Mistral Nemo

Mistral Generally Available

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

Context
131K
tokens
Input
$0.020
per MTok
Output
$0.030
per MTok

About

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

Modalities

Input
Text
Output
Text

Code Examples

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistral-nemo",
    "messages": [
      { "role": "user", "content": "Explain quantum entanglement in one sentence." }
    ]
  }'

API Parameters

Name Type Description
frequency_penalty number Penalize tokens by their frequency so far. Positive values reduce repetition.
logit_bias object Map of token-id to bias (-100…100) added to the logit before sampling.
logprobs boolean Return log probabilities for each output token.
max_tokens deprecated integer Deprecated. Use max_completion_tokens.
min_p unknown
presence_penalty number Penalize tokens that have appeared at all so far. Positive values encourage new topics.
repetition_penalty number Penalize repeated tokens (>1.0 reduces repetition, <1.0 encourages it).
response_format one of Constrain output to a JSON schema or an enum (structured outputs).
seed integer Deterministic seed for sampling. Same seed + same prompt produces identical output.
stop array Up to 4 sequences where the API will stop generating tokens.
structured_outputs boolean Enable JSON-schema-constrained output.
temperature number Sampling temperature; higher values produce more random output. 0 is deterministic.
tool_choice one of Controls which (if any) tool is called: "none", "auto", "required", or a specific tool.
tools array List of tools (functions) the model may call.
top_k integer Limit sampling to the top-k most likely tokens at each step.
top_logprobs integer Return the top-N most likely tokens at each step (requires logprobs: true).
top_p number Nucleus sampling: consider only tokens whose cumulative probability ≥ top_p.

Standard OpenAI-compatible parameters. Consult the provider docs for model-specific behaviour.