GLM 5.3 vs Kimi K3
GLM 5.3 leads Kimi K3 on coding, 70.6 to 62.3 on the Vibe Coding Index, and GLM 5.3 costs 3.4x less per output token ($4.40 vs $15.00 per million). Updated October 21, 2026; 96 benchmarks have a result for both.
GLM 5.3 or Kimi K3: which to pick
Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 62.3 for Kimi K3.
Pick Kimi K3 for work measured by LMArena WebDev or AA Coding Index, where it leads.
- Shared results
- 96
- GLM 5.3 only
- 4
- Kimi K3 only
- 21
- 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
GLM 5.3
GLM 5.3 scores 70.6 against 62.3.
6 benchmarks behind each score
Intelligence
AA Intelligence Index
GLM 5.3
GLM 5.3 leads, 44.8 against 43.6.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3
GLM 5.3 leads, 53.1 against 50.0.
Same board, both measured
Reasoning
GPQA Diamond
Kimi K3
Kimi K3 leads, 92.9% against 88.1%.
Same board, both measured
Knowledge
MMLU Pro
Kimi K3
Kimi K3 leads, 88.0% against 86.8%.
Same board, both measured
Web design
Design Arena: websites
Kimi K3
Kimi K3 leads, 1335 against 1295.
Same board, both measured
General
Vals Index
GLM 5.3
GLM 5.3 leads, 59.7% against 53.0%.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3
GLM 5.3 $0.0036, Kimi K3 $0.011 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3
GLM 5.3 $0.36, Kimi K3 $0.81.
Published attempt cost and pass rate
At a glance
- Coding index
- GLM 5.3 70.6 from 6 benchmarks, Kimi K3 62.3 from 6 benchmarks.
- Widest category
- Math, 9.8 points apart on average over 6 shared benchmarks.
- Widest single gap
- ProofBench: GLM 5.3 49.0% against Kimi K3 87.0%, 38.0 points apart on a 0 to 100 scale.
- Output price
- GLM 5.3 $4.40 against Kimi K3 $15.00 per million output tokens, 3.4x apart.
- Context window
- Both take 1.05M tokens.
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 5.3 | Bars | Kimi K3 | Ties |
|---|---|---|---|---|
| Coding | 7 | 15 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 8 | 7 | ||
| Reasoning | 1 | 8 | 1 tie | |
| Math | 1 | 5 | ||
| Knowledge | 0 | 9 | ||
| Web design | 1 | 7 | ||
| General | 9 | 15 | ||
| All shared boards | 28 | 67 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index715
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| LiveBench coding | 82.8% | 59.3% | GLM 5.3 |
| LMArena WebDev | 1621 | 1655 | Kimi K3 |
| AA Coding Index | 74.8 | 76.2 | Kimi K3 |
| LiveCodeBench (Vals AI) | 80.5% | 87.2% | Kimi K3 |
| SWE-bench Verified (Vals AI) | 95.4% | 93.4% | GLM 5.3 |
| Terminal-Bench 4 (Vals AI) | 38.9% | 17.2% | GLM 5.3 |
| Vibe Code Bench (Vals AI) | 78.1% | 85.0% | Kimi K3 |
| Code migration (Vals AI) | 44.2% | 16.1% | GLM 5.3 |
| ProgramBench (Vals AI) | 1.5% | 2.0% | Kimi K3 |
| IOI (Vals AI) | 68.4% | 48.9% | GLM 5.3 |
| Terminal-Bench 2.1 (Vals AI) | 71.5% | 80.9% | Kimi K3 |
| SWE-bench Multimodal (Vals AI) | Not measured | 44.2% | Only Kimi K3 measured |
| Vibe Code Bench 1-100 (Vals AI) | 20.0% | 18.2% | GLM 5.3 |
| SkillsBench (Vals AI) | 47.5% | Not measured | Only GLM 5.3 measured |
| CyberBench (Vals AI) | 72.1% | 75.2% | Kimi K3 |
| SciCode | 59.0% | 59.5% | Kimi K3 |
| FrontierCode | 40.1% | 44.2% | Kimi K3 |
| FrontierSWE | 30.2% | 25.9% | GLM 5.3 |
| WeirdML | 75.4% | 82.6% | Kimi K3 |
| ALE-Bench | 1317.4 | 1524.5 | Kimi K3 |
| LMArena Text: coding | 1497 | 1508 | Kimi K3 |
| LMArena Text: software and IT | 1493 | 1499 | Kimi K3 |
| LMArena WebDev: React | 1641 | 1670 | Kimi K3 |
| LMArena WebDev: HTML | 1595 | 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 index11
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 44.8 | 43.6 | GLM 5.3 |
| Epoch Capabilities Index | 156.0 | 157.9 | Kimi K3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index87
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| AA Agentic Index | 53.1 | 50.0 | GLM 5.3 |
| 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 | 1194 | 1269 | Kimi K3 |
| Design Arena: agents building Android apps | Not measured | 1250 | 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 | 1189 | 1256 | Kimi K3 |
| Design Arena: PowerPoint slides | 1254 | 1273 | Kimi K3 |
| Design Arena: spreadsheets | Not measured | 1058 | Only Kimi K3 measured |
| LiveBench research | 73.2% | 79.0% | Kimi K3 |
| LiveBench browser | 0.0% | 16.0% | Kimi K3 |
| LiveBench long agentic | 35.9% | 42.8% | Kimi K3 |
| SREBench (Vals AI) | 9.2% | Not measured | Only GLM 5.3 measured |
| Finance Agent (Vals AI) | 55.8% | 53.1% | GLM 5.3 |
| Tax Agent Bench (Vals AI) | 39.7% | 33.4% | GLM 5.3 |
| Legal Research Bench (Vals AI) | 49.0% | 46.1% | GLM 5.3 |
| Harvey's Legal Agent Benchmark (Vals AI) | 14.6% | 12.9% | GLM 5.3 |
| Excel Modeling Benchmark (Vals AI) | 56.3% | 66.7% | Kimi K3 |
| BioMysteryBench (Vals AI) | Not measured | 72.6% | Only Kimi K3 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | 1.4% | GLM 5.3 |
| Time Horizon Index (Vals AI) | Not measured | 10.5% | Only Kimi K3 measured |
| APEX-Agents | 56.6% | 47.8% | GLM 5.3 |
| PostTrainBench | Not measured | 32.0% | Only Kimi K3 measured |
| Vending-Bench 2 | $8,164 | $5,165 | GLM 5.3 |
| Neither model has a result on the other 16 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index18
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| GPQA Diamond | 88.1% | 92.9% | Kimi K3 |
| LiveBench reasoning | 85.8% | 90.7% | Kimi K3 |
| MysteryMechanism (Vals AI) | 23.0% | Not measured | Only GLM 5.3 measured |
| MMMU Pro (Vals AI) | Not measured | 88.2% | Only Kimi K3 measured |
| GPQA Diamond (Artificial Analysis run) | 91.7% | 93.5% | Kimi K3 |
| Humanity's Last Exam (Artificial Analysis run) | 42.3% | 46.9% | Kimi K3 |
| GPQA Diamond (Epoch AI run) | 90.9% | 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 | Not measured | 60.7% | Only Kimi K3 measured |
| Chess puzzles | 37.0% | 37.0% | Tie |
| Mystery game puzzles | 33.0% | 26.0% | GLM 5.3 |
| LMArena Text: hard prompts | 1490 | 1495 | Kimi K3 |
| LMArena Text: expert | 1514 | 1520 | Kimi K3 |
| LMArena Text: hard prompts in English | 1496 | 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 index15
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 91.1% | 97.2% | Kimi K3 |
| FrontierMath, tiers 1 to 3 | 68.8% | 72.2% | Kimi K3 |
| FrontierMath, tier 4 | 29.3% | 39.0% | Kimi K3 |
| ProofBench | 49.0% | 87.0% | Kimi K3 |
| LMArena Text: math | 1495 | 1494 | GLM 5.3 |
| LMArena Text: mathematical work | 1497 | 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 index09
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| MMLU Pro | 86.8% | 88.0% | Kimi K3 |
| LegalBench (Vals AI) | 84.8% | 86.2% | Kimi K3 |
| CorpFin (Vals AI) | Not measured | 71.6% | Only Kimi K3 measured |
| TaxEval (Vals AI) | 72.4% | 75.7% | Kimi K3 |
| MortgageTax (Vals AI) | Not measured | 66.3% | Only Kimi K3 measured |
| MedCode (Vals AI) | 42.9% | 49.4% | Kimi K3 |
| SimpleQA Verified | 41.0% | 50.6% | Kimi K3 |
| LMArena Text: science | 1498 | 1508 | Kimi K3 |
| LMArena Text: medicine and healthcare | 1481 | 1489 | Kimi K3 |
| LMArena Text: legal and government | 1473 | 1503 | Kimi K3 |
| LMArena Text: business and finance | 1459 | 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 index17
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1295 | 1335 | Kimi K3 |
| Design Arena: UI components | 1314 | 1344 | Kimi K3 |
| Design Arena: game dev | 1311 | 1359 | Kimi K3 |
| Design Arena: data viz | 1259 | 1351 | Kimi K3 |
| Design Arena: 3D | 1332 | 1388 | Kimi K3 |
| Design Arena: all code categories | 1304 | 1360 | Kimi K3 |
| Design Arena: SVG | 1293 | 1302 | Kimi K3 |
| Design Arena: ASCII art | 1213 | Not measured | Only GLM 5.3 measured |
| LiveBench design | 77.3% | 77.2% | GLM 5.3 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index915
| Benchmark | GLM 5.3 | Kimi K3 | Leader |
|---|---|---|---|
| Vals Index | 59.7% | 53.0% | GLM 5.3 |
| LiveBench data analysis | 70.2% | 78.7% | Kimi K3 |
| Public Benefits Bench (Vals AI) | 68.5% | 68.2% | GLM 5.3 |
| SAGE (Vals AI) | Not measured | 52.8% | Only Kimi K3 measured |
| MedScribe (Vals AI) | 88.8% | 88.0% | GLM 5.3 |
| Vals Multimodal Index | Not measured | 73.4% | Only Kimi K3 measured |
| Long context reasoning (AA-LCR) | 79.7% | 88.7% | Kimi K3 |
| DTBench | 87.7% | 91.2% | Kimi K3 |
| LMCA | 55.5% | 52.7% | GLM 5.3 |
| Surface Evolver Bench | Not measured | 95.0% | Only Kimi K3 measured |
| Furniture assembly | Not measured | 34.2% | Only Kimi K3 measured |
| LMArena Text | 1474 | 1476 | Kimi K3 |
| LMArena Text: instruction following | 1479 | 1485 | Kimi K3 |
| LMArena Text: creative writing | 1458 | 1457 | GLM 5.3 |
| LMArena Text: English | 1482 | 1481 | GLM 5.3 |
| LMArena Text: non-English | 1459 | 1466 | Kimi K3 |
| LMArena Text: Chinese | 1532 | 1529 | GLM 5.3 |
| LMArena Text: German | 1488 | 1490 | Kimi K3 |
| LMArena Text: Japanese | 1460 | 1494 | Kimi K3 |
| LMArena Text: Korean | 1460 | 1460 | Kimi K3 |
| LMArena Text: French | 1503 | 1492 | GLM 5.3 |
| LMArena Text: Spanish | 1462 | 1472 | Kimi K3 |
| LMArena Text: Russian | 1469 | 1485 | Kimi K3 |
| LMArena Text: Polish | 1466 | 1458 | GLM 5.3 |
| LMArena Text: multi-turn | 1472 | 1489 | Kimi K3 |
| LMArena Text: longer queries | 1483 | 1494 | Kimi K3 |
| LMArena Text: writing and language | 1469 | 1471 | Kimi K3 |
| LMArena Text: entertainment and media | 1447 | 1453 | Kimi K3 |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5.3 | 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 5.3 costs less
Repository review
50K input + 3K output tokens
GLM 5.3 costs less
Agent loop
200K input + 10K output tokens
GLM 5.3 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 5.3 | MoonshotAI Kimi K3 |
|---|---|---|
| Maker | Z.ai | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | August 18, 2026 | July 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.40 | $3.00 |
| Output $/Mtok | $4.40 | $15.00 |
| Coding index | 70.6 | 62.3 |
| Independent measurements behind it | 6 | 6 |
| Cost per solved task | $0.36 | $0.81 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 better than Kimi K3 for coding?
Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 62.3 for Kimi K3. Pick Kimi K3 for work measured by LMArena WebDev or AA Coding Index, where it leads.
Which is cheaper, GLM 5.3 or Kimi K3?
GLM 5.3 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 5.3 costs $0.36 and Kimi K3 $0.81.
Which has the bigger context window, GLM 5.3 or Kimi K3?
Neither: both take 1.05M tokens.
How many benchmarks is the GLM 5.3 vs Kimi K3 comparison based on?
96 benchmarks have a result for both models as of October 21, 2026. GLM 5.3's coding index rests on 6 independent benchmarks and Kimi K3's on 6. Where only one model has a result, the page says so instead of naming a winner.