Grok 4.5 vs Kimi K2.6
Grok 4.5 leads Kimi K2.6 on coding, 58.6 to 52.1 on the Vibe Coding Index, and Kimi K2.6 costs 1.5x less per output token ($4.00 vs $6.00 per million). Updated October 22, 2026; 99 benchmarks have a result for both.
Grok 4.5 or Kimi K2.6: which to pick
Pick Grok 4.5 for coding: it scores 58.6 on the Vibe Coding Index against 52.1 for Kimi K2.6.
Pick Kimi K2.6 for output tokens 1.5x cheaper ($4.00 vs $6.00 per million) and a lower cost per solved task ($0.35 against $0.62).
- Shared results
- 99
- Grok 4.5 only
- 24
- Kimi K2.6 only
- 10
- 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 4.5
Grok 4.5 scores 58.6 against 52.1.
6 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Grok 4.5
Grok 4.5 leads, 38.8 against 27.0.
Same board, both measured
Agentic work
AA Agentic Index
Grok 4.5
Grok 4.5 leads, 41.2 against 20.5.
Same board, both measured
Reasoning
GPQA Diamond
Grok 4.5
Grok 4.5 leads, 92.9% against 89.1%.
Same board, both measured
Knowledge
MMLU Pro
Grok 4.5
Grok 4.5 leads, 89.2% against 87.6%.
Same board, both measured
Web design
Design Arena: websites
Grok 4.5
Grok 4.5 leads, 1281 against 1268.
Same board, both measured
Long documents
Listed context window
Grok 4.5
Grok 4.5 takes 500K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.6
Grok 4.5 $0.0050, Kimi K2.6 $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.6
Grok 4.5 $0.62, Kimi K2.6 $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- Grok 4.5 58.6 from 6 benchmarks, Kimi K2.6 52.1 from 3 benchmarks.
- Widest category
- Agentic work, 11.7 points apart on average over 14 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Grok 4.5 69.0% against Kimi K2.6 37.9%, 31.1 points apart on a 0 to 100 scale.
- Output price
- Grok 4.5 $6.00 against Kimi K2.6 $4.00 per million output tokens, 1.5x apart.
- Context window
- Grok 4.5 takes 500K tokens, Kimi K2.6 262K.
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 4.5 | Bars | Kimi K2.6 | Ties |
|---|---|---|---|---|
| Coding | 12 | 3 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 11 | 3 | ||
| Reasoning | 6 | 5 | ||
| Math | 3 | 2 | 1 tie | |
| Knowledge | 6 | 5 | ||
| Web design | 7 | 1 | ||
| General | 14 | 17 | ||
| All shared boards | 61 | 36 | 2 ties |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index123
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| LiveBench coding | 94.3% | Not measured | Only Grok 4.5 measured |
| LMArena WebDev | 1553 | 1509 | Grok 4.5 |
| AA Coding Index | 72.4 | 61.8 | Grok 4.5 |
| LiveCodeBench (Vals AI) | 87.3% | 86.8% | Grok 4.5 |
| SWE-bench Verified (Vals AI) | 86.6% | 76.2% | Grok 4.5 |
| Terminal-Bench 4 (Vals AI) | 8.6% | Not measured | Only Grok 4.5 measured |
| Vibe Code Bench (Vals AI) | 69.0% | 37.9% | Grok 4.5 |
| Code migration (Vals AI) | 36.6% | 27.8% | Grok 4.5 |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | 40.6% | Not measured | Only Grok 4.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 67.8% | 53.6% | Grok 4.5 |
| SkillsBench (Vals AI) | 66.0% | Not measured | Only Grok 4.5 measured |
| CyberBench (Vals AI) | 71.0% | Not measured | Only Grok 4.5 measured |
| SciCode | 55.0% | 51.5% | Grok 4.5 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 43.9% | Only Kimi K2.6 measured |
| FrontierCode | 42.4% | Not measured | Only Grok 4.5 measured |
| WeirdML | 46.4% | 55.9% | Kimi K2.6 |
| ALE-Bench | 1309.3 | 1092.7 | Grok 4.5 |
| LMArena Text: coding | 1474 | 1489 | Kimi K2.6 |
| LMArena Text: software and IT | 1471 | 1484 | Kimi K2.6 |
| LMArena WebDev: React | 1556 | 1505 | Grok 4.5 |
| LMArena WebDev: HTML | 1567 | 1485 | Grok 4.5 |
| LMArena WebDev: from an image | 1562 | 1521 | Grok 4.5 |
| SciCode | 6.5% | Not measured | Only Grok 4.5 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.8 | 27.0 | Grok 4.5 |
| Epoch Capabilities Index | 154.1 | 150.9 | Grok 4.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index113
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| AA Agentic Index | 41.2 | 20.5 | Grok 4.5 |
| Design Arena: agents building web apps | 1218 | 1268 | Kimi K2.6 |
| Design Arena: agents building full-stack apps | 1249 | 1155 | Grok 4.5 |
| Design Arena: agents building mobile apps | 1220 | 1156 | Grok 4.5 |
| Design Arena: agents building Android apps | 1236 | 1161 | Grok 4.5 |
| Design Arena: agents building Godot games | 1229 | 1120 | Grok 4.5 |
| Design Arena: agents building games | 1236 | 1141 | Grok 4.5 |
| Design Arena: HTML slides | 1205 | 1135 | Grok 4.5 |
| Design Arena: PowerPoint slides | 1230 | 1103 | Grok 4.5 |
| Design Arena: spreadsheets | Not measured | 1276 | Only Kimi K2.6 measured |
| LiveBench research | 85.9% | Not measured | Only Grok 4.5 measured |
| LiveBench browser | 44.0% | Not measured | Only Grok 4.5 measured |
| LiveBench long agentic | 27.9% | Not measured | Only Grok 4.5 measured |
| SREBench (Vals AI) | 0.8% | Not measured | Only Grok 4.5 measured |
| Finance Agent (Vals AI) | 48.4% | 44.9% | Grok 4.5 |
| Tax Agent Bench (Vals AI) | 24.9% | 12.4% | Grok 4.5 |
| Legal Research Bench (Vals AI) | 38.0% | 15.9% | Grok 4.5 |
| Excel Modeling Benchmark (Vals AI) | 52.9% | 57.9% | Kimi K2.6 |
| Time Horizon Index (Vals AI) | 6.3% | Not measured | Only Grok 4.5 measured |
| τ²-Bench Telecom | Not measured | 95.9% | Only Kimi K2.6 measured |
| APEX-Agents | 56.2% | Not measured | Only Grok 4.5 measured |
| OSWorld 2.0 | Not measured | 4.6% | Only Kimi K2.6 measured |
| PostTrainBench | 23.4% | Not measured | Only Grok 4.5 measured |
| Vending-Bench 2 | $3,887 | $6,205 | Kimi K2.6 |
| LMArena Search | 1216 | Not measured | Only Grok 4.5 measured |
| Neither model has a result on the other 16 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index65
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| GPQA Diamond | 92.9% | 89.1% | Grok 4.5 |
| LiveBench reasoning | 87.2% | Not measured | Only Grok 4.5 measured |
| MMMU Pro (Vals AI) | 61.8% | 86.3% | Kimi K2.6 |
| GPQA Diamond (Artificial Analysis run) | 93.1% | 91.1% | Grok 4.5 |
| Humanity's Last Exam (Artificial Analysis run) | 42.7% | 37.5% | Grok 4.5 |
| GPQA Diamond (Epoch AI run) | 93.4% | 90.8% | Grok 4.5 |
| ARC-AGI | 87.2% | Not measured | Only Grok 4.5 measured |
| ARC-AGI-2 | 52.6% | Not measured | Only Grok 4.5 measured |
| SimpleBench | 70.0% | Not measured | Only Grok 4.5 measured |
| Chess puzzles | 35.0% | 20.0% | Grok 4.5 |
| Mystery game puzzles | Not measured | 18.0% | Only Kimi K2.6 measured |
| EBR-bench | Not measured | 2.4% | Only Kimi K2.6 measured |
| LMArena Text: hard prompts | 1462 | 1470 | Kimi K2.6 |
| LMArena Text: expert | 1465 | 1491 | Kimi K2.6 |
| LMArena Text: hard prompts in English | 1464 | 1471 | Kimi K2.6 |
| LMArena Vision: diagrams | 1304 | 1298 | Grok 4.5 |
| LMArena Vision: homework | 1295 | 1310 | Kimi K2.6 |
| Kagi LLM Benchmark | 83.5% | Not measured | Only Grok 4.5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 97.8% | 96.1% | Grok 4.5 |
| FrontierMath, tiers 1 to 3 | 57.2% | 57.2% | Tie |
| FrontierMath, tier 4 | 24.4% | 25.6% | Kimi K2.6 |
| ProofBench | 31.0% | 16.0% | Grok 4.5 |
| LMArena Text: math | 1460 | 1474 | Kimi K2.6 |
| LMArena Text: mathematical work | 1482 | 1480 | Grok 4.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index65
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| MMLU Pro | 89.2% | 87.6% | Grok 4.5 |
| LegalBench (Vals AI) | 86.0% | 84.7% | Grok 4.5 |
| CaseLaw (Vals AI) | Not measured | 61.2% | Only Kimi K2.6 measured |
| CorpFin (Vals AI) | 67.4% | 66.7% | Grok 4.5 |
| TaxEval (Vals AI) | 71.7% | 74.7% | Kimi K2.6 |
| MortgageTax (Vals AI) | 61.8% | 65.8% | Kimi K2.6 |
| MedCode (Vals AI) | 43.3% | 40.1% | Grok 4.5 |
| SimpleQA Verified | 48.3% | 34.9% | Grok 4.5 |
| LMArena Text: science | 1464 | 1468 | Kimi K2.6 |
| LMArena Text: medicine and healthcare | 1440 | 1457 | Kimi K2.6 |
| LMArena Text: legal and government | 1463 | 1462 | Grok 4.5 |
| LMArena Text: business and finance | 1441 | 1445 | Kimi K2.6 |
| FACTS Benchmark Suite | 50.2% | Not measured | Only Grok 4.5 measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| Design Arena: websites | 1281 | 1268 | Grok 4.5 |
| Design Arena: UI components | 1280 | 1263 | Grok 4.5 |
| Design Arena: game dev | 1264 | 1250 | Grok 4.5 |
| Design Arena: data viz | 1266 | 1249 | Grok 4.5 |
| Design Arena: 3D | 1257 | 1267 | Kimi K2.6 |
| Design Arena: all code categories | 1275 | 1271 | Grok 4.5 |
| Design Arena: SVG | 1215 | 1181 | Grok 4.5 |
| Design Arena: ASCII art | 1256 | 1165 | Grok 4.5 |
| LiveBench design | 78.1% | Not measured | Only Grok 4.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index1417
| Benchmark | Grok 4.5 | Kimi K2.6 | Leader |
|---|---|---|---|
| LiveBench data analysis | 73.0% | Not measured | Only Grok 4.5 measured |
| Public Benefits Bench (Vals AI) | Not measured | 56.6% | Only Kimi K2.6 measured |
| SAGE (Vals AI) | 35.0% | 50.2% | Kimi K2.6 |
| MedScribe (Vals AI) | 86.9% | 78.2% | Grok 4.5 |
| Vals Multimodal Index | 63.4% | 56.4% | Grok 4.5 |
| IFBench | Not measured | 76.0% | Only Kimi K2.6 measured |
| Long context reasoning (AA-LCR) | 79.3% | 81.0% | Kimi K2.6 |
| DTBench | 96.5% | 90.9% | Grok 4.5 |
| LMCA | 45.2% | 37.3% | Grok 4.5 |
| Surface Evolver Bench | 74.4% | Not measured | Only Grok 4.5 measured |
| Furniture assembly | 22.5% | 21.7% | Grok 4.5 |
| ExploitBench | Not measured | 18.4% | Only Kimi K2.6 measured |
| LMArena Text | 1448 | 1455 | Kimi K2.6 |
| LMArena Text: instruction following | 1445 | 1451 | Kimi K2.6 |
| LMArena Text: creative writing | 1442 | 1434 | Grok 4.5 |
| LMArena Vision | 1287 | 1282 | Grok 4.5 |
| LMArena Text: English | 1453 | 1460 | Kimi K2.6 |
| LMArena Text: non-English | 1440 | 1446 | Kimi K2.6 |
| LMArena Text: Chinese | 1495 | 1520 | Kimi K2.6 |
| LMArena Text: German | 1448 | 1451 | Kimi K2.6 |
| LMArena Text: Japanese | 1430 | 1443 | Kimi K2.6 |
| LMArena Text: Korean | 1406 | 1427 | Kimi K2.6 |
| LMArena Text: French | 1457 | 1471 | Kimi K2.6 |
| LMArena Text: Spanish | 1451 | 1464 | Kimi K2.6 |
| LMArena Text: Russian | 1449 | 1446 | Grok 4.5 |
| LMArena Text: Polish | 1432 | 1438 | Kimi K2.6 |
| LMArena Text: multi-turn | 1456 | 1453 | Grok 4.5 |
| LMArena Text: longer queries | 1462 | 1468 | Kimi K2.6 |
| LMArena Text: writing and language | 1445 | 1439 | Grok 4.5 |
| LMArena Text: entertainment and media | 1434 | 1428 | Grok 4.5 |
| LMArena Vision: English | 1285 | 1287 | Kimi K2.6 |
| LMArena Vision: Chinese | 1345 | 1346 | Kimi K2.6 |
| LMArena Vision: reading text | 1293 | 1291 | Grok 4.5 |
| LMArena Vision: humor | 1276 | 1280 | Kimi K2.6 |
| LMArena Vision: creative writing | 1293 | 1273 | Grok 4.5 |
| LMArena Document | 1452 | 1451 | Grok 4.5 |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.5 | Kimi K2.6 | 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
Kimi K2.6 costs less
Repository review
50K input + 3K output tokens
Kimi K2.6 costs less
Agent loop
200K input + 10K output tokens
Kimi K2.6 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 4.5 | MoonshotAI Kimi K2.6 |
|---|---|---|
| Maker | xAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | July 8, 2026 | April 20, 2026 |
| Context window | 500K | 262K |
| Input $/Mtok | $2.00 | $0.95 |
| Output $/Mtok | $6.00 | $4.00 |
| Coding index | 58.6 | 52.1 |
| Independent measurements behind it | 6 | 3 |
| Cost per solved task | $0.62 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.5 better than Kimi K2.6 for coding?
Pick Grok 4.5 for coding: it scores 58.6 on the Vibe Coding Index against 52.1 for Kimi K2.6. Pick Kimi K2.6 for output tokens 1.5x cheaper ($4.00 vs $6.00 per million) and a lower cost per solved task ($0.35 against $0.62).
Which is cheaper, Grok 4.5 or Kimi K2.6?
Grok 4.5 costs $2.00 per million input tokens and $6.00 per million output tokens; Kimi K2.6 costs $0.95 and $4.00. Per solved SWE-bench Verified task, Grok 4.5 costs $0.62 and Kimi K2.6 $0.35.
Which has the bigger context window, Grok 4.5 or Kimi K2.6?
Grok 4.5, with 500K tokens against 262K.
How many benchmarks is the Grok 4.5 vs Kimi K2.6 comparison based on?
99 benchmarks have a result for both models as of October 22, 2026. Grok 4.5's coding index rests on 6 independent benchmarks and Kimi K2.6's on 3. Where only one model has a result, the page says so instead of naming a winner.