Mistral Nemo
State-of-the-art reasoning, world knowledge, and coding accuracy model designed for global, multilingual applications.
Mistral Multilingual text generation with 128k context
Mistral NeMo is a text generation model developed by Mistral, a French AI company. It features a 128,000-token context window and is trained with function calling support, making it suitable for agentic and tool-use workflows. The model has particular strength across eleven languages: English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.
Mistral NeMo is a 12-billion parameter model built in collaboration with NVIDIA, which is reflected in the "NeMo" name referencing NVIDIA's NeMo framework. It is designed for developers and organizations building multilingual applications where broad language coverage and a large context window are priorities. The model's combination of function calling capability, multilingual training, and long-context handling makes it a practical choice for global deployment scenarios.
What Mistral Nemo supports
Long Context Window
Processes up to 128,000 tokens in a single request, enabling analysis of long documents, codebases, or extended conversations without truncation.
Multilingual Generation
Generates and understands text in eleven languages including English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.
Function Calling
Supports structured function calling, allowing the model to invoke external tools and APIs as part of agentic or automated workflows.
Code Generation
Produces and reasons about code across common programming languages, with coding accuracy noted as a focus area for its parameter size.
Reasoning & World Knowledge
Applies multi-step reasoning and broad factual knowledge to answer questions, summarize content, and solve problems in text form.
Structured Output
Can return responses in structured formats such as JSON, useful for downstream data processing and integration tasks.
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Get Started FreeCommon questions about Mistral Nemo
What is the context window size for Mistral NeMo?
Mistral NeMo supports a context window of up to 128,000 tokens, allowing it to process long documents or extended conversations in a single request.
Which languages does Mistral NeMo support?
The model is trained with particular strength in English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.
Does Mistral NeMo support function calling?
Yes, Mistral NeMo is trained on function calling, making it suitable for tool-use and agentic application workflows.
Who developed Mistral NeMo?
Mistral NeMo was developed by Mistral in collaboration with NVIDIA. The "NeMo" designation reflects the NVIDIA NeMo framework partnership.
What is the knowledge cutoff date for Mistral NeMo?
The metadata provided does not specify a training cutoff date. For the most accurate information, consult Mistral's official documentation.
What people think about Mistral Nemo
Community sentiment around Mistral NeMo on r/LocalLLaMA is notably positive, with one thread asking why its usage keeps growing over a year after release attracting 223 upvotes and 93 comments. Users frequently cite its multilingual capabilities and 12B parameter size as reasons for its sustained popularity in local deployment scenarios.
Common use cases discussed include multilingual applications and uncensored or fine-tuned variants for roleplay and creative tasks. Some community members have raised questions about a potential follow-up release, suggesting interest in an updated version of the model.
Where's Mistral Nemo 2.0?
Made a 12B uncensored RP merge, putting it out there - MistralNemoDionysusV3
Why does Mistral NeMo's usage keep growing even after more than a year since releasing?
Mistral NEMO upscale, but kinda weird
Best uncensored multi language LLM up to 12B, still Mistral Nemo?
Parameters & options
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