Grok 4.7 vs Kimi K3
Grok 4.7 leads Kimi K3 on coding, 66.7 to 62.3 on the Vibe Coding Index, and Grok 4.7 costs 2.5x less per output token ($6.00 vs $15.00 per million). Updated October 22, 2026; 88 benchmarks have a result for both.
Grok 4.7 or Kimi K3: which to pick
Pick Grok 4.7 for coding: it scores 66.7 on the Vibe Coding Index against 62.3 for Kimi K3, though on 5 benchmarks against 6.
Pick Kimi K3 for a larger context window (1.05M against 500K tokens) and work measured by LMArena WebDev or ProgramBench (Vals AI), where it leads.
- Shared results
- 88
- Grok 4.7 only
- 11
- Kimi K3 only
- 29
- Like-for-like categories
- 8 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
Grok 4.7
Grok 4.7 scores 66.7 against 62.3.
5 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
Grok 4.7
Grok 4.7 leads, 46.4 against 43.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Kimi K3 has a AA Agentic Index result, 50.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Kimi K3 has a GPQA Diamond result, 92.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K3 has a MMLU Pro result, 88.0%.
Directional only
Web design
Design Arena: websites
Kimi K3
Kimi K3 leads, 1334 against 1255.
Same board, both measured
General
Vals Index
Grok 4.7
Grok 4.7 leads, 58.6% against 53.0%.
Same board, both measured
Long documents
Listed context window
Kimi K3
Kimi K3 takes 1.05M tokens against 500K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Grok 4.7
Grok 4.7 $0.0050, Kimi K3 $0.011 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K3 has the number, $0.81.
Directional only
At a glance
- Coding index
- Grok 4.7 66.7 from 5 benchmarks, Kimi K3 62.3 from 6 benchmarks.
- Widest category
- Math, 21.4 points apart on average over 6 shared benchmarks.
- Widest single gap
- ProofBench: Grok 4.7 26.0% against Kimi K3 87.0%, 61.0 points apart on a 0 to 100 scale.
- Output price
- Grok 4.7 $6.00 against Kimi K3 $15.00 per million output tokens, 2.5x apart.
- Context window
- Grok 4.7 takes 500K tokens, Kimi K3 1.05M.
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 | Kimi K3 | Ties |
|---|---|---|---|---|
| Coding | 8 | 10 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 10 | 2 | ||
| Reasoning | 3 | 7 | ||
| Math | 1 | 5 | ||
| Knowledge | 2 | 5 | ||
| Web design | 1 | 6 | ||
| General | 3 | 23 | ||
| All shared boards | 29 | 59 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index810
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | 59.3% | Grok 4.7 |
| LMArena WebDev | 1637 | 1655 | Kimi K3 |
| AA Coding Index | Not measured | 76.2 | Only Kimi K3 measured |
| LiveCodeBench (Vals AI) | Not measured | 87.2% | Only Kimi K3 measured |
| SWE-bench Verified (Vals AI) | Not measured | 93.4% | Only Kimi K3 measured |
| Terminal-Bench 4 (Vals AI) | 28.8% | 17.2% | Grok 4.7 |
| Vibe Code Bench (Vals AI) | 86.2% | 85.0% | Grok 4.7 |
| Code migration (Vals AI) | 44.8% | 16.1% | Grok 4.7 |
| ProgramBench (Vals AI) | 0.5% | 2.0% | Kimi K3 |
| IOI (Vals AI) | 57.7% | 48.9% | Grok 4.7 |
| Terminal-Bench 2.1 (Vals AI) | 73.4% | 80.9% | Kimi K3 |
| SWE-bench Multimodal (Vals AI) | 42.9% | 44.2% | Kimi K3 |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 18.2% | Only Kimi K3 measured |
| CyberBench (Vals AI) | 69.5% | 75.2% | Kimi K3 |
| SciCode | 57.8% | 59.5% | Kimi K3 |
| FrontierCode | 47.6% | 44.2% | Grok 4.7 |
| FrontierSWE | 29.5% | 25.9% | Grok 4.7 |
| WeirdML | Not measured | 82.6% | Only Kimi K3 measured |
| ALE-Bench | Not measured | 1524.5 | Only Kimi K3 measured |
| LMArena Text: coding | 1432 | 1508 | Kimi K3 |
| LMArena Text: software and IT | 1421 | 1499 | Kimi K3 |
| LMArena WebDev: React | 1663 | 1670 | Kimi K3 |
| LMArena WebDev: HTML | 1627 | 1644 | Kimi K3 |
| LMArena WebDev: from an image | 1586 | 1579 | Grok 4.7 |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 46.4 | 43.6 | Grok 4.7 |
| Epoch Capabilities Index | 154.4 | 157.9 | Kimi K3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index102
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.0 | Only Kimi K3 measured |
| Design Arena: agents building web apps | Not measured | 1295 | Only Kimi K3 measured |
| Design Arena: agents building full-stack apps | Not measured | 1315 | Only Kimi K3 measured |
| Design Arena: agents building mobile apps | Not measured | 1269 | Only Kimi K3 measured |
| Design Arena: agents building Android apps | Not measured | 1253 | Only Kimi K3 measured |
| Design Arena: agents building Godot games | Not measured | 1223 | Only Kimi K3 measured |
| Design Arena: agents building games | Not measured | 1252 | Only Kimi K3 measured |
| Design Arena: HTML slides | Not measured | 1206 | Only Kimi K3 measured |
| Design Arena: PowerPoint slides | Not measured | 1247 | Only Kimi K3 measured |
| Design Arena: spreadsheets | Not measured | 1070 | Only Kimi K3 measured |
| LiveBench research | 86.4% | 79.0% | Grok 4.7 |
| LiveBench browser | 60.0% | 16.0% | Grok 4.7 |
| LiveBench long agentic | 50.1% | 42.8% | Grok 4.7 |
| SREBench (Vals AI) | 3.8% | Not measured | Only Grok 4.7 measured |
| Finance Agent (Vals AI) | 52.3% | 53.1% | Kimi K3 |
| Tax Agent Bench (Vals AI) | 34.2% | 33.4% | Grok 4.7 |
| Legal Research Bench (Vals AI) | 47.1% | 46.1% | Grok 4.7 |
| Harvey's Legal Agent Benchmark (Vals AI) | 18.3% | 12.9% | Grok 4.7 |
| Excel Modeling Benchmark (Vals AI) | 67.0% | 66.7% | Grok 4.7 |
| BioMysteryBench (Vals AI) | 69.3% | 72.6% | Kimi K3 |
| Terminal-Bench-Science (Vals AI) | 10.0% | 1.4% | Grok 4.7 |
| Vals Science Index | 34.8% | Not measured | Only Grok 4.7 measured |
| Time Horizon Index (Vals AI) | Not measured | 10.5% | Only Kimi K3 measured |
| Robo-bench (Vals AI) | 0.2% | Not measured | Only Grok 4.7 measured |
| APEX-Agents | 54.6% | 47.8% | Grok 4.7 |
| PostTrainBench | Not measured | 32.0% | Only Kimi K3 measured |
| Vending-Bench 2 | $10,537 | $5,165 | Grok 4.7 |
| Neither model has a result on the other 14 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index37
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 92.9% | Only Kimi K3 measured |
| LiveBench reasoning | 82.7% | 90.7% | Kimi K3 |
| MysteryMechanism (Vals AI) | 25.2% | Not measured | Only Grok 4.7 measured |
| MMMU Pro (Vals AI) | Not measured | 88.2% | Only Kimi K3 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 93.5% | Only Kimi K3 measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.1% | 46.9% | Kimi K3 |
| GPQA Diamond (Epoch AI run) | 92.7% | 93.1% | Kimi K3 |
| ARC-AGI | 90.2% | 94.5% | Kimi K3 |
| ARC-AGI-2 | 61.4% | 60.4% | Grok 4.7 |
| SimpleBench | Not measured | 60.7% | Only Kimi K3 measured |
| Chess puzzles | 41.0% | 37.0% | Grok 4.7 |
| Mystery game puzzles | 29.0% | 26.0% | Grok 4.7 |
| LMArena Text: hard prompts | 1415 | 1495 | Kimi K3 |
| LMArena Text: expert | 1439 | 1520 | Kimi K3 |
| LMArena Text: hard prompts in English | 1427 | 1496 | Kimi K3 |
| LMArena Vision: diagrams | 1254 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: homework | 1309 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.1% | 97.2% | Grok 4.7 |
| FrontierMath, tiers 1 to 3 | 53.0% | 72.2% | Kimi K3 |
| FrontierMath, tier 4 | 17.1% | 39.0% | Kimi K3 |
| ProofBench | 26.0% | 87.0% | Kimi K3 |
| LMArena Text: math | 1414 | 1494 | Kimi K3 |
| LMArena Text: mathematical work | 1435 | 1505 | Kimi K3 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 88.0% | Only Kimi K3 measured |
| LegalBench (Vals AI) | 84.4% | 86.2% | Kimi K3 |
| CorpFin (Vals AI) | Not measured | 71.6% | Only Kimi K3 measured |
| TaxEval (Vals AI) | Not measured | 75.7% | Only Kimi K3 measured |
| MortgageTax (Vals AI) | Not measured | 66.3% | Only Kimi K3 measured |
| MedCode (Vals AI) | 49.5% | 49.4% | Grok 4.7 |
| SimpleQA Verified | 56.0% | 50.6% | Grok 4.7 |
| LMArena Text: science | 1419 | 1508 | Kimi K3 |
| LMArena Text: medicine and healthcare | 1395 | 1489 | Kimi K3 |
| LMArena Text: legal and government | 1423 | 1503 | Kimi K3 |
| LMArena Text: business and finance | 1389 | 1470 | Kimi K3 |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1255 | 1334 | Kimi K3 |
| Design Arena: UI components | 1275 | 1341 | Kimi K3 |
| Design Arena: game dev | 1314 | 1358 | Kimi K3 |
| Design Arena: data viz | 1238 | 1351 | Kimi K3 |
| Design Arena: 3D | 1274 | 1387 | Kimi K3 |
| Design Arena: all code categories | 1273 | 1360 | Kimi K3 |
| Design Arena: SVG | Not measured | 1302 | Only Kimi K3 measured |
| LiveBench design | 78.0% | 77.2% | Grok 4.7 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index323
| Benchmark | Grok 4.7 | Kimi K3 | Leader |
|---|---|---|---|
| Vals Index | 58.6% | 53.0% | Grok 4.7 |
| LiveBench data analysis | 76.9% | 78.7% | Kimi K3 |
| Public Benefits Bench (Vals AI) | 65.6% | 68.2% | Kimi K3 |
| SAGE (Vals AI) | 40.8% | 52.8% | Kimi K3 |
| MedScribe (Vals AI) | 89.4% | 88.0% | Grok 4.7 |
| Vals Multimodal Index | Not measured | 73.4% | Only Kimi K3 measured |
| Long context reasoning (AA-LCR) | 80.0% | 88.7% | Kimi K3 |
| DTBench | 96.0% | 91.2% | Grok 4.7 |
| LMCA | 49.4% | 52.7% | Kimi K3 |
| Surface Evolver Bench | Not measured | 95.0% | Only Kimi K3 measured |
| Furniture assembly | 20.8% | 34.2% | Kimi K3 |
| LMArena Text | 1399 | 1476 | Kimi K3 |
| LMArena Text: instruction following | 1406 | 1485 | Kimi K3 |
| LMArena Text: creative writing | 1381 | 1457 | Kimi K3 |
| LMArena Vision | 1231 | Not measured | Only Grok 4.7 measured |
| LMArena Text: English | 1411 | 1481 | Kimi K3 |
| LMArena Text: non-English | 1386 | 1466 | Kimi K3 |
| LMArena Text: Chinese | 1449 | 1529 | Kimi K3 |
| LMArena Text: German | 1366 | 1490 | Kimi K3 |
| LMArena Text: Japanese | 1359 | 1494 | Kimi K3 |
| LMArena Text: Korean | 1383 | 1460 | Kimi K3 |
| LMArena Text: French | 1431 | 1492 | Kimi K3 |
| LMArena Text: Spanish | 1406 | 1472 | Kimi K3 |
| LMArena Text: Russian | 1399 | 1485 | Kimi K3 |
| LMArena Text: Polish | 1420 | 1458 | Kimi K3 |
| LMArena Text: multi-turn | 1394 | 1489 | Kimi K3 |
| LMArena Text: longer queries | 1416 | 1494 | Kimi K3 |
| LMArena Text: writing and language | 1394 | 1471 | Kimi K3 |
| LMArena Text: entertainment and media | 1376 | 1453 | Kimi K3 |
| LMArena Vision: English | 1229 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: Chinese | 1250 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: reading text | 1241 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: creative writing | 1217 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.7 | Kimi K3 | 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
Grok 4.7 costs less
Repository review
50K input + 3K output tokens
Grok 4.7 costs less
Agent loop
200K input + 10K output tokens
Grok 4.7 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 | MoonshotAI Kimi K3 |
|---|---|---|
| Maker | xAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | September 21, 2026 | July 16, 2026 |
| Context window | 500K | 1.05M |
| Input $/Mtok | $2.00 | $3.00 |
| Output $/Mtok | $6.00 | $15.00 |
| Coding index | 66.7 | 62.3 |
| Independent measurements behind it | 5 | 6 |
| Cost per solved task | Not computable | $0.81 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.7 better than Kimi K3 for coding?
Pick Grok 4.7 for coding: it scores 66.7 on the Vibe Coding Index against 62.3 for Kimi K3, though on 5 benchmarks against 6. Pick Kimi K3 for a larger context window (1.05M against 500K tokens) and work measured by LMArena WebDev or ProgramBench (Vals AI), where it leads.
Which is cheaper, Grok 4.7 or Kimi K3?
Grok 4.7 costs $2.00 per million input tokens and $6.00 per million output tokens; Kimi K3 costs $3.00 and $15.00. Cost per solved task is known for Kimi K3 only.
Which has the bigger context window, Grok 4.7 or Kimi K3?
Kimi K3, with 1.05M tokens against 500K.
How many benchmarks is the Grok 4.7 vs Kimi K3 comparison based on?
88 benchmarks have a result for both models as of October 22, 2026. Grok 4.7's coding index rests on 5 independent benchmarks and Kimi K3's on 6. Where only one model has a result, the page says so instead of naming a winner.