Model comparison
Grok 4.6 vs Mistral 7B
Grok 4.6 is the stronger model overall, scoring 56.9 to 23.0 on the Noometry Index. Mistral 7B costs 12× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Mistral AISummary
- They share 21 benchmarks with published results for both. Grok 4.6 scores higher in 8 categories and Mistral 7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Grok 4.6 leads 67.0 to 8.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 99.2% for Grok 4.6 and 0.3% for Mistral 7B.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $2 / $6 for Grok 4.6.
- Grok 4.6 accepts more context: 500K tokens versus 8K.
- Mistral 7B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.6 | Mistral 7B | |
|---|---|---|
| Provider | xAI | Mistral AI |
| Noometry Index | 56.9 | 23.0 |
| Released | 2026-08-12 | 2023-09-27 |
| Weights | Proprietary | Open |
| Context window | 500K | 8K |
| Max output | 500K | 8K |
| Input $ / M tokens | $2 | $0.25 |
| Output $ / M tokens | $6 | $0.25 |
| Results tracked | 49 | 37 |
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Category by category
Coding Grok 4.6 leads
Grok 4.6: 58.5 (#16), Mistral 7B: 26.4 (#326)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| LMArena Coding | 1465 | 1082 |
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| CursorBench | 41.4% | — |
| LMArena WebDev | 1617 | — |
| FrontierSWE | 25.3% | — |
| SciCode | 56.5% | — |
| WeirdML | 67.3% | — |
| BigCodeBench Instruct | — | 19.5% |
| BigCodeBench Complete | — | 27.3% |
| ALE-Bench | 1,508 | — |
| HumanEval+ | — | 36% |
| MBPP+ | — | 42.1% |
Agentic & Tool Use Not comparable
Grok 4.6: 39.4 (#27), Mistral 7B: —
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| APEX-Agents | 65.3% | — |
| GDP.pdf | 17.2% | — |
| Vending-Bench 2 | 9,047 | — |
Reasoning Grok 4.6 leads
Grok 4.6: 61.4 (#20), Mistral 7B: 13.1 (#336)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| Chess Puzzles | 40% | 0% |
| LMArena Hard Prompts | 1447 | 1067 |
| DTBench | 97.3% | 42.5% |
| Epoch Capabilities Index | 156.44 | 112.21 |
| ARC-AGI-2 | 67.1% | — |
| SimpleBench | 75.9% | — |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| CritPt | 19.7% | — |
| EBR-Bench | 30.5% | — |
| Mystery Game Puzzles | 34% | — |
| LMCA | 48.5% | — |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| HellaSwag | — | 81% |
| PIQA | — | 83% |
| WinoGrande | — | 75.3% |
Math Grok 4.6 leads
Grok 4.6: 67.0 (#24), Mistral 7B: 8.1 (#325)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 99.2% | 0.3% |
| LMArena Math | 1423 | 1085 |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 31.7% | — |
| ProofBench | 51% | — |
| MATH Level 5 | — | 3.7% |
| GSM8K | — | 54.4% |
Knowledge Grok 4.6 leads
Grok 4.6: 63.3 (#20), Mistral 7B: 7.4 (#311)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| GPQA Diamond | 94% | 15.2% |
| LMArena Expert | 1467 | 1036 |
| SimpleQA Verified | 49.3% | — |
| ARC (AI2) Challenge | — | 78.6% |
| BoolQ | — | 87.4% |
| MMLU | — | 62.5% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |
Multimodal Not comparable
Grok 4.6: 43.6 (#23), Mistral 7B: —
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |
Multilingual Grok 4.6 leads
Grok 4.6: 53.0 (#74), Mistral 7B: 25.8 (#283)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| LMArena Non-English | 1420 | 1012 |
| LMArena Chinese | 1480 | 1009 |
| LMArena French | 1461 | 1037 |
| LMArena German | 1431 | 987 |
| LMArena Japanese | 1376 | 878 |
| LMArena Russian | 1422 | 1018 |
| LMArena Spanish | 1404 | 1026 |
| LMArena Korean | 1397 | — |
Instruction Following Grok 4.6 leads
Grok 4.6: 75.4 (#63), Mistral 7B: 54.2 (#280)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | 1431 | 1060 |
Long Context Grok 4.6 leads
Grok 4.6: 44.5 (#66), Mistral 7B: 32.2 (#271)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| LMArena Longer Query | 1454 | 1060 |
Writing & Preference Grok 4.6 leads
Grok 4.6: 62.3 (#80), Mistral 7B: 30.7 (#286)
| Benchmark | Grok 4.6 | Mistral 7B |
|---|---|---|
| LMArena Text | 1428 | 1090 |
| LMArena Creative Writing | 1428 | 1068 |
| LMArena Multi-Turn | 1425 | 1062 |
Frequently asked questions
Is Grok 4.6 better than Mistral 7B?
Grok 4.6 is the stronger model overall, scoring 56.9 to 23.0 on the Noometry Index. Mistral 7B costs 12× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Which is cheaper, Grok 4.6 or Mistral 7B?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; Grok 4.6 lists at $2 and $6.
Is Grok 4.6 or Mistral 7B better for coding?
Grok 4.6 scores higher on coding benchmarks: 58.5 versus 26.4 in the Noometry coding category.
Which has the bigger context window?
Grok 4.6 does, with 500K tokens against 8K.
How many benchmarks do Grok 4.6 and Mistral 7B share?
21 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Mistral 7B has 37.