GLM 5 vs Kimi K3
Updated October 21, 2026. 64 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Kimi K3 for coding: it scores 61.8 on the Vibe Coding Index against 59.7 for GLM 5.
Pick GLM 5 when output tokens cost 3.7x less, or when a solved task costs $0.63 against $0.81.
- Shared results
- 64
- GLM 5 only
- 11
- Kimi K3 only
- 53
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Kimi K3
Kimi K3 scores 61.8 against 59.7.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Kimi K3
Kimi K3 leads, 43.6 against 27.9.
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
Kimi K3
Kimi K3 leads, 92.9% against 83.3%.
Same board, both measured
Math
AIME
No call
Only GLM 5 has a AIME result, 91.7%.
Directional only
Knowledge
MMLU Pro
Kimi K3
Kimi K3 leads, 88.0% against 86.0%.
Same board, both measured
Web design
Design Arena: websites
Kimi K3
Kimi K3 leads, 1336 against 1247.
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
GLM 5 $0.0026, Kimi K3 $0.0062 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5
GLM 5 $0.63, Kimi K3 $0.81.
Published attempt cost and pass rate
At a glance
- Coding index
- GLM 5 59.7 from 2 benchmarks, Kimi K3 61.8 from 2 benchmarks.
- Widest category
- Coding, 24.9 points apart on average over 10 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GLM 5 23.4% against Kimi K3 85.0%, 61.6 points apart on a 0 to 100 scale.
- Output price
- GLM 5 $3.20 against Kimi K3 $11.936 per million output tokens, 3.7x apart.
- Context window
- GLM 5 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 | Bars | Kimi K3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 10 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 6 | ||
| Reasoning | 0 | 10 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 8 | ||
| Web design | 0 | 7 | ||
| General | 0 | 18 | ||
| All shared boards | 0 | 64 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index010
| Benchmark | GLM 5 | Kimi K3 | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GLM 5 measured |
| SWE-bench Multilingual | 69.7% | Not measured | Only GLM 5 measured |
| LiveBench coding | Not measured | 59.3% | Only Kimi K3 measured |
| LMArena WebDev | 1435 | 1655 | Kimi K3 |
| AA Coding Index | Not measured | 76.2 | Only Kimi K3 measured |
| LiveCodeBench (Vals AI) | 81.9% | 87.2% | Kimi K3 |
| SWE-bench Verified (Vals AI) | 71.4% | 93.4% | Kimi K3 |
| Terminal-Bench 4 (Vals AI) | Not measured | 17.2% | Only Kimi K3 measured |
| Vibe Code Bench (Vals AI) | 23.4% | 85.0% | Kimi K3 |
| Code migration (Vals AI) | Not measured | 16.1% | Only Kimi K3 measured |
| ProgramBench (Vals AI) | Not measured | 2.0% | Only Kimi K3 measured |
| IOI (Vals AI) | Not measured | 48.9% | Only Kimi K3 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 80.9% | Only Kimi K3 measured |
| 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 | Not measured | 59.5% | Only Kimi K3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 43.2% | Not measured | Only GLM 5 measured |
| Terminal-Bench | 52.4% | Not measured | Only GLM 5 measured |
| FrontierCode | Not measured | 44.2% | Only Kimi K3 measured |
| FrontierSWE | Not measured | 25.9% | Only Kimi K3 measured |
| WeirdML | 48.2% | 82.6% | Kimi K3 |
| ALE-Bench | 765.6 | 1524.5 | Kimi K3 |
| LMArena Text: coding | 1461 | 1508 | Kimi K3 |
| LMArena Text: software and IT | 1460 | 1499 | Kimi K3 |
| LMArena WebDev: React | 1424 | 1670 | Kimi K3 |
| LMArena WebDev: HTML | 1450 | 1644 | Kimi K3 |
| LMArena WebDev: from an image | Not measured | 1579 | Only Kimi K3 measured |
| Neither model has a result on the other 10 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 5 | Kimi K3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 27.9 | 43.6 | Kimi K3 |
| Epoch Capabilities Index | 145.8 | 157.9 | Kimi K3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GLM 5 | Kimi K3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.0 | Only Kimi K3 measured |
| Design Arena: agents building web apps | Not measured | 1296 | Only Kimi K3 measured |
| Design Arena: agents building full-stack apps | 1123 | 1315 | Kimi K3 |
| Design Arena: agents building mobile apps | 1136 | 1267 | Kimi K3 |
| Design Arena: agents building Android apps | 1152 | 1256 | Kimi K3 |
| Design Arena: agents building Godot games | 1144 | 1223 | Kimi K3 |
| Design Arena: agents building games | Not measured | 1252 | Only Kimi K3 measured |
| Design Arena: HTML slides | 1148 | 1256 | Kimi K3 |
| Design Arena: PowerPoint slides | Not measured | 1273 | Only Kimi K3 measured |
| Design Arena: spreadsheets | Not measured | 1058 | Only Kimi K3 measured |
| 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) | Not measured | 53.1% | Only Kimi K3 measured |
| Tax Agent Bench (Vals AI) | Not measured | 33.4% | Only Kimi K3 measured |
| Legal Research Bench (Vals AI) | Not measured | 46.1% | Only Kimi K3 measured |
| 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 | 98.2% | Not measured | Only GLM 5 measured |
| APEX-Agents | Not measured | 47.8% | Only Kimi K3 measured |
| PostTrainBench | Not measured | 32.0% | Only Kimi K3 measured |
| Vending-Bench 2 | $4,432 | $5,165 | Kimi K3 |
| Neither model has a result on the other 14 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | GLM 5 | Kimi K3 | Leader |
|---|---|---|---|
| GPQA Diamond | 83.3% | 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) | 82.0% | 93.5% | Kimi K3 |
| Humanity's Last Exam (Artificial Analysis run) | 29.3% | 46.9% | Kimi K3 |
| GPQA Diamond (Epoch AI run) | 87.8% | 93.1% | Kimi K3 |
| ARC-AGI | 44.7% | 94.5% | Kimi K3 |
| ARC-AGI-2 | 4.9% | 60.4% | Kimi K3 |
| SimpleBench | 53.2% | 60.7% | Kimi K3 |
| Chess puzzles | Not measured | 37.0% | Only Kimi K3 measured |
| Mystery game puzzles | Not measured | 26.0% | Only Kimi K3 measured |
| LMArena Text: hard prompts | 1452 | 1495 | Kimi K3 |
| LMArena Text: expert | 1454 | 1520 | Kimi K3 |
| LMArena Text: hard prompts in English | 1460 | 1496 | Kimi K3 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GLM 5 | Kimi K3 | Leader |
|---|---|---|---|
| AIME | 91.7% | Not measured | Only GLM 5 measured |
| OTIS Mock AIME | 80.0% | 97.2% | Kimi K3 |
| FrontierMath, tiers 1 to 3 | Not measured | 72.2% | Only Kimi K3 measured |
| FrontierMath, tier 4 | Not measured | 39.0% | Only Kimi K3 measured |
| ProofBench | Not measured | 87.0% | Only Kimi K3 measured |
| LMArena Text: math | 1440 | 1494 | Kimi K3 |
| LMArena Text: mathematical work | 1451 | 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 index08
| Benchmark | GLM 5 | Kimi K3 | Leader |
|---|---|---|---|
| MMLU Pro | 86.0% | 88.0% | Kimi K3 |
| LegalBench (Vals AI) | 84.1% | 86.2% | Kimi K3 |
| CaseLaw (Vals AI) | 52.5% | Not measured | Only GLM 5 measured |
| CorpFin (Vals AI) | 62.9% | 71.6% | Kimi K3 |
| TaxEval (Vals AI) | 70.0% | 75.7% | Kimi K3 |
| MortgageTax (Vals AI) | Not measured | 66.3% | Only Kimi K3 measured |
| MedQA (Vals AI) | 94.3% | Not measured | Only GLM 5 measured |
| MedCode (Vals AI) | Not measured | 49.4% | Only Kimi K3 measured |
| SimpleQA Verified | Not measured | 50.6% | Only Kimi K3 measured |
| LMArena Text: science | 1460 | 1508 | Kimi K3 |
| LMArena Text: medicine and healthcare | 1455 | 1489 | Kimi K3 |
| LMArena Text: legal and government | 1453 | 1503 | Kimi K3 |
| LMArena Text: business and finance | 1430 | 1470 | Kimi K3 |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | GLM 5 | Kimi K3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1247 | 1336 | Kimi K3 |
| Design Arena: UI components | 1230 | 1345 | Kimi K3 |
| Design Arena: game dev | 1234 | 1361 | Kimi K3 |
| Design Arena: data viz | 1228 | 1350 | Kimi K3 |
| Design Arena: 3D | 1229 | 1388 | Kimi K3 |
| Design Arena: all code categories | 1246 | 1361 | Kimi K3 |
| Design Arena: SVG | 1168 | 1301 | Kimi K3 |
| Design Arena: ASCII art | 1146 | Not measured | Only GLM 5 measured |
| LiveBench design | Not measured | 77.2% | Only Kimi K3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
| Benchmark | GLM 5 | 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) | Not measured | 68.2% | Only Kimi K3 measured |
| SAGE (Vals AI) | Not measured | 52.8% | Only Kimi K3 measured |
| MedScribe (Vals AI) | Not measured | 88.0% | Only Kimi K3 measured |
| Vals Multimodal Index | Not measured | 73.4% | Only Kimi K3 measured |
| IFBench | 72.3% | Not measured | Only GLM 5 measured |
| Long context reasoning (AA-LCR) | 75.7% | 88.7% | Kimi K3 |
| DTBench | Not measured | 91.2% | Only Kimi K3 measured |
| LMCA | Not measured | 52.7% | Only Kimi K3 measured |
| CL-bench | 18.7% | Not measured | Only GLM 5 measured |
| Surface Evolver Bench | Not measured | 95.0% | Only Kimi K3 measured |
| Furniture assembly | Not measured | 34.2% | Only Kimi K3 measured |
| LMArena Text | 1446 | 1476 | Kimi K3 |
| LMArena Text: instruction following | 1428 | 1485 | Kimi K3 |
| LMArena Text: creative writing | 1438 | 1457 | Kimi K3 |
| LMArena Text: English | 1458 | 1481 | Kimi K3 |
| LMArena Text: non-English | 1430 | 1466 | Kimi K3 |
| LMArena Text: Chinese | 1511 | 1529 | Kimi K3 |
| LMArena Text: German | 1447 | 1490 | Kimi K3 |
| LMArena Text: Japanese | 1416 | 1494 | Kimi K3 |
| LMArena Text: Korean | 1423 | 1460 | Kimi K3 |
| LMArena Text: French | 1456 | 1492 | Kimi K3 |
| LMArena Text: Spanish | 1454 | 1472 | Kimi K3 |
| LMArena Text: Russian | 1436 | 1485 | Kimi K3 |
| LMArena Text: Polish | 1434 | 1458 | Kimi K3 |
| LMArena Text: multi-turn | 1456 | 1489 | Kimi K3 |
| LMArena Text: longer queries | 1446 | 1494 | Kimi K3 |
| LMArena Text: writing and language | 1437 | 1471 | Kimi K3 |
| LMArena Text: entertainment and media | 1426 | 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 | 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 costs less
Repository review
50K input + 3K output tokens
Kimi K3 costs less
Agent loop
200K input + 10K output tokens
Kimi K3 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 | MoonshotAI Kimi K3 |
|---|---|---|
| Maker | Z.ai | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | February 11, 2026 | July 16, 2026 |
| Context window | 205K | 1.05M |
| Input $/Mtok | $1.00 | $0.239 |
| Output $/Mtok | $3.20 | $11.936 |
| Coding index | 59.7 | 61.8 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.63 | $0.81 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5 better than Kimi K3 for coding?
Pick Kimi K3 for coding: it scores 61.8 on the Vibe Coding Index against 59.7 for GLM 5. Pick GLM 5 when output tokens cost 3.7x less, or when a solved task costs $0.63 against $0.81.
Which is cheaper, GLM 5 or Kimi K3?
GLM 5 costs $1.00 per million input tokens and $3.20 per million output tokens; Kimi K3 costs $0.239 and $11.936. Per solved SWE-bench Verified task, GLM 5 costs $0.63 and Kimi K3 $0.81.
Which has the bigger context window, GLM 5 or Kimi K3?
Kimi K3, with 1.05M tokens against 205K.
How many benchmarks is the GLM 5 vs Kimi K3 comparison based on?
64 benchmarks have a result for both models as of October 21, 2026. GLM 5's coding index rests on 2 independent benchmarks and Kimi K3's on 2. Where only one model has a result, the page says so instead of naming a winner.