Model comparison
Grok 4.7 vs Mistral Large
Grok 4.7 is the stronger model overall, scoring 46.6 to 31.6 on the Noometry Index.
Last verified . 15 shared benchmarks.
Mistral AISummary
- They share 15 benchmarks with published results for both. Grok 4.7 scores higher in 8 categories and Mistral Large in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Grok 4.7 leads 70.1 to 40.9.
- The biggest single-benchmark swing is SciCode: 57.4% for Grok 4.7 and 36.2% for Mistral Large.
- Both cost about the same: $2 input and $6 output per million tokens.
- Grok 4.7 accepts more context: 500K tokens versus 131K.
- Mistral Large has downloadable open weights; the other is API-only.
Side by side
| Grok 4.7 | Mistral Large | |
|---|---|---|
| Provider | xAI | Mistral AI |
| Noometry Index | 46.6 | 31.6 |
| Released | 2026-09-21 | 2024-02-26 |
| Weights | Proprietary | Open |
| Context window | 500K | 131K |
| Max output | 500K | 16K |
| Input $ / M tokens | $2 | $2 |
| Output $ / M tokens | $6 | $6 |
| Results tracked | 21 | 51 |
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Category by category
Coding Grok 4.7 leads
Grok 4.7: 55.0 (#23), Mistral Large: 33.8 (#240)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| SciCode | 57.4% | 36.2% |
| LMArena Coding | 1423 | 1277 |
| CursorBench | 46.3% | — |
| LMArena WebDev | 1636 | — |
| FrontierSWE | 29.5% | — |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | — | 38.3% |
| ALE-Bench | — | 264.7 |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |
Agentic & Tool Use Not comparable
Grok 4.7: —, Mistral Large: 28.4 (#83)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 38.4% |
Reasoning Grok 4.7 leads
Grok 4.7: 40.1 (#49), Mistral Large: 15.4 (#305)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| CritPt | 17.7% | 0% |
| LMArena Hard Prompts | 1409 | 1257 |
| SimpleBench | — | 22.5% |
| NYT Connections (extended) | 76.8% | — |
| LiveBench Reasoning | — | 43.5% |
| DTBench | — | 65.1% |
| LiveBench Data Analysis | — | 50.1% |
| LMCA | — | 16.7% |
| Epoch Capabilities Index | — | 128.52 |
| ForecastBench | — | 57.1 |
| LiveBench | — | 48.4% |
Math Grok 4.7 leads
Grok 4.7: 41.1 (#73), Mistral Large: 17.1 (#285)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| LMArena Math | 1393 | 1262 |
| OTIS Mock AIME 2024-2025 | — | 8.5% |
| ProofBench | 34% | — |
| Omni-MATH | — | 28.1% |
| LiveBench Math | — | 42.5% |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |
Knowledge Grok 4.7 leads
Grok 4.7: 38.7 (#130), Mistral Large: 30.0 (#224)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| LMArena Expert | 1413 | 1232 |
| GPQA Diamond | — | 51.3% |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| GPQA (HELM) | — | 43.5% |
| MMLU | — | 80% |
Multimodal Not comparable
Grok 4.7: 28.8 (#107), Mistral Large: —
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| Furniture Assembly | 20.8% | — |
Multilingual Grok 4.7 leads
Grok 4.7: 51.2 (#108), Mistral Large: 40.1 (#214)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| LMArena Non-English | 1392 | 1237 |
| LMArena Chinese | 1476 | 1240 |
| LMArena Russian | 1396 | 1257 |
| LMArena French | — | 1324 |
| LMArena German | — | 1254 |
| LMArena Japanese | — | 1187 |
| LMArena Korean | — | 1202 |
| LMArena Spanish | — | 1268 |
Instruction Following Grok 4.7 leads
Grok 4.7: 74.3 (#98), Mistral Large: 68.1 (#186)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| LMArena Instruction Following | 1406 | 1249 |
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |
Long Context Grok 4.7 leads
Grok 4.7: 43.2 (#97), Mistral Large: 38.3 (#194)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1416 | 1262 |
Writing & Preference Grok 4.7 leads
Grok 4.7: 70.1 (#23), Mistral Large: 40.9 (#237)
| Benchmark | Grok 4.7 | Mistral Large |
|---|---|---|
| LMArena Text | 1397 | 1266 |
| LMArena Creative Writing | 1391 | 1243 |
| EQ-Bench Creative Writing | 2007 | 985 |
| LMArena Multi-Turn | 1389 | 1260 |
| Short-Story Creative Writing | — | 69% |
| WildBench | — | 80.1% |
| LiveBench Language | — | 39.4% |
Frequently asked questions
Is Grok 4.7 better than Mistral Large?
Grok 4.7 is the stronger model overall, scoring 46.6 to 31.6 on the Noometry Index.
Which is cheaper, Grok 4.7 or Mistral Large?
Mistral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Grok 4.7 lists at $2 and $6.
Is Grok 4.7 or Mistral Large better for coding?
Grok 4.7 scores higher on coding benchmarks: 55.0 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
Grok 4.7 does, with 500K tokens against 131K.
How many benchmarks do Grok 4.7 and Mistral Large share?
15 benchmarks have published results for both models. Grok 4.7 has 21 scored results on Noometry and Mistral Large has 51.