GPT-4o (08-06) vs Mistral Large 2
GPT-4o (08-06) (2024) and Mistral Large 2 (2025) are compact production models from OpenAI and MistralAI. GPT-4o (08-06) ships a 128K-token context window, while Mistral Large 2 ships a 128K-token context window. On MMLU PRO, GPT-4o (08-06) leads by 5.0 pts. On pricing, Mistral Large 2 costs $0.48/1M input tokens versus $2.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mistral Large 2 is ~421% cheaper at $0.48/1M; pay for GPT-4o (08-06) only for coding workflow support.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-08-06 | 2025-11-25 |
| Context window | 128K | 128K |
| Parameters | 1.76T (8x222B MoE)* | 123B |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | True |
| Knowledge cutoff | 2023-10 | 2025-07 |
Pricing and availability
| Pricing attribute | GPT-4o (08-06) | Mistral Large 2 |
|---|---|---|
| Input price | $2.5/1M tokens | $0.48/1M tokens |
| Output price | $10/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Capability | GPT-4o (08-06) | Mistral Large 2 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
| Benchmark | GPT-4o (08-06) | Mistral Large 2 |
|---|---|---|
| MMLU PRO | 74.7 | 69.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has GPT-4o (08-06) at 74.7 and Mistral Large 2 at 69.7, with GPT-4o (08-06) ahead by 5.0 points. The largest visible gap is 5.0 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on function calling: Mistral Large 2, tool use: Mistral Large 2, and code execution: GPT-4o (08-06). Both models share vision, multimodal input, and structured outputs, 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 (08-06) lists $2.5/1M input and $10/1M output tokens, while Mistral Large 2 lists $0.48/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Large 2 lower by about $3.69 per million blended tokens. Availability is 3 providers versus 4, so concentration risk also matters.
Choose GPT-4o (08-06) when coding workflow support are central to the workload. Choose Mistral Large 2 when vision-heavy evaluation, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-4o (08-06) or Mistral Large 2?
GPT-4o (08-06) supports 128K tokens, while Mistral Large 2 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 (08-06) or Mistral Large 2?
Mistral Large 2 is cheaper on tracked token pricing. GPT-4o (08-06) costs $2.5/1M input and $10/1M output tokens. Mistral Large 2 costs $0.48/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-4o (08-06) or Mistral Large 2 open source?
GPT-4o (08-06) is listed under Proprietary. Mistral Large 2 is listed under True. 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 (08-06) or Mistral Large 2?
Both GPT-4o (08-06) and Mistral Large 2 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-4o (08-06) or Mistral Large 2?
Both GPT-4o (08-06) and Mistral Large 2 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 GPT-4o (08-06) and Mistral Large 2?
GPT-4o (08-06) is available on OpenAI API, Salesforce Einstein Generative AI, and OpenRouter. Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.