GPT-4o (05-13) vs Mistral Large 2 (2407)
GPT-4o (05-13) (2024) and Mistral Large 2 (2407) (2024) are compact production models from OpenAI and MistralAI. Both ship a 128K-token context window. On MMLU PRO, GPT-4o (05-13) leads by 6.6 pts. On pricing, Mistral Large 2 (2407) costs $0.50/1M input tokens versus $2.50/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Mistral Large 2 (2407) is ~400% cheaper at $0.50/1M; pay for GPT-4o (05-13) only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GPT-4o (05-13) | Mistral Large 2 (2407) |
|---|---|---|
| Best for | multimodal apps and provider-routed production | tool-calling agents and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 128K | 128K |
| Cheapest output | $10/1M tokens | $1.50/1M tokens |
| Provider routes | 4 tracked | 7 tracked |
| Shared benchmarks | MMLU PRO leader | 3 shared |
Decision tradeoffs
- GPT-4o (05-13) holds a shared-benchmark lead on MMLU PRO, ahead by 6.6 points.
- GPT-4o (05-13) uniquely exposes Vision, Multimodal, and Code execution in local model data.
- Local decision data tags GPT-4o (05-13) for Coding, RAG, and Agents.
- Mistral Large 2 (2407) holds a shared-benchmark lead on HumanEval, ahead by 1.8 points.
- Mistral Large 2 (2407) has the lower cheapest tracked output price at $1.50/1M tokens.
- Mistral Large 2 (2407) has broader tracked provider coverage for fallback and route flexibility.
- Mistral Large 2 (2407) uniquely exposes JSON / Tool use in local model data.
- Local decision data tags Mistral Large 2 (2407) for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-4o (05-13)
$4,500
Cheapest tracked route/tier: OpenAI API
Mistral Large 2 (2407)
$775
Cheapest tracked route/tier: Chutes AI
Estimated monthly gap: $3,725. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Mistral Large 2 (2407) is $8.50/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Code execution before moving production traffic.
- Mistral Large 2 (2407) adds JSON / Tool use in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-4o (05-13) is $8.50/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for JSON / Tool use before moving production traffic.
- GPT-4o (05-13) adds Vision, Multimodal, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-05-13 | 2024-07-24 |
| Context window | 128K | 128K |
| Parameters | 1.76T (8x222B MoE)* | 123B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Proprietary | Mistral License |
| Openness | Proprietary | Open weights |
| Weights | Not released | Available |
| Code | Unknown | Unknown |
| Commercial use | Restricted | Not permitted |
| Knowledge cutoff | 2023-10 | 2024-03 |
Pricing and availability
| Pricing attribute | GPT-4o (05-13) | Mistral Large 2 (2407) |
|---|---|---|
| Input price | $2.50/1M tokens | $0.50/1M tokens |
| Output price | $10/1M tokens | $1.50/1M tokens |
| Providers |
Capabilities
| Capability | GPT-4o (05-13) | Mistral Large 2 (2407) |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| JSON / Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GPT-4o (05-13) | Mistral Large 2 (2407) |
|---|---|---|
| MMLU PRO | 72.5 | 65.9 |
| HumanEval | 90.2 | 92.0 |
| Massive Multitask Language Understanding | 88.7 | 84.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has GPT-4o (05-13) at 72.5 and Mistral Large 2 (2407) at 65.9, with GPT-4o (05-13) ahead by 6.6 points; HumanEval has GPT-4o (05-13) at 90.2 and Mistral Large 2 (2407) at 92, with Mistral Large 2 (2407) ahead by 1.8 points; Massive Multitask Language Understanding has GPT-4o (05-13) at 88.7 and Mistral Large 2 (2407) at 84, with GPT-4o (05-13) ahead by 4.7 points. The largest visible gap is 6.6 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 vision: GPT-4o (05-13), multimodal input: GPT-4o (05-13), JSON / Tool use: Mistral Large 2 (2407), and code execution: GPT-4o (05-13). Both models share 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 (05-13) lists $2.50/1M input and $10/1M output tokens on the cheapest tracked provider, while Mistral Large 2 (2407) lists $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Large 2 (2407) lower by about $3.95 per million blended tokens. Availability is 4 providers versus 7, so concentration risk also matters.
Choose GPT-4o (05-13) when coding workflow support are central to the workload. Choose Mistral Large 2 (2407) when provider fit, 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 (05-13) or Mistral Large 2 (2407)?
GPT-4o (05-13) supports 128K tokens, while Mistral Large 2 (2407) 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 (05-13) or Mistral Large 2 (2407)?
Mistral Large 2 (2407) is cheaper on tracked token pricing. GPT-4o (05-13) costs $2.50/1M input and $10/1M output tokens. Mistral Large 2 (2407) costs $0.50/1M input and $1.50/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-4o (05-13) or Mistral Large 2 (2407) open source?
GPT-4o (05-13) is listed under Proprietary. Mistral Large 2 (2407) is listed under Mistral License. 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 (05-13) or Mistral Large 2 (2407)?
GPT-4o (05-13) has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. 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 (05-13) or Mistral Large 2 (2407)?
GPT-4o (05-13) 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 (05-13) and Mistral Large 2 (2407)?
GPT-4o (05-13) is available on Azure OpenAI, OpenAI API, OpenRouter, and Replicate API. Mistral Large 2 (2407) is available on Microsoft Foundry, IBM watsonx, OpenRouter, AWS Bedrock, and Chutes AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-10-17. Data sourced from public model cards and provider documentation.