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GPT-4o Mini (07-18) vs Mistral Small 4

GPT-4o Mini (07-18) (2024) and Mistral Small 4 (2026) are compact production models from OpenAI and MistralAI. GPT-4o Mini (07-18) ships a 128K-token context window, while Mistral Small 4 ships a 256k-token context window. On pricing, GPT-4o Mini (07-18) costs $0.15/1M input tokens versus $0.15/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Mistral Small 4 is safer overall; choose GPT-4o Mini (07-18) when coding workflow support matters.

Specs

Specification
Released2024-07-182026-03-16
Context window128K256k
Parameters119B (6.5B active)
Architecturedecoder onlymoe
LicenseProprietaryApache 2.0
Knowledge cutoff2023-10-

Pricing and availability

Pricing attributeGPT-4o Mini (07-18)Mistral Small 4
Input price$0.15/1M tokens$0.15/1M tokens
Output price$0.6/1M tokens$0.6/1M tokens
Providers

Capabilities

CapabilityGPT-4o Mini (07-18)Mistral Small 4
VisionYesYes
MultimodalNoYes
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsYesNo
Code executionYesNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on multimodal input: Mistral Small 4, function calling: Mistral Small 4, tool use: Mistral Small 4, structured outputs: GPT-4o Mini (07-18), and code execution: GPT-4o Mini (07-18). Both models share vision, 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, GPT-4o Mini (07-18) lists $0.15/1M input and $0.6/1M 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 GPT-4o Mini (07-18) lower by about $0 per million blended tokens. Availability is 3 providers versus 2, so concentration risk also matters.

Choose GPT-4o Mini (07-18) when coding workflow support and broader provider choice are central to the workload. Choose Mistral Small 4 when long-context analysis and larger context windows 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.

FAQ

Which has a larger context window, GPT-4o Mini (07-18) or Mistral Small 4?

Mistral Small 4 supports 256k tokens, while GPT-4o Mini (07-18) supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, GPT-4o Mini (07-18) or Mistral Small 4?

GPT-4o Mini (07-18) is cheaper on tracked token pricing. GPT-4o Mini (07-18) costs $0.15/1M input and $0.6/1M 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 GPT-4o Mini (07-18) or Mistral Small 4 open source?

GPT-4o Mini (07-18) 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, GPT-4o Mini (07-18) or Mistral Small 4?

Both GPT-4o Mini (07-18) 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, GPT-4o Mini (07-18) or Mistral Small 4?

Mistral Small 4 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run GPT-4o Mini (07-18) and Mistral Small 4?

GPT-4o Mini (07-18) is available on OpenAI API, OpenRouter, and Replicate API. 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.