LLM Reference

Magistral Small 2506 vs o4-mini

Magistral Small 2506 (2025) and o4-mini (2025) are frontier-tier reasoning models from MistralAI and OpenAI. Magistral Small 2506 ships a 128k-token context window, while o4-mini ships a 200k-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 is safer overall; choose o4-mini when coding workflow support matters.

Decision scorecard

Local evidence first
SignalMagistral Small 2506o4-mini
Best forreasoning-heavy appsreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitLong contextCoding, RAG, and Agents
Context window128k200k
Cheapest output-$4/1M tokens
Provider routes1 tracked4 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Magistral Small 2506 when...
  • Local decision data tags Magistral Small 2506 for Long context.
Choose o4-mini when...
  • o4-mini has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • o4-mini has broader tracked provider coverage for fallback and procurement flexibility.
  • o4-mini uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags o4-mini for Coding, RAG, and Agents.

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

o4-mini

$1,800

Cheapest tracked route/tier: Replicate API

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

Switch friction

Magistral Small 2506 -> o4-mini
  • No overlapping tracked provider route is sourced for Magistral Small 2506 and o4-mini; plan for SDK, billing, or endpoint changes.
  • o4-mini adds Vision, Multimodal, and Function calling in local capability data.
o4-mini -> Magistral Small 2506
  • No overlapping tracked provider route is sourced for o4-mini and Magistral Small 2506; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.

Specs

Specification
Released2025-06-102025-04-16
Context window128k200k
Parameters24B
Architecturedecoder onlydecoder only
LicenseApache 2.0(OSI)Proprietary
OpennessOpen sourceProprietary
Commercial useCommercial use allowedCommercial use with conditions
Knowledge cutoff2025-062025-08

Pricing and availability

Pricing attributeMagistral Small 2506o4-mini
Input price-$1/1M tokens
Output price-$4/1M tokens
Providers

Capabilities

CapabilityMagistral Small 2506o4-mini
VisionNoYes
MultimodalNoYes
ReasoningYesYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: o4-mini, multimodal input: o4-mini, function calling: o4-mini, tool use: o4-mini, structured outputs: o4-mini, and code execution: o4-mini. Both models share reasoning mode, 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 o4-mini has $1/1M input tokens. Provider availability is 1 tracked routes versus 4. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Magistral Small 2506 when provider fit are central to the workload. Choose o4-mini when coding workflow support, larger context windows, 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 o4-mini?

o4-mini 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 o4-mini open source?

Magistral Small 2506 is listed under Apache 2.0. o4-mini 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 o4-mini?

o4-mini 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 multimodal input, Magistral Small 2506 or o4-mini?

o4-mini has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for reasoning mode, Magistral Small 2506 or o4-mini?

Both Magistral Small 2506 and o4-mini expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run Magistral Small 2506 and o4-mini?

Magistral Small 2506 is available on NVIDIA NIM. o4-mini is available on OpenAI API, OpenRouter, Replicate API, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.