Supported base models

Each row below is a Hugging Face repo ID you can pass as base_model when starting a Loops run, along with the maximum supported sequence length and whether the model accepts vision-language input. Baseten adds rows as it validates new models end to end.

Models

Model	Max sequence length	Vision
`Qwen/Qwen3-0.6B`	8,192	No
`Qwen/Qwen3-8B`	40,960	No
`Qwen/Qwen3-30B-A3B-Instruct-2507`	131,072	No
`Qwen/Qwen3.5-0.8B`	131,072	Yes
`Qwen/Qwen3.5-2B`	131,072	Yes
`Qwen/Qwen3.5-4B`	131,072	Yes
`Qwen/Qwen3.5-9B`	131,072	Yes
`Qwen/Qwen3.5-27B`	131,072	Yes
`Qwen/Qwen3.5-35B-A3B`	131,072	Yes
`Qwen/Qwen3.5-122B-A10B`	262,144	Yes
`Qwen/Qwen3.5-397B-A17B`	262,144	Yes
`Qwen/Qwen3.6-27B`	131,072	Yes
`Qwen/Qwen3.6-35B-A3B`	262,144	Yes
`Qwen/Qwen3.8-27B`	262,144	Yes
`deepseek-ai/DeepSeek-V4-Flash`	131,072	No
`deepseek-ai/DeepSeek-V4-Flash-0731`	131,072	No
`google/gemma-4-26B-A4B`	65,536	No
`google/gemma-4-26B-A4B-it`	65,536	No
`google/gemma-4-31B`	131,072	No
`google/gemma-4-31B-it`	131,072	No
`moonshotai/Kimi-K2.6`	262,144	Yes
`moonshotai/Kimi-K2.7-Code`	262,144	Yes
`moonshotai/Kimi-K3`	131,072	No
`nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16`	262,144	No
`nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4`	262,144	No
`zai-org/GLM-5.2-FP8`	262,144	No
`zai-org/GLM-5.3`	262,144	No
`zai-org/GLM-5.3-Flash`	131,072	Yes

Some models restrict the available loss functions by configuration. GLM 5.3 runs long contexts with context parallelism and router replay (R3) enabled, and in that configuration cross_entropy and dpo are unavailable. See Loss functions for the full list.

List supported models

Query the /v1/loops/capabilities endpoint for the current list of base models, their maximum sequence lengths, and whether they support vision-language input:

curl https://api.baseten.co/v1/loops/capabilities \
  -H "Authorization: Bearer $BASETEN_API_KEY"

{
  "supported_models": [
    {"model_name": "Qwen/Qwen3-0.6B", "max_context_length": 8192, "supports_vision_language": false},
    {"model_name": "Qwen/Qwen3.5-27B", "max_context_length": 131072, "supports_vision_language": true},
    ...
  ]
}

The endpoint lists the base models Loops supports, so its response is the source of truth for what you can pass as base_model, even where it differs from the table above. See GET /v1/loops/capabilities for the full route reference.

Pass a model to Loops

Pass the table value verbatim as base_model through any of the following entry points:

The Python SDK, using ServiceClient.create_lora_training_client(base_model=...). See the Loops quickstart.
The HTTP API, using POST /v1/loops/trainers.
The CLI, using baseten loops run create --base-model <base_model>, which provisions a session, run, and paired sampler in one call.

The minimal HTTP call provisions a trainer against an existing session. Replace 2qjl22w with the session.id returned by POST /v1/loops/sessions:

curl --request POST \
  --url https://api.baseten.co/v1/loops/trainers \
  --header "Authorization: Bearer $BASETEN_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "session_id": "2qjl22w",
    "base_model": "Qwen/Qwen3.5-9B"
  }'

For the full request body and response shape, see the Loops API reference.

Request a model

To request a base model that isn’t listed, contact support.

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Supported base models

Models

List supported models

Pass a model to Loops

Request a model

​Models

​List supported models

​Pass a model to Loops

​Request a model

Models

List supported models

Pass a model to Loops

Request a model