GLM 5.1 vs Kimi K3
Kimi K3 leads GLM 5.1 on coding, 62.3 to 49.2 on the Vibe Coding Index, and GLM 5.1 costs 3.4x less per output token ($4.40 vs $15.00 per million). Updated October 22, 2026; 82 benchmarks have a result for both.
GLM 5.1 or Kimi K3: which to pick
Pick Kimi K3 for coding: it scores 62.3 on the Vibe Coding Index against 49.2 for GLM 5.1.
Pick GLM 5.1 for output tokens 3.4x cheaper ($4.40 vs $15.00 per million) and a lower cost per solved task ($0.60 against $0.81).
- Shared results
- 82
- GLM 5.1 only
- 7
- Kimi K3 only
- 35
- 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
Kimi K3
Kimi K3 scores 62.3 against 49.2.
3 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
Kimi K3
Kimi K3 leads, 43.6 against 26.1.
Same board, both measured
Agentic work
AA Agentic Index
Kimi K3
Kimi K3 leads, 50.0 against 23.9.
Same board, both measured
Reasoning
GPQA Diamond
Kimi K3
Kimi K3 leads, 92.9% against 84.5%.
Same board, both measured
Math
AIME
No call
Only GLM 5.1 has a AIME result, 91.9%.
Directional only
Knowledge
MMLU Pro
Kimi K3
Kimi K3 leads, 88.0% against 86.9%.
Same board, both measured
Web design
Design Arena: websites
Kimi K3
Kimi K3 leads, 1334 against 1290.
Same board, both measured
General
Vals Index
No call
Only Kimi K3 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
Kimi K3
Kimi K3 takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.1
GLM 5.1 $0.0036, Kimi K3 $0.011 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.1
GLM 5.1 $0.60, Kimi K3 $0.81.
Published attempt cost and pass rate
At a glance
- Coding index
- GLM 5.1 49.2 from 3 benchmarks, Kimi K3 62.3 from 6 benchmarks.
- Widest category
- Math, 22.7 points apart on average over 5 shared benchmarks.
- Widest single gap
- ProofBench: GLM 5.1 22.2% against Kimi K3 87.0%, 64.8 points apart on a 0 to 100 scale.
- Output price
- GLM 5.1 $4.40 against Kimi K3 $15.00 per million output tokens, 3.4x apart.
- Context window
- GLM 5.1 takes 205K 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 | GLM 5.1 | Bars | Kimi K3 | Ties |
|---|---|---|---|---|
| Coding | 1 | 14 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 2 | 12 | ||
| Reasoning | 0 | 9 | ||
| Math | 0 | 5 | ||
| Knowledge | 0 | 10 | ||
| Web design | 1 | 6 | ||
| General | 0 | 20 | ||
| All shared boards | 4 | 78 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index114
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 59.3% | Only Kimi K3 measured |
| LMArena WebDev | 1508 | 1655 | Kimi K3 |
| AA Coding Index | 55.8 | 76.2 | Kimi K3 |
| LiveCodeBench (Vals AI) | 81.4% | 87.2% | Kimi K3 |
| SWE-bench Verified (Vals AI) | 76.4% | 93.4% | Kimi K3 |
| Terminal-Bench 4 (Vals AI) | Not measured | 17.2% | Only Kimi K3 measured |
| Vibe Code Bench (Vals AI) | 31.5% | 85.0% | Kimi K3 |
| Code migration (Vals AI) | 25.8% | 16.1% | GLM 5.1 |
| ProgramBench (Vals AI) | 0.0% | 2.0% | Kimi K3 |
| IOI (Vals AI) | Not measured | 48.9% | Only Kimi K3 measured |
| Terminal-Bench 2.1 (Vals AI) | 56.9% | 80.9% | Kimi K3 |
| SWE-bench Multimodal (Vals AI) | Not measured | 44.2% | Only Kimi K3 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 18.2% | Only Kimi K3 measured |
| CyberBench (Vals AI) | Not measured | 75.2% | Only Kimi K3 measured |
| SciCode | 44.8% | 59.5% | Kimi K3 |
| Terminal-Bench Hard (Artificial Analysis run) | 43.2% | Not measured | Only GLM 5.1 measured |
| FrontierCode | Not measured | 44.2% | Only Kimi K3 measured |
| FrontierSWE | Not measured | 25.9% | Only Kimi K3 measured |
| WeirdML | 57.1% | 82.6% | Kimi K3 |
| ALE-Bench | 887.1 | 1524.5 | Kimi K3 |
| LMArena Text: coding | 1485 | 1508 | Kimi K3 |
| LMArena Text: software and IT | 1484 | 1499 | Kimi K3 |
| LMArena WebDev: React | 1505 | 1670 | Kimi K3 |
| LMArena WebDev: HTML | 1508 | 1644 | Kimi K3 |
| LMArena WebDev: from an image | Not measured | 1579 | Only Kimi K3 measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.1 | 43.6 | Kimi K3 |
| Epoch Capabilities Index | 149.8 | 157.9 | Kimi K3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index212
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| AA Agentic Index | 23.9 | 50.0 | Kimi K3 |
| Design Arena: agents building web apps | 1175 | 1295 | Kimi K3 |
| Design Arena: agents building full-stack apps | 1167 | 1315 | Kimi K3 |
| Design Arena: agents building mobile apps | 1162 | 1269 | Kimi K3 |
| Design Arena: agents building Android apps | 1182 | 1253 | Kimi K3 |
| Design Arena: agents building Godot games | 1053 | 1223 | Kimi K3 |
| Design Arena: agents building games | 1164 | 1252 | Kimi K3 |
| Design Arena: HTML slides | 1120 | 1206 | Kimi K3 |
| Design Arena: PowerPoint slides | 1163 | 1247 | Kimi K3 |
| Design Arena: spreadsheets | 1315 | 1070 | GLM 5.1 |
| LiveBench research | Not measured | 79.0% | Only Kimi K3 measured |
| LiveBench browser | Not measured | 16.0% | Only Kimi K3 measured |
| LiveBench long agentic | Not measured | 42.8% | Only Kimi K3 measured |
| Finance Agent (Vals AI) | 44.8% | 53.1% | Kimi K3 |
| Tax Agent Bench (Vals AI) | Not measured | 33.4% | Only Kimi K3 measured |
| Legal Research Bench (Vals AI) | 27.9% | 46.1% | Kimi K3 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.9% | Only Kimi K3 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 66.7% | Only Kimi K3 measured |
| BioMysteryBench (Vals AI) | Not measured | 72.6% | Only Kimi K3 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 1.4% | Only Kimi K3 measured |
| Time Horizon Index (Vals AI) | Not measured | 10.5% | Only Kimi K3 measured |
| τ²-Bench Telecom | 97.7% | Not measured | Only GLM 5.1 measured |
| APEX-Agents | 40.9% | 47.8% | Kimi K3 |
| PostTrainBench | Not measured | 32.0% | Only Kimi K3 measured |
| Vending-Bench 2 | $5,634 | $5,165 | GLM 5.1 |
| Neither model has a result on the other 16 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| GPQA Diamond | 84.5% | 92.9% | Kimi K3 |
| LiveBench reasoning | Not measured | 90.7% | Only Kimi K3 measured |
| MMMU Pro (Vals AI) | Not measured | 88.2% | Only Kimi K3 measured |
| GPQA Diamond (Artificial Analysis run) | 86.8% | 93.5% | Kimi K3 |
| Humanity's Last Exam (Artificial Analysis run) | 30.1% | 46.9% | Kimi K3 |
| GPQA Diamond (Epoch AI run) | 89.9% | 93.1% | Kimi K3 |
| ARC-AGI | Not measured | 94.5% | Only Kimi K3 measured |
| ARC-AGI-2 | Not measured | 60.4% | Only Kimi K3 measured |
| SimpleBench | 55.1% | 60.7% | Kimi K3 |
| Chess puzzles | 20.0% | 37.0% | Kimi K3 |
| Mystery game puzzles | Not measured | 26.0% | Only Kimi K3 measured |
| LMArena Text: hard prompts | 1473 | 1495 | Kimi K3 |
| LMArena Text: expert | 1478 | 1520 | Kimi K3 |
| LMArena Text: hard prompts in English | 1482 | 1496 | Kimi K3 |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| AIME | 91.9% | Not measured | Only GLM 5.1 measured |
| OTIS Mock AIME | 93.3% | 97.2% | Kimi K3 |
| FrontierMath, tiers 1 to 3 | 36.8% | 72.2% | Kimi K3 |
| FrontierMath, tier 4 | Not measured | 39.0% | Only Kimi K3 measured |
| ProofBench | 22.2% | 87.0% | Kimi K3 |
| LMArena Text: math | 1473 | 1494 | Kimi K3 |
| LMArena Text: mathematical work | 1470 | 1505 | Kimi K3 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| MMLU Pro | 86.9% | 88.0% | Kimi K3 |
| LegalBench (Vals AI) | 84.4% | 86.2% | Kimi K3 |
| CaseLaw (Vals AI) | 51.5% | Not measured | Only GLM 5.1 measured |
| CorpFin (Vals AI) | 64.5% | 71.6% | Kimi K3 |
| TaxEval (Vals AI) | 71.2% | 75.7% | Kimi K3 |
| MortgageTax (Vals AI) | Not measured | 66.3% | Only Kimi K3 measured |
| MedCode (Vals AI) | 41.6% | 49.4% | Kimi K3 |
| SimpleQA Verified | 34.0% | 50.6% | Kimi K3 |
| LMArena Text: science | 1478 | 1508 | Kimi K3 |
| LMArena Text: medicine and healthcare | 1474 | 1489 | Kimi K3 |
| LMArena Text: legal and government | 1465 | 1503 | Kimi K3 |
| LMArena Text: business and finance | 1452 | 1470 | Kimi K3 |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1290 | 1334 | Kimi K3 |
| Design Arena: UI components | 1292 | 1341 | Kimi K3 |
| Design Arena: game dev | 1265 | 1358 | Kimi K3 |
| Design Arena: data viz | 1366 | 1351 | GLM 5.1 |
| Design Arena: 3D | 1336 | 1387 | Kimi K3 |
| Design Arena: all code categories | 1268 | 1360 | Kimi K3 |
| Design Arena: SVG | 1218 | 1302 | Kimi K3 |
| Design Arena: ASCII art | 1141 | Not measured | Only GLM 5.1 measured |
| LiveBench design | Not measured | 77.2% | Only Kimi K3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index020
| Benchmark | GLM 5.1 | Kimi K3 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.0% | Only Kimi K3 measured |
| LiveBench data analysis | Not measured | 78.7% | Only Kimi K3 measured |
| Public Benefits Bench (Vals AI) | 61.8% | 68.2% | Kimi K3 |
| SAGE (Vals AI) | Not measured | 52.8% | Only Kimi K3 measured |
| MedScribe (Vals AI) | 72.3% | 88.0% | Kimi K3 |
| Vals Multimodal Index | Not measured | 73.4% | Only Kimi K3 measured |
| IFBench | 76.3% | Not measured | Only GLM 5.1 measured |
| Long context reasoning (AA-LCR) | 73.7% | 88.7% | Kimi K3 |
| DTBench | Not measured | 91.2% | Only Kimi K3 measured |
| LMCA | Not measured | 52.7% | Only Kimi K3 measured |
| Surface Evolver Bench | Not measured | 95.0% | Only Kimi K3 measured |
| Furniture assembly | Not measured | 34.2% | Only Kimi K3 measured |
| ExploitBench | 18.1% | Not measured | Only GLM 5.1 measured |
| LMArena Text | 1463 | 1476 | Kimi K3 |
| LMArena Text: instruction following | 1453 | 1485 | Kimi K3 |
| LMArena Text: creative writing | 1453 | 1457 | Kimi K3 |
| LMArena Text: English | 1476 | 1481 | Kimi K3 |
| LMArena Text: non-English | 1448 | 1466 | Kimi K3 |
| LMArena Text: Chinese | 1515 | 1529 | Kimi K3 |
| LMArena Text: German | 1467 | 1490 | Kimi K3 |
| LMArena Text: Japanese | 1435 | 1494 | Kimi K3 |
| LMArena Text: Korean | 1424 | 1460 | Kimi K3 |
| LMArena Text: French | 1470 | 1492 | Kimi K3 |
| LMArena Text: Spanish | 1468 | 1472 | Kimi K3 |
| LMArena Text: Russian | 1454 | 1485 | Kimi K3 |
| LMArena Text: Polish | 1449 | 1458 | Kimi K3 |
| LMArena Text: multi-turn | 1473 | 1489 | Kimi K3 |
| LMArena Text: longer queries | 1467 | 1494 | Kimi K3 |
| LMArena Text: writing and language | 1454 | 1471 | Kimi K3 |
| LMArena Text: entertainment and media | 1442 | 1453 | Kimi K3 |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5.1 | 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
GLM 5.1 costs less
Repository review
50K input + 3K output tokens
GLM 5.1 costs less
Agent loop
200K input + 10K output tokens
GLM 5.1 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 | Z.ai GLM 5.1 | MoonshotAI Kimi K3 |
|---|---|---|
| Maker | Z.ai | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | April 7, 2026 | July 16, 2026 |
| Context window | 205K | 1.05M |
| Input $/Mtok | $1.40 | $3.00 |
| Output $/Mtok | $4.40 | $15.00 |
| Coding index | 49.2 | 62.3 |
| Independent measurements behind it | 3 | 6 |
| Cost per solved task | $0.60 | $0.81 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.1 better than Kimi K3 for coding?
Pick Kimi K3 for coding: it scores 62.3 on the Vibe Coding Index against 49.2 for GLM 5.1. Pick GLM 5.1 for output tokens 3.4x cheaper ($4.40 vs $15.00 per million) and a lower cost per solved task ($0.60 against $0.81).
Which is cheaper, GLM 5.1 or Kimi K3?
GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; Kimi K3 costs $3.00 and $15.00. Per solved SWE-bench Verified task, GLM 5.1 costs $0.60 and Kimi K3 $0.81.
Which has the bigger context window, GLM 5.1 or Kimi K3?
Kimi K3, with 1.05M tokens against 205K.
How many benchmarks is the GLM 5.1 vs Kimi K3 comparison based on?
82 benchmarks have a result for both models as of October 22, 2026. GLM 5.1's coding index rests on 3 independent benchmarks and Kimi K3's on 6. Where only one model has a result, the page says so instead of naming a winner.