Gemini 1.5 Pro vs Mistral Magistral Small 2509
Gemini 1.5 Pro (2024) and Mistral Magistral Small 2509 (2025) are general-purpose language models from Google DeepMind and MistralAI. Gemini 1.5 Pro ships a 2M-token context window, while Mistral Magistral Small 2509 ships a not-yet-sourced context window. On pricing, Mistral Magistral Small 2509 costs $0.5/1M input tokens versus $1.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mistral Magistral Small 2509 is ~150% cheaper at $0.5/1M; pay for Gemini 1.5 Pro only for provider fit.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-02-15 | 2025-09-01 |
| Context window | 2M | — |
| Parameters | — | — |
| Architecture | decoder only | - |
| License | Unknown | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Gemini 1.5 Pro | Mistral Magistral Small 2509 |
|---|---|---|
| Input price | $1.25/1M tokens | $0.5/1M tokens |
| Output price | $5/1M tokens | $1.5/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 1.5 Pro | Mistral Magistral Small 2509 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Gemini 1.5 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.
For cost, Gemini 1.5 Pro lists $1.25/1M input and $5/1M output tokens, while Mistral Magistral Small 2509 lists $0.5/1M input and $1.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Magistral Small 2509 lower by about $1.58 per million blended tokens. Availability is 2 providers versus 1, so concentration risk also matters.
Choose Gemini 1.5 Pro when provider fit and broader provider choice are central to the workload. Choose Mistral Magistral Small 2509 when provider fit and lower input-token cost 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 is cheaper, Gemini 1.5 Pro or Mistral Magistral Small 2509?
Mistral Magistral Small 2509 is cheaper on tracked token pricing. Gemini 1.5 Pro costs $1.25/1M input and $5/1M output tokens. Mistral Magistral Small 2509 costs $0.5/1M input and $1.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 1.5 Pro or Mistral Magistral Small 2509 open source?
Gemini 1.5 Pro is listed under Unknown. Mistral Magistral Small 2509 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 structured outputs, Gemini 1.5 Pro or Mistral Magistral Small 2509?
Gemini 1.5 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 Gemini 1.5 Pro and Mistral Magistral Small 2509?
Gemini 1.5 Pro is available on GCP Vertex AI and Google AI Studio. Mistral Magistral Small 2509 is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemini 1.5 Pro over Mistral Magistral Small 2509?
Mistral Magistral Small 2509 is ~150% cheaper at $0.5/1M; pay for Gemini 1.5 Pro only for provider fit. If your workload also depends on provider fit, start with Gemini 1.5 Pro; if it depends on provider fit, run the same evaluation with Mistral Magistral Small 2509.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.