Magistral Medium is the large half of Mistral's reasoning line, priced at $2.00 / 1M input tokens and $5.00 / 1M output tokens. Inside Atlas it is the model to reach for when the agent has to work backwards from a stack trace across several services, not when it needs to type a lot of code. Max output is only 16,384 tokens, and reasoning tokens eat into that budget, so Magistral Medium cannot emit a huge patch. Use it for the diagnosis, then apply the fix with a cheaper model.
When is Magistral Medium the right model for an Atlas session?
Magistral Medium is the right model when Atlas has to work backwards from a stack trace across several services. A full reasoning chain over a 128,000 token window is enough to hold the stack trace, the failing test, and the two services involved at $2.00 / 1M input tokens.
Multi-hop root cause is the specific job. A failing test in one service caused by a contract change in another is the class of bug that defeats pattern matching and rewards actual reasoning. Magistral Medium holds all of it in context at once. Atlas searches code with hybrid semantic and keyword retrieval fused by reciprocal rank fusion, so the two services and the failing path can be assembled into the 128,000 token window without hand-picking files. What Magistral Medium is not for is typing. Reach for it when the question is why, not when the task is how much code.
Why does the 16,384 token output cap matter on Magistral Medium?
Magistral Medium caps max output at only 16,384 tokens, and reasoning tokens eat into that budget, so it cannot emit a huge patch. Inside Atlas, the practical consequence is to ask for the fix as a plan first, then apply it with a cheaper model.
The output cap is the defining constraint of Magistral Medium, and it is easy to miss when you see the 128,000 token input window. Reading is generous, writing is not, and the chain of thought competes with the patch for the same 16,384 tokens. Trying to get a large refactor out of Magistral Medium in one turn will truncate. The workflow that respects the cap: let Magistral Medium reason to a diagnosis and produce a plan, then switch models for the build. Atlas drafts a plan in a read-only plan agent and asks before switching to a build agent, so the boundary is already built into the tool.
How much does Magistral Medium cost to run in Atlas?
Magistral Medium costs $2.00 / 1M input tokens and $5.00 / 1M output tokens. Add invisible reasoning tokens billed at the output rate, and Magistral Medium becomes the wrong default for a long agentic session, however good it is on a hard bug.
The $5.00 / 1M output tokens rate is the number that decides how you use Magistral Medium. Reasoning tokens are output tokens, and they are not visible in the final answer, so a session can bill far more than the diffs suggest. The defence is to keep routine traffic off the model entirely. Set `"small_model": "mistral/mistral-small-2506"` so Atlas does not send routine summaries to a $5.00 / Mtok reasoner, and pin Magistral Medium only for the debugging session, not as your all-day default. Atlas fans out work to subagents that can run in the foreground or in parallel background sessions, and a wide fan-out on a $5.00 output model is the fastest way to a surprising invoice.
Why do regulated teams choose Magistral Medium over US reasoning APIs?
Magistral Medium is enterprise-deployable in the EU alongside the rest of the Mistral line, which is why regulated teams pick it over US reasoning APIs in 2026. At $2.00 per 1M input tokens, its full reasoning chain runs in-region, so a data residency requirement does not cost you a reasoning model.
Where the model runs is a hard requirement in some organisations, not a preference. Magistral Medium being deployable in the EU means a regulated team can put a real reasoning model behind Atlas without a legal exception. Atlas adds its own controls on top: every Atlas tool call is permission-gated against allow, ask, and deny rules before it runs, and Atlas can build its code index with local Ollama embeddings, keeping code off third-party servers. Retrieval stays local, generation stays in-region, and the agent still cannot touch a file without passing the permission rules.
When should you use Magistral Small or Devstral instead of Magistral Medium?
Use Magistral Small instead of Magistral Medium for routine planning, since Magistral Medium is 4x the input price at $2.00 / Mtok. Use Devstral for the build pass, because Magistral Medium's 16,384 token output cap cannot carry a large patch anyway.
Magistral Medium is a scalpel and it is priced like one. It is noticeably stronger on multi-hop root-cause work than Magistral Small, and that strength is worth $2.00 / 1M input tokens on the bug that has eaten two days. It is not worth it on a scoped ticket where the fix is already understood. Atlas lets you switch the active model and provider on the fly with favorites and recents, so the healthy pattern is to favorite Magistral Medium, summon it for the diagnosis, then cycle back to a cheaper model for the code. Atlas snapshots file changes as git patches so edits can be diffed and rolled back, which keeps the cheap build pass low risk.
Setup
- 01Export MISTRAL_API_KEY or run `atlas login` and select Mistral.
- 02Verify magistral-medium-latest with `atlas models mistral`.
- 03Pin `"model": "mistral/magistral-medium-latest"` in atlas.json only for the debugging session, not as your all-day default.
- 04Set `"small_model": "mistral/mistral-small-2506"` so Atlas does not send routine summaries to a $5.00 / Mtok reasoner.
- 05Because output is capped at 16,384 tokens, ask for the fix as a plan first, then apply it with a cheaper model.
Frequently asked questions
- how much does magistral medium cost
- Magistral Medium costs $2.00 / 1M input tokens and $5.00 / 1M output tokens. Reasoning tokens bill at the output rate and are invisible in the final answer, which makes it the wrong default for a long agentic session.
- what is magistral medium max output tokens
- Magistral Medium caps output at 16,384 tokens, and reasoning tokens eat into that budget, so it cannot emit a huge patch. Ask Atlas for the fix as a plan first, then apply it with a cheaper model.
- best model for debugging across multiple services
- Magistral Medium is built for exactly that. Its reasoning chain runs over a 128,000 token window, enough to hold a stack trace, the failing test, and the two services involved, which is why Atlas users reach for it on multi-hop root cause.
- how do I set up magistral medium in atlas
- Export MISTRAL_API_KEY or run `atlas login` and select Mistral, verify magistral-medium-latest with `atlas models mistral`, then pin `"model": "mistral/magistral-medium-latest"` in atlas.json for the debugging session.
- magistral medium vs magistral small which should I use
- Magistral Medium is 4x the input price of Magistral Small at $2.00 / Mtok but noticeably stronger on multi-hop root-cause work. Use Magistral Small for routine planning and reserve Magistral Medium for the bug that resists everything else.
- is magistral medium available in the eu
- Yes. Magistral Medium is enterprise-deployable in the EU alongside the rest of the Mistral line, which is why regulated teams pick it over US reasoning APIs when running an agent like Atlas.
- what small_model should I pair with magistral medium
- Set `"small_model": "mistral/mistral-small-2506"` so Atlas does not send routine summaries and session titles to a $5.00 / Mtok reasoner. Keep Magistral Medium in the primary slot for the diagnosis only.
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