Grok 4.7 vs Mistral Small 3.1 24B
Mistral Small 3.1 24B costs 10.8x less per output token than Grok 4.7 ($0.555 vs $6.00 per million). Updated October 21, 2026; 35 benchmarks have a result for both.
Grok 4.7 or Mistral Small 3.1 24B: which to pick
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Mistral Small 3.1 24B has none, so the two cannot be ranked on coding.
Pick Mistral Small 3.1 24B for output tokens 10.8x cheaper ($0.555 vs $6.00 per million).
- Shared results
- 35
- Grok 4.7 only
- 64
- Mistral Small 3.1 24B only
- 3
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Grok 4.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Grok 4.7 has a AA Intelligence Index result, 46.4.
Directional only
Web design
Design Arena: websites
No call
Only Grok 4.7 has a Design Arena: websites result, 1254.
Directional only
General
Vals Index
No call
Only Grok 4.7 has a Vals Index result, 58.6%.
Directional only
Long documents
Listed context window
Grok 4.7
Grok 4.7 takes 500K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.1 24B
Grok 4.7 $0.0050, Mistral Small 3.1 24B $0.0006 per turn.
List prices
At a glance
- Coding index
- Grok 4.7 66.7 from 5 benchmarks, Mistral Small 3.1 24B not benchmarked.
- Widest category
- Math, 26.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: Chinese: Grok 4.7 1449 against Mistral Small 3.1 24B 1253, 32.8 points apart on a 0 to 100 scale.
- Output price
- Grok 4.7 $6.00 against Mistral Small 3.1 24B $0.555 per million output tokens, 10.8x apart.
- Context window
- Grok 4.7 takes 500K tokens, Mistral Small 3.1 24B 128K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Grok 4.7 | Bars | Mistral Small 3.1 24B | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 22 | 0 | ||
| All shared boards | 35 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only Grok 4.7 measured |
| LMArena WebDev | 1637 | Not measured | Only Grok 4.7 measured |
| Terminal-Bench 4 (Vals AI) | 28.8% | Not measured | Only Grok 4.7 measured |
| Vibe Code Bench (Vals AI) | 86.2% | Not measured | Only Grok 4.7 measured |
| Code migration (Vals AI) | 44.8% | Not measured | Only Grok 4.7 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only Grok 4.7 measured |
| IOI (Vals AI) | 57.7% | Not measured | Only Grok 4.7 measured |
| Terminal-Bench 2.1 (Vals AI) | 73.4% | Not measured | Only Grok 4.7 measured |
| SWE-bench Multimodal (Vals AI) | 42.9% | Not measured | Only Grok 4.7 measured |
| CyberBench (Vals AI) | 69.5% | Not measured | Only Grok 4.7 measured |
| SciCode | 57.8% | Not measured | Only Grok 4.7 measured |
| FrontierCode | 47.6% | Not measured | Only Grok 4.7 measured |
| FrontierSWE | 29.5% | Not measured | Only Grok 4.7 measured |
| LMArena Text: coding | 1432 | 1309 | Grok 4.7 |
| LMArena Text: software and IT | 1421 | 1301 | Grok 4.7 |
| LMArena WebDev: React | 1663 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: HTML | 1627 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: from an image | 1586 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 46.4 | Not measured | Only Grok 4.7 measured |
| Epoch Capabilities Index | 154.4 | Not measured | Only Grok 4.7 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LiveBench research | 86.4% | Not measured | Only Grok 4.7 measured |
| LiveBench browser | 60.0% | Not measured | Only Grok 4.7 measured |
| LiveBench long agentic | 50.1% | Not measured | Only Grok 4.7 measured |
| SREBench (Vals AI) | 3.8% | Not measured | Only Grok 4.7 measured |
| Finance Agent (Vals AI) | 52.3% | Not measured | Only Grok 4.7 measured |
| Tax Agent Bench (Vals AI) | 34.2% | Not measured | Only Grok 4.7 measured |
| Legal Research Bench (Vals AI) | 47.1% | Not measured | Only Grok 4.7 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 18.3% | Not measured | Only Grok 4.7 measured |
| Excel Modeling Benchmark (Vals AI) | 67.0% | Not measured | Only Grok 4.7 measured |
| BioMysteryBench (Vals AI) | 69.3% | Not measured | Only Grok 4.7 measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only Grok 4.7 measured |
| Vals Science Index | 34.8% | Not measured | Only Grok 4.7 measured |
| Robo-bench (Vals AI) | 0.2% | Not measured | Only Grok 4.7 measured |
| APEX-Agents | 54.6% | Not measured | Only Grok 4.7 measured |
| Vending-Bench 2 | $10,537 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LiveBench reasoning | 82.7% | Not measured | Only Grok 4.7 measured |
| MysteryMechanism (Vals AI) | 25.2% | Not measured | Only Grok 4.7 measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.1% | Not measured | Only Grok 4.7 measured |
| GPQA Diamond (Epoch AI run) | 92.7% | Not measured | Only Grok 4.7 measured |
| ARC-AGI | 90.2% | Not measured | Only Grok 4.7 measured |
| ARC-AGI-2 | 61.4% | Not measured | Only Grok 4.7 measured |
| Chess puzzles | 41.0% | Not measured | Only Grok 4.7 measured |
| Mystery game puzzles | 29.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: hard prompts | 1415 | 1278 | Grok 4.7 |
| LMArena Text: expert | 1439 | 1257 | Grok 4.7 |
| LMArena Text: hard prompts in English | 1427 | 1290 | Grok 4.7 |
| LMArena Vision: diagrams | 1254 | 1119 | Grok 4.7 |
| LMArena Vision: homework | 1309 | 1158 | Grok 4.7 |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.1% | Not measured | Only Grok 4.7 measured |
| FrontierMath, tiers 1 to 3 | 53.0% | Not measured | Only Grok 4.7 measured |
| FrontierMath, tier 4 | 17.1% | Not measured | Only Grok 4.7 measured |
| ProofBench | 26.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: math | 1414 | 1261 | Grok 4.7 |
| LMArena Text: mathematical work | 1435 | 1271 | Grok 4.7 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 84.4% | Not measured | Only Grok 4.7 measured |
| MedCode (Vals AI) | 49.5% | Not measured | Only Grok 4.7 measured |
| SimpleQA Verified | 56.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: science | 1419 | 1265 | Grok 4.7 |
| LMArena Text: medicine and healthcare | 1395 | 1267 | Grok 4.7 |
| LMArena Text: legal and government | 1423 | 1271 | Grok 4.7 |
| LMArena Text: business and finance | 1389 | 1257 | Grok 4.7 |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Design Arena: websites | 1254 | Not measured | Only Grok 4.7 measured |
| Design Arena: UI components | 1275 | Not measured | Only Grok 4.7 measured |
| Design Arena: game dev | 1313 | Not measured | Only Grok 4.7 measured |
| Design Arena: data viz | 1235 | Not measured | Only Grok 4.7 measured |
| Design Arena: 3D | 1270 | Not measured | Only Grok 4.7 measured |
| Design Arena: all code categories | 1271 | Not measured | Only Grok 4.7 measured |
| LiveBench design | 78.0% | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index220
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Vals Index | 58.6% | Not measured | Only Grok 4.7 measured |
| LiveBench data analysis | 76.9% | Not measured | Only Grok 4.7 measured |
| Public Benefits Bench (Vals AI) | 65.6% | Not measured | Only Grok 4.7 measured |
| SAGE (Vals AI) | 40.8% | Not measured | Only Grok 4.7 measured |
| MedScribe (Vals AI) | 89.4% | Not measured | Only Grok 4.7 measured |
| Long context reasoning (AA-LCR) | 80.0% | Not measured | Only Grok 4.7 measured |
| DTBench | 96.0% | Not measured | Only Grok 4.7 measured |
| LMCA | 49.4% | Not measured | Only Grok 4.7 measured |
| Furniture assembly | 20.8% | Not measured | Only Grok 4.7 measured |
| LMArena Text | 1399 | 1277 | Grok 4.7 |
| LMArena Text: instruction following | 1406 | 1263 | Grok 4.7 |
| LMArena Text: creative writing | 1381 | 1252 | Grok 4.7 |
| LMArena Vision | 1231 | 1136 | Grok 4.7 |
| LMArena Text: English | 1411 | 1295 | Grok 4.7 |
| LMArena Text: non-English | 1386 | 1255 | Grok 4.7 |
| LMArena Text: Chinese | 1449 | 1253 | Grok 4.7 |
| LMArena Text: German | 1366 | 1266 | Grok 4.7 |
| LMArena Text: Japanese | 1359 | 1208 | Grok 4.7 |
| LMArena Text: Korean | 1383 | 1207 | Grok 4.7 |
| LMArena Text: French | 1431 | 1273 | Grok 4.7 |
| LMArena Text: Spanish | 1406 | 1284 | Grok 4.7 |
| LMArena Text: Russian | 1399 | 1263 | Grok 4.7 |
| LMArena Text: Polish | 1420 | 1242 | Grok 4.7 |
| LMArena Text: multi-turn | 1394 | 1270 | Grok 4.7 |
| LMArena Text: longer queries | 1416 | 1299 | Grok 4.7 |
| LMArena Text: writing and language | 1394 | 1268 | Grok 4.7 |
| LMArena Text: entertainment and media | 1376 | 1250 | Grok 4.7 |
| LMArena Vision: English | 1229 | 1157 | Grok 4.7 |
| LMArena Vision: Chinese | 1250 | 1155 | Grok 4.7 |
| LMArena Vision: reading text | 1241 | 1132 | Grok 4.7 |
| LMArena Vision: humor | Not measured | 1142 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: captioning | Not measured | 1153 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: recognizing things | Not measured | 1155 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: creative writing | 1217 | 1123 | Grok 4.7 |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.7 | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Small 3.1 24B costs less
Repository review
50K input + 3K output tokens
Mistral Small 3.1 24B costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3.1 24B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | SpaceXAI Grok 4.7 | Mistral Small 3.1 24B |
|---|---|---|
| Maker | xAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | September 21, 2026 | March 17, 2025 |
| Context window | 500K | 128K |
| Input $/Mtok | $2.00 | $0.351 |
| Output $/Mtok | $6.00 | $0.555 |
| Coding index | 66.7 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.7 better than Mistral Small 3.1 24B for coding?
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Mistral Small 3.1 24B has none, so the two cannot be ranked on coding. Pick Mistral Small 3.1 24B for output tokens 10.8x cheaper ($0.555 vs $6.00 per million).
Which is cheaper, Grok 4.7 or Mistral Small 3.1 24B?
Grok 4.7 costs $2.00 per million input tokens and $6.00 per million output tokens; Mistral Small 3.1 24B costs $0.351 and $0.555. Cost per solved task is known for neither of them.
Which has the bigger context window, Grok 4.7 or Mistral Small 3.1 24B?
Grok 4.7, with 500K tokens against 128K.
How many benchmarks is the Grok 4.7 vs Mistral Small 3.1 24B comparison based on?
35 benchmarks have a result for both models as of October 21, 2026. Grok 4.7's coding index rests on 5 independent benchmarks and Mistral Small 3.1 24B's on 0. Where only one model has a result, the page says so instead of naming a winner.