Model comparison
Grok 4.7 vs Mistral Small
Grok 4.7 is the stronger model overall, scoring 46.6 to 33.1 on the Noometry Index. Mistral Small costs 11× less per token, which makes it the better buy when Grok 4.7's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
Mistral AISummary
- They share 14 benchmarks with published results for both. Grok 4.7 scores higher in 8 categories and Mistral Small in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Grok 4.7 leads 41.1 to 15.4.
- The biggest single-benchmark swing is SciCode: 57.4% for Grok 4.7 and 26.5% for Mistral Small.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $2 / $6 for Grok 4.7.
- Grok 4.7 accepts more context: 500K tokens versus 256K.
- Mistral Small has downloadable open weights; the other is API-only.
Side by side
| Grok 4.7 | Mistral Small | |
|---|---|---|
| Provider | xAI | Mistral AI |
| Noometry Index | 46.6 | 33.1 |
| Released | 2026-09-21 | 2024-02-26 |
| Weights | Proprietary | Open |
| Context window | 500K | 256K |
| Max output | 500K | 256K |
| Input $ / M tokens | $2 | $0.15 |
| Output $ / M tokens | $6 | $0.60 |
| Results tracked | 21 | 39 |
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Category by category
Coding Grok 4.7 leads
Grok 4.7: 55.0 (#23), Mistral Small: 33.5 (#242)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| SciCode | 57.4% | 26.5% |
| LMArena Coding | 1423 | 1363 |
| CursorBench | 46.3% | — |
| LMArena WebDev | 1636 | — |
| FrontierSWE | 29.5% | — |
| BigCodeBench Instruct | — | 36.1% |
| LiveBench Coding | — | 36.2% |
| BigCodeBench Complete | — | 46.6% |
| ALE-Bench | — | 497.62 |
Agentic & Tool Use Not comparable
Grok 4.7: —, Mistral Small: 27.9 (#87)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.1% |
Reasoning Grok 4.7 leads
Grok 4.7: 40.1 (#49), Mistral Small: 19.3 (#238)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| CritPt | 17.7% | 0% |
| LMArena Hard Prompts | 1409 | 1336 |
| Kagi LLM Benchmark | — | 37.8% |
| NYT Connections (extended) | 76.8% | — |
| LiveBench Reasoning | — | 44.8% |
| DTBench | — | 70.9% |
| LiveBench Data Analysis | — | 53.7% |
| LMCA | — | 20.6% |
| LiveBench | — | 44% |
Math Grok 4.7 leads
Grok 4.7: 41.1 (#73), Mistral Small: 15.4 (#287)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| LMArena Math | 1393 | 1341 |
| OTIS Mock AIME 2024-2025 | — | 5.8% |
| ProofBench | 34% | — |
| LiveBench Math | — | 39.9% |
| MATH Level 5 | — | 46.8% |
Knowledge Grok 4.7 leads
Grok 4.7: 38.7 (#130), Mistral Small: 30.9 (#214)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| LMArena Expert | 1413 | 1293 |
| GPQA Diamond | — | 47.5% |
| Vectara Hallucination Rate | — | 5.1% |
| MMLU | — | 68.7% |
Multimodal Mistral Small leads
Grok 4.7: 28.8 (#107), Mistral Small: 32.9 (#91)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| LMArena Vision | — | 1142 |
| Furniture Assembly | 20.8% | — |
Multilingual Grok 4.7 leads
Grok 4.7: 51.2 (#108), Mistral Small: 45.7 (#164)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| LMArena Non-English | 1392 | 1315 |
| LMArena Chinese | 1476 | 1342 |
| LMArena Russian | 1396 | 1324 |
| LMArena French | — | 1337 |
| LMArena German | — | 1341 |
| LMArena Japanese | — | 1275 |
| LMArena Korean | — | 1260 |
| LMArena Spanish | — | 1346 |
Instruction Following Grok 4.7 leads
Grok 4.7: 74.3 (#98), Mistral Small: 66.6 (#204)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1406 | 1310 |
| LiveBench Instruction Following | — | 63.7% |
Long Context Grok 4.7 leads
Grok 4.7: 43.2 (#97), Mistral Small: 40.4 (#151)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1416 | 1327 |
Writing & Preference Grok 4.7 leads
Grok 4.7: 70.1 (#23), Mistral Small: 52.6 (#165)
| Benchmark | Grok 4.7 | Mistral Small |
|---|---|---|
| LMArena Text | 1397 | 1338 |
| LMArena Creative Writing | 1391 | 1304 |
| LMArena Multi-Turn | 1389 | 1344 |
| EQ-Bench Creative Writing | 2007 | — |
| LiveBench Language | — | 30.5% |
Frequently asked questions
Is Grok 4.7 better than Mistral Small?
Grok 4.7 is the stronger model overall, scoring 46.6 to 33.1 on the Noometry Index. Mistral Small costs 11× less per token, which makes it the better buy when Grok 4.7's lead doesn't matter for your workload.
Which is cheaper, Grok 4.7 or Mistral Small?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Grok 4.7 lists at $2 and $6.
Is Grok 4.7 or Mistral Small better for coding?
Grok 4.7 scores higher on coding benchmarks: 55.0 versus 33.5 in the Noometry coding category.
Which has the bigger context window?
Grok 4.7 does, with 500K tokens against 256K.
How many benchmarks do Grok 4.7 and Mistral Small share?
14 benchmarks have published results for both models. Grok 4.7 has 21 scored results on Noometry and Mistral Small has 39.