Question 1

What context window does Mistral Nemo support?

Accepted Answer

It was trained with a 128k context window and config.json sets max_position_embeddings to 131,072. Both prompt and completion share that budget.

Question 2

What temperature should I use?

Accepted Answer

0.3. The Mistral card states explicitly that, unlike previous Mistral models, Nemo requires smaller temperatures, and its own examples use 0.3 to 0.35. The chute default is 0.7, so pass temperature explicitly for card-recommended behavior.

Question 3

Is the unsloth repo different from the Mistral AI original?

Accepted Answer

No functional difference: unsloth/Mistral-Nemo-Instruct-2407 carries the same MistralForCausalLM architecture, the same 12.25B safetensors parameter count, and the same Apache-2.0 license as mistralai/Mistral-Nemo-Instruct-2407. The unsloth mirror exists mainly to pair with their fine-tuning notebooks.

Question 4

Does it support function calling?

Accepted Answer

Yes. The model card demonstrates tool use through the Mistral function-calling format, defining tools with JSON schemas and parsing structured tool-call output. Via the OpenAI-compatible endpoint you can send standard tools fields where supported.

Question 5

How do I call it from the OpenAI SDK?

Accepted Answer

Use base_url https://llm.chutes.ai/v1 with your Chutes API key and set model to unsloth/Mistral-Nemo-Instruct-2407-TEE. Chat completions with streaming work unchanged.

Question 6

What does the TEE suffix mean?

Accepted Answer

The chute runs inside a Trusted Execution Environment: attested confidential-compute hardware that keeps prompts and outputs protected in memory during inference. It is a serving property of this chute, not a change to the model.

Question 7

Can I use it commercially?

Accepted Answer

Yes. Mistral-Nemo-Instruct-2407 is released under Apache-2.0, which permits commercial use, modification, and redistribution with attribution. Chutes endpoint usage is billed separately through your account.

Question 8

Is it multilingual?

Accepted Answer

Yes. It was trained on a large proportion of multilingual and code data, uses the Tekken tokenizer designed for efficient multilingual compression, and the card publishes multilingual MMLU scores for French, German, Spanish, Italian, Portuguese, Russian, Chinese, and Japanese.

Mistral Nemo Instruct 2407

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Mistral Nemo Instruct 2407

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