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Gemini 2.5 Flash vs Mistral Small 4

Gemini 2.5 Flash (2025) and Mistral Small 4 (2026) are general-purpose language models from Google DeepMind and MistralAI. Gemini 2.5 Flash ships a 1M-token context window, while Mistral Small 4 ships a 256k-token context window. On pricing, Mistral Small 4 costs $0.15/1M input tokens versus $0.3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Mistral Small 4 is ~100% cheaper at $0.15/1M; pay for Gemini 2.5 Flash only for coding workflow support.

Specs

Specification
Released2025-06-172026-03-16
Context window1M256k
Parameters119B (6.5B active)
Architecturedecoder onlymoe
LicenseProprietaryApache 2.0
Knowledge cutoff2025-01-

Pricing and availability

Pricing attributeGemini 2.5 FlashMistral Small 4
Input price$0.3/1M tokens$0.15/1M tokens
Output price$2.5/1M tokens$0.6/1M tokens
Providers

Capabilities

CapabilityGemini 2.5 FlashMistral Small 4
VisionYesYes
MultimodalYesYes
ReasoningNoNo
Function callingYesYes
Tool useYesYes
Structured outputsYesNo
Code executionYesNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Gemini 2.5 Flash and code execution: Gemini 2.5 Flash. Both models share vision, multimodal input, function calling, and tool use, 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 2.5 Flash lists $0.3/1M input and $2.5/1M output tokens, while Mistral Small 4 lists $0.15/1M input and $0.6/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Small 4 lower by about $0.68 per million blended tokens. Availability is 4 providers versus 2, so concentration risk also matters.

Choose Gemini 2.5 Flash when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Mistral Small 4 when vision-heavy evaluation 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 has a larger context window, Gemini 2.5 Flash or Mistral Small 4?

Gemini 2.5 Flash supports 1M tokens, while Mistral Small 4 supports 256k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Gemini 2.5 Flash or Mistral Small 4?

Mistral Small 4 is cheaper on tracked token pricing. Gemini 2.5 Flash costs $0.3/1M input and $2.5/1M output tokens. Mistral Small 4 costs $0.15/1M input and $0.6/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Gemini 2.5 Flash or Mistral Small 4 open source?

Gemini 2.5 Flash is listed under Proprietary. Mistral Small 4 is listed under Apache 2.0. 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, Gemini 2.5 Flash or Mistral Small 4?

Both Gemini 2.5 Flash and Mistral Small 4 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for multimodal input, Gemini 2.5 Flash or Mistral Small 4?

Both Gemini 2.5 Flash and Mistral Small 4 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run Gemini 2.5 Flash and Mistral Small 4?

Gemini 2.5 Flash is available on Google AI Studio, GCP Vertex AI, Replicate API, and OpenRouter. Mistral Small 4 is available on OpenRouter and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.