Supported models

This page lists all supported model sources for the Evaluations API. You can use serverless models, dedicated endpoints, or external models from providers like OpenAI, Anthropic, and Google.

Serverless models

Set model_source = "serverless" to use Together’s serverless inference.

Any Together serverless model that supports structured outputs can be used.

Model	Model ID
DeepSeek-R1	`deepseek-ai/DeepSeek-R1`
DeepSeek-V3.1	`deepseek-ai/DeepSeek-V3.1`
DeepSeek-V4 Pro	`deepseek-ai/DeepSeek-V4-Pro`
Llama 3.3 70B Instruct Turbo	`meta-llama/Llama-3.3-70B-Instruct-Turbo`
LFM2 24B A2B	`LiquidAI/LFM2-24B-A2B`
MiniMax M2.7	`MiniMaxAI/MiniMax-M2.7`
Kimi K2.5	`moonshotai/Kimi-K2.5`
Kimi K2.6	`moonshotai/Kimi-K2.6`
Qwen3 235B A22B Instruct 2507	`Qwen/Qwen3-235B-A22B-Instruct-2507-tput`
Qwen3 Coder 480B A35B Instruct FP8	`Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8`
Qwen3 Coder Next FP8	`Qwen/Qwen3-Coder-Next-FP8`
Qwen 3.5 397B A17B	`Qwen/Qwen3.5-397B-A17B`
Qwen 3.5 9B	`Qwen/Qwen3.5-9B`
Qwen 3.6 Plus	`Qwen/Qwen3.6-Plus`
Gemma 3n E4B	`google/gemma-3n-E4B-it`
Gemma 4 31B	`google/gemma-4-31B-it`
Cogito V2 1 671B	`deepcogito/cogito-v2-1-671b`
Essential AI RNJ-1	`essentialai/rnj-1-instruct`
GLM-5	`zai-org/GLM-5`
GLM-5.1	`zai-org/GLM-5.1`
GPT OSS 20B	`openai/gpt-oss-20b`
GPT OSS 120B	`openai/gpt-oss-120b`

Example configuration:

Python

from together import Together

client = Together()

model_config = {
    "model": "deepseek-ai/DeepSeek-V3.1",
    "model_source": "serverless",
    "system_template": "You are a helpful assistant.",
    "input_template": "{{prompt}}",
    "max_tokens": 512,
    "temperature": 0.7,
}

Dedicated models

Set model_source = "dedicated" to use your own dedicated endpoint.

A user-launched dedicated endpoint must be created before running evaluations. After launching an endpoint, copy-paste the endpoint ID into the model field.

Example configuration:

Python

from together import Together

client = Together()

model_config = {
    "model": "your-endpoint-id",
    "model_source": "dedicated",
    "system_template": "You are a helpful assistant.",
    "input_template": "{{prompt}}",
    "max_tokens": 512,
    "temperature": 0.7,
}

External models

Set model_source = "external" to use models from external providers.

External models require an API token from the respective provider. Set the external_api_token parameter with your provider’s API key.

Supported shortcuts

Use these shortcuts in the model field - the API base URL will be determined automatically:

Provider	Model Name	Model String for API
OpenAI	GPT-5.5	`openai/gpt-5.5`
OpenAI	GPT-5.4	`openai/gpt-5.4`
OpenAI	GPT-5.4 Mini	`openai/gpt-5.4-mini`
OpenAI	GPT-5.4 Nano	`openai/gpt-5.4-nano`
OpenAI	GPT-5.3 Chat Latest	`openai/gpt-5.3-chat-latest`
OpenAI	GPT-4.1	`openai/gpt-4.1`
OpenAI	GPT-4.1 Mini	`openai/gpt-4.1-mini`
OpenAI	GPT-4.1 Nano	`openai/gpt-4.1-nano`
OpenAI	GPT-4o	`openai/gpt-4o`
OpenAI	GPT-4o Mini	`openai/gpt-4o-mini`
OpenAI	o4-mini	`openai/o4-mini`
OpenAI	o3	`openai/o3`
Anthropic	Claude Opus 4.7	`anthropic/claude-opus-4-7`
Anthropic	Claude Opus 4.6	`anthropic/claude-opus-4-6`
Anthropic	Claude Opus 4.5	`anthropic/claude-opus-4-5`
Anthropic	Claude Sonnet 4.6	`anthropic/claude-sonnet-4-6`
Anthropic	Claude Sonnet 4.5	`anthropic/claude-sonnet-4-5`
Anthropic	Claude Haiku 4.5	`anthropic/claude-haiku-4-5`
Google	Gemini 3.1 Pro Preview	`google/gemini-3.1-pro-preview`
Google	Gemini 3.1 Flash Lite	`google/gemini-3.1-flash-lite`
Google	Gemini 3 Pro Preview	`google/gemini-3-pro-preview`
Google	Gemini 3 Flash Preview	`google/gemini-3-flash-preview`
Google	Gemini 2.5 Pro	`google/gemini-2.5-pro`
Google	Gemini 2.5 Flash	`google/gemini-2.5-flash`
Google	Gemini 2.5 Flash Lite	`google/gemini-2.5-flash-lite`

Example configuration with shortcut:

Python

from together import Together

client = Together()

model_config = {
    "model": "openai/gpt-5",
    "model_source": "external",
    "external_api_token": "your-openai-api-key",
    "system_template": "You are a helpful assistant.",
    "input_template": "{{prompt}}",
    "max_tokens": 512,
    "temperature": 0.7,
}

Custom base URL

You can also use any OpenAI chat/completions-compatible API by specifying a custom external_base_url:

Python

from together import Together

client = Together()

model_config = {
    "model": "mistral-small-latest",
    "model_source": "external",
    "external_api_token": "your-mistral-api-key",
    "external_base_url": "https://api.mistral.ai/",
    "system_template": "You are a helpful assistant.",
    "input_template": "{{prompt}}",
    "max_tokens": 512,
    "temperature": 0.7,
}

The external API must be OpenAI chat/completions-compatible.

​Serverless models