> For the complete documentation index, see [llms.txt](https://docs.gensyn.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.gensyn.ai/tech/ree/supported-models.md).

# Supported Models

A list of models verified to work with REE.

## Verified-Compatible Models

The following models have been verified to work with REE. Any Hugging Face model compatible with the system *may* work, but this list represents models that have been explicitly tested.

If you have a specific model in mind that doesn't work with REE, you can reach out to the Gensyn team by creating an issue in the [GitHub repository](https://github.com/gensyn-ai/ree/issues) and we'll do our best to support it.

{% hint style="info" %}
Models above \~32B typically require pipeline parallelism to run.

Use the `--n-partitions` flag to split the model across multiple GPUs. See [Pipeline Parallelism](https://docs.gensyn.ai/tech/ree/advanced-usage#pipeline-parallelism) for details.
{% endhint %}

### Tool-Calling Models

REE can run many Hugging Face models, but tool-call behavior depends on the selected model.

Tool definitions are passed through the tokenizer's chat template when using `InferenceSession.complete(messages=..., tools=...)`. Models with chat templates and tool/function-calling instruction tuning are more likely to emit useful structured tool-call output.

REE SDK support *does not make every supported model equally capable of using tools.* Test your selected model against your tool schemas before relying on it in an application workflow.

#### Thinking-Capable Models

`enable_thinking` (`v0.4.0`, SDK only) applies only when the model's tokenizer chat template accepts an `enable_thinking` parameter (for example, Qwen3). Other models ignore or do not support this toggle.

### Qwen

| Model                              | Parameters |
| ---------------------------------- | ---------- |
| `Qwen/Qwen2.5-72B-Instruct`        | 72B        |
| `Qwen/Qwen3-32B`                   | 32B        |
| `Qwen/Qwen3-8B`                    | 8B         |
| `Qwen/Qwen3-4B`                    | 4B         |
| `Qwen/Qwen3-1.7B`                  | 1.7B       |
| `Qwen/Qwen3-0.6B`                  | 0.6B       |
| `Qwen/Qwen2.5-32B-Instruct`        | 32B        |
| `Qwen/Qwen2.5-14B-Instruct`        | 14B        |
| `Qwen/Qwen2.5-7B-Instruct`         | 7B         |
| `Qwen/Qwen2.5-7B`                  | 7B         |
| `Qwen/Qwen2.5-3B-Instruct`         | 3B         |
| `Qwen/Qwen2.5-0.5B-Instruct`       | 0.5B       |
| `Qwen/Qwen2.5-0.5B`                | 0.5B       |
| `Qwen/Qwen2.5-Coder-7B-Instruct`   | 7B         |
| `Qwen/Qwen2.5-Coder-0.5B-Instruct` | 0.5B       |
| `Qwen/Qwen2-1.5B-Instruct`         | 1.5B       |

### Meta Llama

| Model                                 | Parameters |
| ------------------------------------- | ---------- |
| `meta-llama/Llama-3.1-8B-Instruct`    | 8B         |
| `meta-llama/Llama-3.1-8B`             | 8B         |
| `meta-llama/Meta-Llama-3-8B`          | 8B         |
| `meta-llama/Meta-Llama-3-8B-Instruct` | 8B         |
| `meta-llama/Llama-3.2-3B-Instruct`    | 3B         |
| `meta-llama/Llama-3.2-1B-Instruct`    | 1B         |
| `meta-llama/Llama-3.2-1B`             | 1B         |
| `meta-llama/Llama-3.1-70B-Instruct`   | 70B        |
| `meta-llama/Llama-3.3-70B-Instruct`   | 70B        |

### DeepSeek

| Model                                      | Parameters |
| ------------------------------------------ | ---------- |
| `deepseek-ai/DeepSeek-R1-Distill-Qwen-32B` | 32B        |

### Mistral

| Model                                | Parameters |
| ------------------------------------ | ---------- |
| `mistralai/Mistral-7B-Instruct-v0.2` | 7B         |

### Code Models

| Model                              | Parameters |
| ---------------------------------- | ---------- |
| `codellama/CodeLlama-7b-hf`        | 7B         |
| `bigcode/starcoder2-3b`            | 3B         |
| `Qwen/Qwen2.5-Coder-7B-Instruct`   | 7B         |
| `Qwen/Qwen2.5-Coder-0.5B-Instruct` | 0.5B       |

### Other Models

| Model                                | Provider     | Parameters |
| ------------------------------------ | ------------ | ---------- |
| `01-ai/Yi-1.5-6B-Chat`               | 01.AI        | 6B         |
| `llm-jp/llm-jp-3-3.7b-instruct`      | LLM-JP       | 3.7B       |
| `TinyLlama/TinyLlama-1.1B-Chat-v1.0` | TinyLlama    | 1.1B       |
| `HuggingFaceTB/SmolLM-1.7B-Instruct` | Hugging Face | 1.7B       |
| `allenai/OLMo-1B-hf`                 | Allen AI     | 1B         |
| `facebook/opt-125m`                  | Meta         | 125M       |
| `stabilityai/stablelm-2-1_6b`        | Stability AI | 1.6B       |

### Using an Unlisted Model

REE is not limited to the models above. `v0.6.0` improves ONNX export compatibility through PyTorch's dynamo path and supports ONNX LayerNormalization nodes without a bias input. An unlisted model may work when it exports and executes successfully.

To try an unlisted model, enter its Hugging Face model ID in the [**Model Name** field in the TUI](/tech/ree/using-the-tui.md) (e.g., `organization/model-name`) and run it.