LLM Reference

Magistral Small 2506 vs Mistral Medium

Magistral Small 2506 (2025) and Mistral Medium (2023) are frontier reasoning models from MistralAI. Magistral Small 2506 ships a 128k-token context window, while Mistral Medium ships a 32k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

Magistral Small 2506 fits 4x more tokens; pick it for long-context work and Mistral Medium for tighter calls.

Decision scorecard

Local evidence first
SignalMagistral Small 2506Mistral Medium
Best forreasoning-heavy appsprovider-routed production
Decision fitLong contextCoding, Classification, and JSON / Tool use
Context window128k32k
Cheapest output-$2/1M tokens
Provider routes1 tracked2 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Magistral Small 2506 when...
  • Magistral Small 2506 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Magistral Small 2506 uniquely exposes Reasoning in local model data.
  • Local decision data tags Magistral Small 2506 for Long context.
Choose Mistral Medium when...
  • Mistral Medium has broader tracked provider coverage for fallback and procurement flexibility.
  • Mistral Medium uniquely exposes Structured outputs in local model data.
  • Local decision data tags Mistral Medium for Coding, Classification, and JSON / Tool use.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Magistral Small 2506

Unavailable

No complete token price in local provider data

Mistral Medium

$820

Cheapest tracked route/tier: OpenRouter

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Magistral Small 2506 -> Mistral Medium
  • No overlapping tracked provider route is sourced for Magistral Small 2506 and Mistral Medium; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning before moving production traffic.
  • Mistral Medium adds Structured outputs in local capability data.
Mistral Medium -> Magistral Small 2506
  • No overlapping tracked provider route is sourced for Mistral Medium and Magistral Small 2506; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.
  • Magistral Small 2506 adds Reasoning in local capability data.

Specs

Specification
Released2025-06-102023-12-11
Context window128k32k
Parameters24B
ArchitectureDecoder OnlyDecoder Only
LicenseApache 2.0OSI-approvedProprietary
OpennessOpen sourceProprietary
Commercial useCommercial use: permittedCommercial use: conditional
Knowledge cutoff2025-06-

Pricing and availability

Pricing attributeMagistral Small 2506Mistral Medium
Input price-$0.40/1M tokens
Output price-$2/1M tokens
Providers

Capabilities

CapabilityMagistral Small 2506Mistral Medium
VisionNoNo
MultimodalNoNo
ReasoningYesNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on reasoning mode: Magistral Small 2506 and structured outputs: Mistral Medium. 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 Medium has $0.40/1M input tokens. Provider availability is 1 tracked routes versus 2. 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 Medium when provider fit 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, Magistral Small 2506 or Mistral Medium?

Magistral Small 2506 supports 128k tokens, while Mistral Medium 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 Medium open source?

Magistral Small 2506 is listed under Apache 2.0. Mistral Medium 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 reasoning mode, Magistral Small 2506 or Mistral Medium?

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 structured outputs, Magistral Small 2506 or Mistral Medium?

Mistral Medium 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 Magistral Small 2506 and Mistral Medium?

Magistral Small 2506 is available on NVIDIA NIM. Mistral Medium is available on Mistral AI Studio and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Magistral Small 2506 over Mistral Medium?

Magistral Small 2506 fits 4x more tokens; pick it for long-context work and Mistral Medium for tighter calls. If your workload also depends on reasoning depth, start with Magistral Small 2506; if it depends on provider fit, run the same evaluation with Mistral Medium.

Continue comparing

Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.