GPT-4o vs Mistral Large
Pricing, benchmarks, and use case comparison
Verdict
Our pick: Mistral LargePick GPT-4o for fast, cheap multimodal everyday tasks with mature tooling; pick Mistral Large for stronger reasoning, multilingual work, open weights, and self-hosting.
Specs comparison
| GPT-4o | Mistral Large | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Type | Closed source | Closed source |
| Context window | 128,000 tokens (16,384 max output) | ✓128000 |
| Input / 1M tokens | $2.50 | ✓2.00 |
| Output / 1M tokens | $10.00 | 6.00 |
| Release date | 2024-05 | 2024-02 |
Benchmarks
| Benchmark | GPT-4o | Mistral Large |
|---|---|---|
| MMLU | ✓88.7% | 84.0% |
| HumanEval | 90.2% | ✓92.0% |
| MATH | 76.6% | - |
Scores sourced from official provider release posts and independent benchmark aggregators.
Capability and benchmarks
Mistral Large is the stronger reasoner and coder. It reports 92.0% HumanEval and 84.0% MMLU, with capability scores of reasoning 85 and coding 82. GPT-4o reports 90.2% HumanEval, 88.7% MMLU, and 76.6% MATH, but its capability profile is more everyday-assistant (reasoning 68, coding 72). For nuanced reasoning, multilingual generation, and structured output across 80+ programming languages, Mistral Large leads; GPT-4o is tuned for fast, direct instruction-following.
Price, speed, and deployment
GPT-4o is faster and multimodal-friendly: $2.50 input / $10 output per 1M (cached input $1.25), a 128K context, text and image input, and very mature tooling (capability speed 85). Mistral Large is $2/$6 per 1M (cheaper on output), handles text and images, and is notably open-weight, so you can self-host for data sovereignty. Its context window is not published, which is a consideration for long-input work.
Which to pick
- Pick GPT-4o for high-volume everyday assistant tasks, image understanding with fast responses, and deep ecosystem integration.
- Pick Mistral Large for stronger reasoning and coding, multilingual and structured-output work, lower output cost, and the option to self-host open weights.
Which should you choose?
Choose GPT-4o if...
- →Everyday assistant, drafting, summarization, and classification tasks
- →Latency- and cost-sensitive applications at scale
- →Multimodal tasks needing image understanding with fast responses
Choose Mistral Large if...
- →You need a strong European-built flagship with open weights
- →Your work is multilingual or requires nuanced reasoning
- →You want structured/JSON output and solid coding ability
- →You need the option to self-host for data sovereignty