Mistral Magistral Small 2509 vs Phi 3.5 MoE Instruct
Mistral Magistral Small 2509 (2025) and Phi 3.5 MoE Instruct (2024) are compact production models from MistralAI and Microsoft Research. Mistral Magistral Small 2509 ships a not-yet-sourced context window, while Phi 3.5 MoE Instruct ships a 128K-token context window. On pricing, Mistral Magistral Small 2509 costs $0.5/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mistral Magistral Small 2509 is safer overall; choose Phi 3.5 MoE Instruct when provider fit matters.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-01 | 2024-08-20 |
| Context window | — | 128K |
| Parameters | — | 16x3.8B (42B, 6.6B active) |
| Architecture | - | decoder only |
| License | Proprietary | MIT |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Mistral Magistral Small 2509 | Phi 3.5 MoE Instruct |
|---|---|---|
| Input price | $0.5/1M tokens | $0.5/1M tokens |
| Output price | $1.5/1M tokens | $0.5/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Magistral Small 2509 | Phi 3.5 MoE Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Mistral Magistral Small 2509 lists $0.5/1M input and $1.5/1M output tokens, while Phi 3.5 MoE Instruct lists $0.5/1M input and $0.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi 3.5 MoE Instruct lower by about $0.3 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Mistral Magistral Small 2509 when provider fit are central to the workload. Choose Phi 3.5 MoE Instruct when provider fit 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 is cheaper, Mistral Magistral Small 2509 or Phi 3.5 MoE Instruct?
Mistral Magistral Small 2509 is cheaper on tracked token pricing. Mistral Magistral Small 2509 costs $0.5/1M input and $1.5/1M output tokens. Phi 3.5 MoE Instruct costs $0.5/1M input and $0.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Magistral Small 2509 or Phi 3.5 MoE Instruct open source?
Mistral Magistral Small 2509 is listed under Proprietary. Phi 3.5 MoE Instruct is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Where can I run Mistral Magistral Small 2509 and Phi 3.5 MoE Instruct?
Mistral Magistral Small 2509 is available on AWS Bedrock. Phi 3.5 MoE Instruct is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Mistral Magistral Small 2509 over Phi 3.5 MoE Instruct?
Mistral Magistral Small 2509 is safer overall; choose Phi 3.5 MoE Instruct when provider fit matters. If your workload also depends on provider fit, start with Mistral Magistral Small 2509; if it depends on provider fit, run the same evaluation with Phi 3.5 MoE Instruct.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.