Magistral Small 2506 vs Mistral Large
Magistral Small 2506 (2026) and Mistral Large (2024) are frontier reasoning models from MistralAI. Magistral Small 2506 ships a 128K-token context window, while Mistral Large ships a 32k-token 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.
Magistral Small 2506 fits 4x more tokens; pick it for long-context work and Mistral Large for tighter calls.
Specs
| Released | 2026-01-15 | 2024-02-08 |
| Context window | 128K | 32k |
| Parameters | — | — |
| Architecture | decoder only | - |
| License | 1 | Proprietary |
| Knowledge cutoff | - | 2024-03 |
Pricing and availability
| Magistral Small 2506 | Mistral Large | |
|---|---|---|
| Input price | - | $0.32/1M tokens |
| Output price | - | $0.96/1M tokens |
| Providers |
Capabilities
| Magistral Small 2506 | Mistral Large | |
|---|---|---|
| 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, reasoning mode: Magistral Small 2506, function calling: Mistral Large, tool use: Mistral Large, and structured outputs: Mistral Large. 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: Magistral Small 2506 has no token price sourced yet and Mistral Large has $0.32/1M input tokens. Provider availability is 1 tracked routes versus 8. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Magistral Small 2506 when reasoning depth and larger context windows are central to the workload. Choose Mistral Large when vision-heavy evaluation and broader provider choice 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.
FAQ
Which has a larger context window, Magistral Small 2506 or Mistral Large?
Magistral Small 2506 supports 128K tokens, while Mistral Large supports 32k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Magistral Small 2506 or Mistral Large open source?
Magistral Small 2506 is listed under 1. Mistral Large is listed under Proprietary. 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, Magistral Small 2506 or Mistral Large?
Mistral Large 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, Magistral Small 2506 or Mistral Large?
Magistral Small 2506 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, Magistral Small 2506 or Mistral Large?
Mistral Large has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Magistral Small 2506 and Mistral Large?
Magistral Small 2506 is available on NVIDIA NIM. Mistral Large is available on NVIDIA NIM, Microsoft Foundry, AWS Bedrock, Mistral AI Studio, and IBM watsonx. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.