Serverless models
Chat models
In the table below, models marked as "Turbo" are quantized to FP8 and those marked as "Lite" are INT4. All our other models are at full precision (FP16).
If you're not sure which chat model to use, we currently recommend Llama 3.1 8B Turbo (meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo) to get started.
| Organization | Model Name | API Model String | Context length | Quantization |
|---|---|---|---|---|
| Meta | Llama 3.3 70B Instruct Turbo | meta-llama/Llama-3.3-70B-Instruct-Turbo | 131072 | FP8 |
| Meta | Llama 3.1 8B Instruct Turbo | meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo | 131072 | FP8 |
| Meta | Llama 3.1 70B Instruct Turbo | meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo | 131072 | FP8 |
| Meta | Llama 3.1 405B Instruct Turbo | meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo | 130815 | FP8 |
| Meta | Llama 3 8B Instruct Turbo | meta-llama/Meta-Llama-3-8B-Instruct-Turbo | 8192 | FP8 |
| Meta | Llama 3 70B Instruct Turbo | meta-llama/Meta-Llama-3-70B-Instruct-Turbo | 8192 | FP8 |
| Meta | Llama 3.2 3B Instruct Turbo | meta-llama/Llama-3.2-3B-Instruct-Turbo | 131072 | FP16 |
| Meta | Llama 3 8B Instruct Lite | meta-llama/Meta-Llama-3-8B-Instruct-Lite | 8192 | INT4 |
| Meta | Llama 3 70B Instruct Lite | meta-llama/Meta-Llama-3-70B-Instruct-Lite | 8192 | INT4 |
| Meta | Llama 3 8B Instruct Reference | meta-llama/Llama-3-8b-chat-hf | 8192 | FP16 |
| Meta | Llama 3 70B Instruct Reference | meta-llama/Llama-3-70b-chat-hf | 8192 | FP16 |
| Nvidia | Llama 3.1 Nemotron 70B | nvidia/Llama-3.1-Nemotron-70B-Instruct-HF | 32768 | FP16 |
| Qwen | Qwen 2.5 Coder 32B Instruct | Qwen/Qwen2.5-Coder-32B-Instruct | 32768 | FP16 |
| Qwen | QwQ-32B-Preview | Qwen/QwQ-32B-Preview | 32768 | FP16 |
| Microsoft | WizardLM-2 8x22B | microsoft/WizardLM-2-8x22B | 65536 | FP16 |
| Gemma 2 27B | google/gemma-2-27b-it | 8192 | FP16 | |
| Gemma 2 9B | google/gemma-2-9b-it | 8192 | FP16 | |
| databricks | DBRX Instruct | databricks/dbrx-instruct | 32768 | FP16 |
| DeepSeek | DeepSeek LLM Chat (67B) | deepseek-ai/deepseek-llm-67b-chat | 4096 | FP16 |
| Gemma Instruct (2B) | google/gemma-2b-it | 8192 | FP16 | |
| Gryphe | MythoMax-L2 (13B) | Gryphe/MythoMax-L2-13b | 4096 | FP16 |
| Meta | LLaMA-2 Chat (13B) | meta-llama/Llama-2-13b-chat-hf | 4096 | FP16 |
| mistralai | Mistral (7B) Instruct | mistralai/Mistral-7B-Instruct-v0.1 | 8192 | FP16 |
| mistralai | Mistral (7B) Instruct v0.2 | mistralai/Mistral-7B-Instruct-v0.2 | 32768 | FP16 |
| mistralai | Mistral (7B) Instruct v0.3 | mistralai/Mistral-7B-Instruct-v0.3 | 32768 | FP16 |
| mistralai | Mixtral-8x7B Instruct (46.7B) | mistralai/Mixtral-8x7B-Instruct-v0.1 | 32768 | FP16 |
| mistralai | Mixtral-8x22B Instruct (141B) | mistralai/Mixtral-8x22B-Instruct-v0.1 | 65536 | FP16 |
| NousResearch | Nous Hermes 2 - Mixtral 8x7B-DPO (46.7B) | NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO | 32768 | FP16 |
| Qwen | Qwen 2.5 7B Instruct Turbo | Qwen/Qwen2.5-7B-Instruct-Turbo | 32768 | FP8 |
| Qwen | Qwen 2.5 72B Instruct Turbo | Qwen/Qwen2.5-72B-Instruct-Turbo | 32768 | FP8 |
| Qwen | Qwen 2 Instruct (72B) | Qwen/Qwen2-72B-Instruct | 32768 | FP16 |
| upstage | Upstage SOLAR Instruct v1 (11B) | upstage/SOLAR-10.7B-Instruct-v1.0 | 4096 | FP16 |
Image models
Use our Images endpoint for Image Models.
| Organization | Model Name | Model String for API | Default steps |
|---|---|---|---|
| Black Forest Labs | Flux.1 [schnell] (free)* | black-forest-labs/FLUX.1-schnell-Free | - |
| Black Forest Labs | Flux.1 [schnell] (Turbo) | black-forest-labs/FLUX.1-schnell | 4 |
| Black Forest Labs | Flux.1 Dev | black-forest-labs/FLUX.1-dev | 28 |
| Black Forest Labs | Flux.1 Canny | black-forest-labs/FLUX.1-canny | 28 |
| Black Forest Labs | Flux.1 Depth | black-forest-labs/FLUX.1-depth | 28 |
| Black Forest Labs | Flux.1 Redux | black-forest-labs/FLUX.1-redux | 28 |
| Black Forest Labs | Flux1.1 [pro] | black-forest-labs/FLUX.1.1-pro | - |
| Black Forest Labs | Flux.1 [pro] | black-forest-labs/FLUX.1-pro | - |
| Stability AI | Stable Diffusion XL 1.0 | stabilityai/stable-diffusion-xl-base-1.0 | - |
*Free model has reduced rate limits and performance compared to our paid Turbo endpoint for Flux Shnell named black-forest-labs/FLUX.1-schnell
Vision models
If you're not sure which vision model to use, we currently recommend Llama 3.2 11B Turbo (meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo) to get started. For model specific rate limits, navigate here.
| Organization | Model Name | API Model String | Context length |
|---|---|---|---|
| Meta | (Free) Llama 3.2 11B Vision Instruct Turbo* | meta-llama/Llama-Vision-Free | 131072 |
| Meta | Llama 3.2 11B Vision Instruct Turbo | meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo | 131072 |
| Meta | Llama 3.2 90B Vision Instruct Turbo | meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo | 131072 |
*Free model has reduced rate limits compared to paid version of Llama 3.2 Vision 11B named Llama-3.2-11B-Vision-Instruct-Turbo
Code models
Use our Completions endpoint for Code Models.
| Organization | Model Name | Model String for API | Context length |
|---|---|---|---|
| Meta | CodeLlama 34B Instruct | codellama/CodeLlama-34b-Instruct-hf | 16384 |
| Qwen | Qwen 2.5 Coder 32B Instruct | Qwen/Qwen2.5-Coder-32B-Instruct | 32768 |
Language models
Use our Completions endpoint for Language Models.
| Organization | Model Name | Model String for API | Context length |
|---|---|---|---|
| Meta | LLaMA-2 (70B) | meta-llama/Llama-2-70b-hf | 4096 |
| mistralai | Mistral (7B) | mistralai/Mistral-7B-v0.1 | 8192 |
| mistralai | Mixtral-8x7B (46.7B) | mistralai/Mixtral-8x7B-v0.1 | 32768 |
Moderation models
Use our Completions endpoint to run a moderation model as a standalone classifier, or use it alongside any of the other models above as a filter to safeguard responses from 100+ models, by specifying the parameter "safety_model": "MODEL_API_STRING"
| Organization | Model Name | Model String for API | Context length |
|---|---|---|---|
| Meta | Llama Guard (7B) | Meta-Llama/Llama-Guard-7b | 4096 |
Embedding models
| Model Name | Model String for API | Model Size | Embedding Dimension | Context Window |
|---|---|---|---|---|
| M2-BERT-80M-2K-Retrieval | togethercomputer/m2-bert-80M-2k-retrieval | 80M | 768 | 2048 |
| M2-BERT-80M-8K-Retrieval | togethercomputer/m2-bert-80M-8k-retrieval | 80M | 768 | 8192 |
| M2-BERT-80M-32K-Retrieval | togethercomputer/m2-bert-80M-32k-retrieval | 80M | 768 | 32768 |
| UAE-Large-v1 | WhereIsAI/UAE-Large-V1 | 326M | 1024 | 512 |
| BGE-Large-EN-v1.5 | BAAI/bge-large-en-v1.5 | 326M | 1024 | 512 |
| BGE-Base-EN-v1.5 | BAAI/bge-base-en-v1.5 | 102M | 768 | 512 |
| Sentence-BERT | sentence-transformers/msmarco-bert-base-dot-v5 | 110M | 768 | 512 |
| BERT | bert-base-uncased | 110M | 768 | 512 |
Rerank models
Our Rerank API has built-in support for the following models, that we host via our serverless endpoints.
| Organization | Model Name | Model Size | Model String for API | Max Doc Size (tokens) | Max Docs |
|---|---|---|---|---|---|
| Salesforce | LlamaRank | 8B | Salesforce/Llama-Rank-v1 | 8192 | 1024 |
Updated 12 days ago