LLM ReferenceLLM Reference

Magistral Small 2506 vs o1-pro

Magistral Small 2506 (2026) and o1-pro (2024) are frontier reasoning models from MistralAI and OpenAI. Magistral Small 2506 ships a 128K-token context window, while o1-pro ships a 200K-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 is safer overall; choose o1-pro when long-context analysis matters.

Specs

Specification
Released2026-01-152024-12-05
Context window128K200K
Parameters
Architecturedecoder onlydecoder only
License1Unknown
Knowledge cutoff--

Pricing and availability

Pricing attributeMagistral Small 2506o1-pro
Input price-$150/1M tokens
Output price-$600/1M tokens
Providers

Capabilities

CapabilityMagistral Small 2506o1-pro
VisionNoNo
MultimodalNoNo
ReasoningYesNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on reasoning mode: Magistral Small 2506 and structured outputs: o1-pro. 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 o1-pro has $150/1M input tokens. Provider availability is 1 tracked routes versus 1. 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 are central to the workload. Choose o1-pro when long-context analysis and larger context windows 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 o1-pro?

o1-pro supports 200K tokens, while Magistral Small 2506 supports 128K 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 o1-pro open source?

Magistral Small 2506 is listed under 1. o1-pro is listed under Unknown. 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 o1-pro?

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 o1-pro?

o1-pro 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 o1-pro?

Magistral Small 2506 is available on NVIDIA NIM. o1-pro is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

When should I pick Magistral Small 2506 over o1-pro?

Magistral Small 2506 is safer overall; choose o1-pro when long-context analysis matters. If your workload also depends on reasoning depth, start with Magistral Small 2506; if it depends on long-context analysis, run the same evaluation with o1-pro.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.