# Atlas with Magistral Small: Open Reasoning for the Plan Agent in 2026 > Magistral Small emits an explicit chain of thought at $0.50 / 1M input tokens, a quarter the input price of Magistral Medium, over a 128,000 token window. Magistral Small is Mistral's first open reasoning model, and inside Atlas it changes what the plan agent is for. Magistral Small emits an explicit chain of thought before answering, which turns Atlas's plan agent from a summarizer into an actual step-by-step debugger for $0.50 / 1M input tokens and $1.50 / 1M output tokens across a 128,000 token window. The 24B weights are open, so the same reasoning model can be pulled locally via Ollama for offline work. ## Key takeaways - Magistral Small is Mistral's first open reasoning model, emitting an explicit chain of thought before answering. - Pricing is $0.50 / 1M input tokens and $1.50 / 1M output tokens, a quarter the input price of Magistral Medium. - 128,000 tokens in and 128,000 tokens out, so a long reasoning chain plus the final patch fit in one response. - 24B open weights can be pulled into Ollama, so the same reasoning model runs offline. - Reasoning tokens bill as output, so a hard bug can cost far more than the token count of the final diff suggests. ## What does Magistral Small change about Atlas's plan agent? Magistral Small emits an explicit chain of thought before answering, which turns Atlas's plan agent from a summarizer into an actual step-by-step debugger for $0.50 / 1M input tokens. Atlas drafts a plan in a read-only plan agent and asks before switching to a build agent, and Magistral Small makes that read-only phase genuinely analytical. Without a reasoning model, a plan agent mostly restates the ticket back to you in bullet form. With Magistral Small, the plan phase becomes a place where a hypothesis is formed, tested against the code, and discarded if it does not hold. The read-only constraint is what makes this safe to run aggressively: no edits happen while the model is thinking, and Atlas will ask before it switches to a build agent. Reasoning at $0.50 / 1M input tokens is cheap enough that you can afford to let Magistral Small think through a plan on ordinary work, not just on emergencies. ## How much does Magistral Small cost compared with Magistral Medium? Magistral Small costs $0.50 / 1M input tokens and $1.50 / 1M output tokens, a quarter the input price of Magistral Medium. For Atlas users who want reasoning traces on routine planning turns rather than only on the hardest bugs, that 4x gap is the deciding number. The invoice trap with any reasoning model is that reasoning tokens are billed as output. On Magistral Small that means $1.50 / 1M output tokens applies to the entire chain of thought, not just the final answer, so a hard bug can cost far more than the token count of the final diff suggests. Budget by problem difficulty, not by patch size. A 20 line fix that took Magistral Small a long chain to find is an expensive 20 lines, and that is usually still cheaper than the wrong 200 lines you would have written without it. ## Can Magistral Small run locally with Ollama? Yes. Magistral Small ships 24B open weights, so the same reasoning model can be pulled locally via Ollama for offline work. Paired with Atlas's local embedding index, an entire reasoning-driven debugging session can run without source code leaving your machine. Magistral Small being open is genuinely unusual for a reasoning model, and it is the reason it appears in air-gapped Atlas setups. Atlas can build its code index with local Ollama embeddings, keeping code off third-party servers, so the retrieval half is already local. Adding Magistral Small's 24B weights to the same Ollama runtime makes the generation half local too. The 128,000 token window travels with the weights, so a self-hosted Magistral Small still holds a stack trace, the failing test, and the code path in one context. ## Why is Magistral Small a poor small_model choice for Atlas? Magistral Small has a slower first token than Mistral Small 3.2, which makes it a poor small_model choice. Atlas's cheap slot handles session titles and summaries, and a reasoning chain in front of a one-line title is latency you pay for on every single turn. The small_model slot is defined by frequency, not by difficulty. It fires constantly, and every millisecond of first-token latency is felt in the TUI. Magistral Small's reasoning trace is exactly the wrong shape for that workload: valuable when the answer is hard, wasteful when the answer is a four word session title. Keep Magistral Small in the primary slot for planning and debugging, and put a fast non-reasoning model in `"small_model"`. Atlas lets you switch the active model and provider on the fly with favorites and recents, so a bad slot assignment is a two second fix. ## How do you combine Magistral Small with Devstral in one Atlas session? Run Atlas's plan agent on Magistral Small at $0.50 / 1M input tokens, then switch to Devstral for the build pass with `/models` in the TUI. Reasoning finds the fix, an agent-trained coding model writes it, and neither model pays for the other's weakness. The two-model workflow is the most cost-effective way to use Magistral Small. Reasoning is expensive per token and slow per turn, but it is only needed while the answer is unknown. Once the plan exists, the work becomes typing, and a coding model does that faster and cheaper. Atlas computes a unified diff for every file edit and surfaces it for approval before writing, so the handoff is visible: you read the plan Magistral Small produced, approve it, and watch the build model turn it into diffs. The 128,000 token window on Magistral Small holds the long reasoning chain plus the final patch in one response if you would rather not switch at all. ## Setup 1. Export MISTRAL_API_KEY in the shell where Atlas runs. 2. Run `atlas models mistral` and confirm magistral-small is present. 3. Pin `"model": "mistral/magistral-small"` in atlas.json. 4. Run Atlas's plan agent on the reasoning model and switch to Devstral for the build pass with `/models` in the TUI. 5. For offline work, pull the 24B open weights into Ollama and point Atlas at the local runtime. ## FAQ ### what is magistral small Magistral Small is Mistral's first open reasoning model. It emits an explicit chain of thought before answering, runs a 128,000 token window, and costs $0.50 / 1M input tokens and $1.50 / 1M output tokens. ### how much does magistral small cost per million tokens Magistral Small costs $0.50 / 1M input tokens and $1.50 / 1M output tokens, a quarter the input price of Magistral Medium. Reasoning tokens are billed as output, so hard problems cost more than the final diff suggests. ### can I run magistral small locally Yes. Magistral Small ships 24B open weights, so the same reasoning model can be pulled locally via Ollama for offline work, alongside Atlas's local Ollama embedding index. ### how do I use magistral small in atlas Export MISTRAL_API_KEY, run `atlas models mistral` and confirm magistral-small is present, then pin `"model": "mistral/magistral-small"` in atlas.json. Run the plan agent on it and switch to Devstral for the build pass. ### should magistral small be my small_model in atlas No. Magistral Small has a slower first token than Mistral Small 3.2, which makes it a poor small_model choice. The cheap slot fires constantly for titles and summaries, where a reasoning chain is latency you pay for on every turn. ### magistral small vs magistral medium for debugging Magistral Small gives reasoning traces at a quarter the input price of Magistral Medium's $2.00 / Mtok. Magistral Medium is the stronger multi-hop reasoner, so use Small for routine planning and step up when a root cause spans several services. ### why is my reasoning model bill higher than expected Reasoning tokens are billed as output. On Magistral Small that means the entire chain of thought is charged at $1.50 / 1M output tokens, so a hard bug can cost far more than the token count of the final diff implies. --- Canonical HTML: https://runatlas.sh/resources/models/magistral-small Source of truth: aeo_pages row `/resources/models/magistral-small` (segment: Models) (this file is generated from it, never hand-edited). Licence: Atlas is proprietary with a free core. It is not open source and there is no public source repository.