Mistral Nemo: Efficient Vision Inference on Modular

Mistral-Nemo-Instruct-2407 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-Nemo-Base-2407. Trained jointly by Mistral AI and NVIDIA, it significantly outperforms existing models smaller or similar in size.

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Example Usage

Output

  Speculative decoding uses a smaller draft model to predict multiple
  tokens ahead, then verifies them against the full model in a single
  pass. Accepted tokens skip individual generation steps, improving
  throughput without sacrificing accuracy. It's most effective when the
  draft model closely matches the target model's distribution.

Code to use

Python


  from openai import OpenAI
  
  client = OpenAI(
      base_url="https://model.api.modular.com",
      api_key="<your_api_token>",
  )
  
  response = client.chat.completions.create(
      model="mistralai/Mistral-Nemo-Instruct-2407",
      messages=[
          {"role": "system", "content": "You are a helpful assistant."},
          {"role": "user", "content": "Explain speculative decoding in 3 sentences."},
      ],
      stream=True,
  )
  
  for chunk in response:
      if chunk.choices[0].delta.content:
          print(chunk.choices[0].delta.content, end="")

Get your API token

Model Details

Developed by
Mistral AI
Model family
mistralai/Mistral-Nemo-Instruct-2407
Modality
LLM,
Context Window
128K
Total Params
12B
Precision
BF16
Deployment options
Shared, Dedicated, Self-hosted

Why choose Mistral Nemo on Modular?

High performance, out of the box
Run leading open models with strong default performance and the ability to optimize down to the kernel — extracting more from every GPU.
Lower Infrastructure Costs
Deploy efficiently across NVIDIA and AMD hardware to reduce GPU count, increase throughput, and avoid expensive closed-model licensing.
Easy Integration
Integrate through an OpenAI-compatible endpoint, swap models freely, and scale across clouds or hardware without redesigning your application stack.

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Mistral Nemo: Efficient Vision Inference on Modular

Example Usage

Why choose Mistral Nemo on Modular?

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