LLM Compare
Head to head

Mistral Large 4 vs Grok 4.7

How Mistral Large 4 and Grok 4.7 stack up across benchmarks, pricing, speed, and the workloads that matter.

Mistral Large 4

Mistral AI · Proprietary

Blended price$0.84per 1M tokens
Context1Mtokens
Speedn/atok/s
Benchmarks18results
VS

Grok 4.7

xAI · Proprietary

Blended price$2.44per 1M tokens
Context500Ktokens
Speedn/atok/s
Benchmarks23results

Mistral Large 4 is the cheaper of the two at $0.84 per million blended tokens, about 2.92x less than Grok 4.7 at $2.44. On coding, Mistral Large 4 leads by about 19 points in our normalized benchmark average.

The table below breaks down every workload axis where both models have published results. Each score is a normalized 0 to 1 average across the benchmarks tagged with that category. A gap of a few points is noise; a gap of ten or more is a real difference in capability. Where one model has not reported a result, the cell shows n/a and the missing benchmark does not drag its average down.

Benchmark scores by workload

WorkloadMistral Large 4Grok 4.7Edge
Reasoning 63% 59% +3.6 pts
Coding 68% 49% +18.9 pts
Agents & tool use 52% 42% +10 pts
Math 92% n/a n/a
Vision & multimodal 41% n/a n/a
Writing 46% 55% +8.8 pts
Knowledge & factuality 17% 38% +20.8 pts

The headline benchmarks below are the most widely cited individual tests. GPQA Diamond measures graduate-level reasoning in physics, chemistry, and biology. SWE-Bench Verified tests whether a model can fix real GitHub issues. MMMU-Pro covers college-level multimodal understanding across six disciplines. AIME and FrontierMath push competitive and research math. BrowseComp measures web research ability.

Headline benchmarks

BenchmarkMistral Large 4Grok 4.7

Benchmarks tell you what a model can do in a controlled setting. They do not tell you whether it will work on your specific task, with your specific data, at your specific scale. The recommendations below map each common workload to whichever of these two models scores higher on the relevant axis. Use them as a starting point, not a final answer.

Which should you choose?

Hard reasoning

Multi-step analysis, research, and problems that need sustained thought.

Mistral Large 4

Coding & software

Writing, reviewing, and debugging code across a real codebase.

Mistral Large 4

Agents & tool use

Long-running agents that call tools, browse, and act on their own.

Mistral Large 4

Math & science

Formal math, competitive problems, and quantitative science.

Mistral Large 4

Vision & documents

Reading images, screenshots, charts, and dense documents.

Mistral Large 4

Writing & drafting

Copy, emails, and long-form drafting where tone matters.

Grok 4.7

High-volume & cost-sensitive

Cheap, repetitive calls where the blended token price dominates.

Mistral Large 4

Scores are normalized from public benchmarks published by llm-stats.com and averaged per workload. Pricing is the blended input/output cost per million tokens at an 8:1 mix. Refreshes daily. How this works.