LLM Reference

Mistral NeMo (2407)

Released
2024-07-18
Last refreshed
2026-06-01
Status
Researched 3d ago
Long context

Mistral NeMo (2407) is worth evaluating for long context when its provider route and context window match the workload.

Use it for

  • Teams evaluating long context
  • Workloads that can use a 128k context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Released
2024-07-18
Context
128k
Parameters
12B
Architecture
Decoder Only
Knowledge cutoff
2024-04
Specialization
general
Training
finetuned
Created by

Enterprise AI solutions for trust and transparency.

Paris, France
Founded 2023
Website
Pricing
Output / 1M
$0.030
Input / 1M
$0.020

Cheapest of 7 routes · OpenRouter

About

Mistral NeMo is a 12B parameter open-source language model developed by Mistral AI, designed for efficient performance and reasoning tasks. With a 128K token context window, it excels at handling long documents and complex reasoning. The model is optimized for fast inference while maintaining strong performance across multiple benchmarks, making it suitable for enterprise deployments where balance between performance and resource efficiency is critical.

Mistral NeMo is a 12-billion-parameter open-source language model developed jointly by Mistral AI and NVIDIA, released in July 2024. It supports a 128,000-token context window and is available under the Apache 2.0 license, making it freely usable for both research and commercial applications. The model was designed to replace Mistral 7B as the default open mid-tier model, offering substantially longer context and improved multilingual capability at a modest increase in parameter count.

A notable architectural feature is the Tekken tokenizer, which has a vocabulary of approximately 131,000 tokens—significantly larger than the previous Mistral tokenizer. This improves tokenization efficiency for multilingual text, including European and Asian languages, reducing token count for equivalent text and thus lowering cost and latency for multilingual applications. The model architecture is otherwise a standard decoder-only transformer, similar to Mistral 7B, optimized for efficient inference on commodity hardware.

Mistral NeMo is available through Mistral AI's API, Fireworks AI, Bitdeer, OpenRouter, Novita AI, and SiliconFlow. It can be self-hosted from Hugging Face (mistralai/Mistral-Nemo-Instruct-2407). At 12B parameters, it is heavier than Mistral 7B but substantially cheaper than Mistral Small or Mistral Large and fits on a single GPU with 24GB VRAM in standard precision. For applications currently using Mistral 7B that need longer context or better multilingual coverage, Mistral NeMo is the natural upgrade path.

Mistral NeMo (2407) has a 128k-token context window.

Mistral NeMo (2407) input tokens at $0.02/1M, output at $0.03/1M.

Top use-case fit

Long context

Included by capability and metadata signals in the decision map.

Provider price ladder

Compare all 7

Compare API pricing across 4 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
OpenRouter$0.020$0.030
Serverless
Vercel AI Gateway$0.020$0.040
Serverless
Mistral AI Studio$0.150$0.150
Serverless
Novita AI$0.040$0.170
Serverless

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Long context

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.

Rankings & picks(7)

Comparison and alternatives

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