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Mistral Large 2 (2407) vs Mistral Nemotron

Mistral Large 2 (2407) (2024) and Mistral Nemotron (2025) are compact production models from MistralAI. Mistral Large 2 (2407) ships a 128K-token context window, while Mistral Nemotron ships a not-yet-sourced context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Mistral Nemotron is safer overall; choose Mistral Large 2 (2407) when vision-heavy evaluation matters.

Specs

Released2024-07-232025-12-01
Context window128K
Parameters123B
Architecturedecoder onlydecoder only
LicenseApache 2.01
Knowledge cutoff--

Pricing and availability

Mistral Large 2 (2407)Mistral Nemotron
Input price$0.5/1M tokens-
Output price$1.5/1M tokens-
Providers

Capabilities

Mistral Large 2 (2407)Mistral Nemotron
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Mistral Large 2 (2407) and structured outputs: Mistral Large 2 (2407). Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: Mistral Large 2 (2407) has $0.5/1M input tokens and Mistral Nemotron has no token price sourced yet. Provider availability is 3 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Mistral Large 2 (2407) when vision-heavy evaluation and broader provider choice are central to the workload. Choose Mistral Nemotron when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Is Mistral Large 2 (2407) or Mistral Nemotron open source?

Mistral Large 2 (2407) is listed under Apache 2.0. Mistral Nemotron is listed under 1. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, Mistral Large 2 (2407) or Mistral Nemotron?

Mistral Large 2 (2407) has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Mistral Large 2 (2407) or Mistral Nemotron?

Mistral Large 2 (2407) has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Mistral Large 2 (2407) and Mistral Nemotron?

Mistral Large 2 (2407) is available on Microsoft Foundry, Chutes AI, and SiliconFlow. Mistral Nemotron is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Mistral Large 2 (2407) over Mistral Nemotron?

Mistral Nemotron is safer overall; choose Mistral Large 2 (2407) when vision-heavy evaluation matters. If your workload also depends on vision-heavy evaluation, start with Mistral Large 2 (2407); if it depends on provider fit, run the same evaluation with Mistral Nemotron.

Continue comparing

Last reviewed: 2026-04-23. Data sourced from public model cards and provider documentation.