to-Speech | Cartesia Sonic 2 | cartesia/sonic-2 | \$65.00 per 1M chars |
| Cartesia | Text-to-Speech | Cartesia Sonic | cartesia/sonic | \$65.00 per 1M chars |
| OpenAI | Speech-to-Text | Whisper Large v3 | openai/whisper-large-v3 | \$0.0015 per audio min |
| NVIDIA | Speech-to-Text | Parakeet TDT 0.6B v3 | nvidia/parakeet-tdt-0.6b-v3 | \$0.0015 per audio min |
| NVIDIA | Speech-to-Text | NVIDIA Nemotron 3 ASR Streaming 0.6B | nvidia/nemotron-3-asr-streaming-0.6b | \$0.0015 per audio min |
| NVIDIA | Speech-to-Text | NVIDIA Nemotron 3.5 ASR Streaming 0.6B | nvidia/nemotron-3.5-asr-streaming-0.6b | \$0.0015 per audio min |

**Audio model examples**

* [PDF to podcast notebook](https://github.com/togethercomputer/together-cookbook/blob/main/apps/PDF_to_Podcast.ipynb): Generate a NotebookLM style podcast given a PDF.
* [Audio podcast agent workflow](https://github.com/togethercomputer/together-cookbook/blob/main/agents/Serial_Chain_Agent_Workflow.ipynb): Agent workflow to generate audio files given input content.

## Embedding models

There are currently no embedding models offered via serverless.

## Rerank models

There are currently no rerank models offered via serverless. Rerank models like `mixedbread-ai/mxbai-rerank-large-v2` are only available with [dedicated model inference](/docs/dedicated-endpoints/models).

## Moderation models

There are currently no moderation models offered via serverless.


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