GLM 5.3 vs Kimi K2 Thinking
GLM 5.3 leads Kimi K2 Thinking on the Artificial Analysis Intelligence Index, 44.8 to 22.0, and Kimi K2 Thinking costs 1.8x less per output token ($2.50 vs $4.40 per million). Updated October 22, 2026; 14 benchmarks have a result for both.
GLM 5.3 or Kimi K2 Thinking: which to pick
Only GLM 5.3 has a coding score, 70.6 on the Vibe Coding Index; Kimi K2 Thinking has none, so the two cannot be ranked on coding.
Pick Kimi K2 Thinking for output tokens 1.8x cheaper ($2.50 vs $4.40 per million).
- Shared results
- 14
- GLM 5.3 only
- 86
- Kimi K2 Thinking only
- 16
- Like-for-like categories
- 6 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
No call
Only GLM 5.3 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GLM 5.3
GLM 5.3 leads, 44.8 against 22.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GLM 5.3 has a AA Agentic Index result, 53.1.
Directional only
Reasoning
GPQA Diamond
GLM 5.3
GLM 5.3 leads, 88.1% against 78.5%.
Same board, both measured
Math
AIME
No call
Only Kimi K2 Thinking has a AIME result, 85.4%.
Directional only
Knowledge
MMLU Pro
GLM 5.3
GLM 5.3 leads, 86.8% against 81.1%.
Same board, both measured
Web design
Design Arena: websites
GLM 5.3
GLM 5.3 leads, 1295 against 1113.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 has a Vals Index result, 59.7%.
Directional only
Long documents
Listed context window
GLM 5.3
GLM 5.3 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2 Thinking
GLM 5.3 $0.0036, Kimi K2 Thinking $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3
GLM 5.3 $0.36, Kimi K2 Thinking $0.61.
Published attempt cost and pass rate
At a glance
- Coding index
- GLM 5.3 70.6 from 6 benchmarks, Kimi K2 Thinking not benchmarked.
- Widest category
- Coding, 27.3 points apart on average over 4 shared benchmarks.
- Widest single gap
- SWE-bench Verified (Vals AI): GLM 5.3 95.4% against Kimi K2 Thinking 60.2%, 35.2 points apart on a 0 to 100 scale.
- Output price
- GLM 5.3 $4.40 against Kimi K2 Thinking $2.50 per million output tokens, 1.8x apart.
- Context window
- GLM 5.3 takes 1.05M tokens, Kimi K2 Thinking 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 | GLM 5.3 | Bars | Kimi K2 Thinking | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 3 | 0 | ||
| Knowledge | 3 | 0 | ||
| Web design | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 14 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 63.4% | Only Kimi K2 Thinking measured |
| LiveBench coding | 82.8% | Not measured | Only GLM 5.3 measured |
| LMArena WebDev | 1621 | Not measured | Only GLM 5.3 measured |
| AA Coding Index | 74.8 | Not measured | Only GLM 5.3 measured |
| LiveCodeBench (Vals AI) | 80.5% | 63.1% | GLM 5.3 |
| SWE-bench Verified (Vals AI) | 95.4% | 60.2% | GLM 5.3 |
| Terminal-Bench 4 (Vals AI) | 38.9% | Not measured | Only GLM 5.3 measured |
| Vibe Code Bench (Vals AI) | 78.1% | Not measured | Only GLM 5.3 measured |
| Code migration (Vals AI) | 44.2% | Not measured | Only GLM 5.3 measured |
| ProgramBench (Vals AI) | 1.5% | Not measured | Only GLM 5.3 measured |
| IOI (Vals AI) | 68.4% | Not measured | Only GLM 5.3 measured |
| Terminal-Bench 2.1 (Vals AI) | 71.5% | Not measured | Only GLM 5.3 measured |
| Vibe Code Bench 1-100 (Vals AI) | 20.0% | Not measured | Only GLM 5.3 measured |
| SkillsBench (Vals AI) | 47.5% | Not measured | Only GLM 5.3 measured |
| CyberBench (Vals AI) | 72.1% | Not measured | Only GLM 5.3 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 85.3% | Only Kimi K2 Thinking measured |
| SciCode | 59.0% | Not measured | Only GLM 5.3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 31.1% | Only Kimi K2 Thinking measured |
| Terminal-Bench | Not measured | 35.7% | Only Kimi K2 Thinking measured |
| FrontierCode | 40.1% | Not measured | Only GLM 5.3 measured |
| FrontierSWE | 30.2% | Not measured | Only GLM 5.3 measured |
| WeirdML | 75.4% | 42.8% | GLM 5.3 |
| ALE-Bench | 1317.4 | 597.5 | GLM 5.3 |
| LMArena Text: coding | 1497 | Not measured | Only GLM 5.3 measured |
| LMArena Text: software and IT | 1493 | Not measured | Only GLM 5.3 measured |
| LMArena WebDev: React | 1641 | Not measured | Only GLM 5.3 measured |
| LMArena WebDev: HTML | 1595 | Not measured | Only GLM 5.3 measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Intelligence Index | 44.8 | 22.0 | GLM 5.3 |
| Epoch Capabilities Index | 156.0 | 145.8 | GLM 5.3 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Agentic Index | 53.1 | Not measured | Only GLM 5.3 measured |
| Design Arena: agents building mobile apps | 1194 | Not measured | Only GLM 5.3 measured |
| Design Arena: HTML slides | 1189 | Not measured | Only GLM 5.3 measured |
| Design Arena: PowerPoint slides | 1230 | Not measured | Only GLM 5.3 measured |
| LiveBench research | 73.2% | Not measured | Only GLM 5.3 measured |
| LiveBench browser | 0.0% | Not measured | Only GLM 5.3 measured |
| LiveBench long agentic | 35.9% | Not measured | Only GLM 5.3 measured |
| SREBench (Vals AI) | 9.2% | Not measured | Only GLM 5.3 measured |
| Finance Agent (Vals AI) | 55.8% | Not measured | Only GLM 5.3 measured |
| Tax Agent Bench (Vals AI) | 39.7% | Not measured | Only GLM 5.3 measured |
| Legal Research Bench (Vals AI) | 49.0% | Not measured | Only GLM 5.3 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 14.6% | Not measured | Only GLM 5.3 measured |
| Excel Modeling Benchmark (Vals AI) | 56.3% | Not measured | Only GLM 5.3 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only GLM 5.3 measured |
| τ²-Bench Telecom | Not measured | 93.0% | Only Kimi K2 Thinking measured |
| APEX-Agents | 56.6% | Not measured | Only GLM 5.3 measured |
| METR time horizons | Not measured | 59.2% | Only Kimi K2 Thinking measured |
| Vending-Bench 2 | $8,164 | Not measured | Only GLM 5.3 measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| GPQA Diamond | 88.1% | 78.5% | GLM 5.3 |
| LiveBench reasoning | 85.8% | Not measured | Only GLM 5.3 measured |
| MysteryMechanism (Vals AI) | 23.0% | Not measured | Only GLM 5.3 measured |
| GPQA Diamond (Artificial Analysis run) | 91.7% | 83.8% | GLM 5.3 |
| Humanity's Last Exam (Artificial Analysis run) | 42.3% | 23.8% | GLM 5.3 |
| GPQA Diamond (Epoch AI run) | 90.9% | Not measured | Only GLM 5.3 measured |
| Chess puzzles | 37.0% | Not measured | Only GLM 5.3 measured |
| Mystery game puzzles | 33.0% | Not measured | Only GLM 5.3 measured |
| LMArena Text: hard prompts | 1490 | Not measured | Only GLM 5.3 measured |
| LMArena Text: expert | 1514 | Not measured | Only GLM 5.3 measured |
| LMArena Text: hard prompts in English | 1496 | Not measured | Only GLM 5.3 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AIME | Not measured | 85.4% | Only Kimi K2 Thinking measured |
| MGSM (Vals AI) | Not measured | 90.2% | Only Kimi K2 Thinking measured |
| AA Math Index | Not measured | 94.7 | Only Kimi K2 Thinking measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 94.7% | Only Kimi K2 Thinking measured |
| OTIS Mock AIME | 91.1% | Not measured | Only GLM 5.3 measured |
| FrontierMath, tiers 1 to 3 | 68.8% | Not measured | Only GLM 5.3 measured |
| FrontierMath, tier 4 | 29.3% | Not measured | Only GLM 5.3 measured |
| ProofBench | 49.0% | Not measured | Only GLM 5.3 measured |
| LMArena Text: math | 1495 | Not measured | Only GLM 5.3 measured |
| LMArena Text: mathematical work | 1497 | Not measured | Only GLM 5.3 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| MMLU Pro | 86.8% | 81.1% | GLM 5.3 |
| LegalBench (Vals AI) | 84.8% | 80.2% | GLM 5.3 |
| CaseLaw (Vals AI) | Not measured | 65.7% | Only Kimi K2 Thinking measured |
| CorpFin (Vals AI) | Not measured | 60.6% | Only Kimi K2 Thinking measured |
| TaxEval (Vals AI) | 72.4% | 71.7% | GLM 5.3 |
| MedQA (Vals AI) | Not measured | 92.6% | Only Kimi K2 Thinking measured |
| MedCode (Vals AI) | 42.9% | Not measured | Only GLM 5.3 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 84.8% | Only Kimi K2 Thinking measured |
| SimpleQA Verified | 41.0% | Not measured | Only GLM 5.3 measured |
| LMArena Text: science | 1498 | Not measured | Only GLM 5.3 measured |
| LMArena Text: medicine and healthcare | 1481 | Not measured | Only GLM 5.3 measured |
| LMArena Text: legal and government | 1473 | Not measured | Only GLM 5.3 measured |
| LMArena Text: business and finance | 1459 | Not measured | Only GLM 5.3 measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Design Arena: websites | 1295 | 1113 | GLM 5.3 |
| Design Arena: UI components | 1314 | Not measured | Only GLM 5.3 measured |
| Design Arena: game dev | 1311 | Not measured | Only GLM 5.3 measured |
| Design Arena: data viz | 1260 | Not measured | Only GLM 5.3 measured |
| Design Arena: 3D | 1332 | Not measured | Only GLM 5.3 measured |
| Design Arena: all code categories | 1304 | Not measured | Only GLM 5.3 measured |
| Design Arena: SVG | 1294 | Not measured | Only GLM 5.3 measured |
| Design Arena: ASCII art | 1208 | Not measured | Only GLM 5.3 measured |
| LiveBench design | 77.3% | Not measured | Only GLM 5.3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5.3 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Vals Index | 59.7% | Not measured | Only GLM 5.3 measured |
| LiveBench data analysis | 70.2% | Not measured | Only GLM 5.3 measured |
| Public Benefits Bench (Vals AI) | 68.5% | Not measured | Only GLM 5.3 measured |
| MedScribe (Vals AI) | 88.8% | Not measured | Only GLM 5.3 measured |
| IFBench | Not measured | 68.1% | Only Kimi K2 Thinking measured |
| Long context reasoning (AA-LCR) | 79.7% | 72.0% | GLM 5.3 |
| DTBench | 87.7% | Not measured | Only GLM 5.3 measured |
| LMCA | 55.5% | Not measured | Only GLM 5.3 measured |
| CL-bench | Not measured | 17.6% | Only Kimi K2 Thinking measured |
| LMArena Text | 1474 | Not measured | Only GLM 5.3 measured |
| LMArena Text: instruction following | 1479 | Not measured | Only GLM 5.3 measured |
| LMArena Text: creative writing | 1458 | Not measured | Only GLM 5.3 measured |
| LMArena Text: English | 1482 | Not measured | Only GLM 5.3 measured |
| LMArena Text: non-English | 1459 | Not measured | Only GLM 5.3 measured |
| LMArena Text: Chinese | 1532 | Not measured | Only GLM 5.3 measured |
| LMArena Text: German | 1488 | Not measured | Only GLM 5.3 measured |
| LMArena Text: Japanese | 1460 | Not measured | Only GLM 5.3 measured |
| LMArena Text: Korean | 1460 | Not measured | Only GLM 5.3 measured |
| LMArena Text: French | 1503 | Not measured | Only GLM 5.3 measured |
| LMArena Text: Spanish | 1462 | Not measured | Only GLM 5.3 measured |
| LMArena Text: Russian | 1469 | Not measured | Only GLM 5.3 measured |
| LMArena Text: Polish | 1466 | Not measured | Only GLM 5.3 measured |
| LMArena Text: multi-turn | 1472 | Not measured | Only GLM 5.3 measured |
| LMArena Text: longer queries | 1483 | Not measured | Only GLM 5.3 measured |
| LMArena Text: writing and language | 1469 | Not measured | Only GLM 5.3 measured |
| LMArena Text: entertainment and media | 1447 | Not measured | Only GLM 5.3 measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5.3 | Kimi K2 Thinking | 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 Thinking costs less
Repository review
50K input + 3K output tokens
Kimi K2 Thinking costs less
Agent loop
200K input + 10K output tokens
Kimi K2 Thinking 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 K2 Thinking |
|---|---|---|
| Maker | Z.ai | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | August 18, 2026 | November 6, 2025 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.40 | $0.60 |
| Output $/Mtok | $4.40 | $2.50 |
| Coding index | 70.6 | Not benchmarked |
| Independent measurements behind it | 6 | 1 |
| Cost per solved task | $0.36 | $0.61 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 better than Kimi K2 Thinking for coding?
Only GLM 5.3 has a coding score, 70.6 on the Vibe Coding Index; Kimi K2 Thinking has none, so the two cannot be ranked on coding. Pick Kimi K2 Thinking for output tokens 1.8x cheaper ($2.50 vs $4.40 per million).
Which is cheaper, GLM 5.3 or Kimi K2 Thinking?
GLM 5.3 costs $1.40 per million input tokens and $4.40 per million output tokens; Kimi K2 Thinking costs $0.60 and $2.50. Per solved SWE-bench Verified task, GLM 5.3 costs $0.36 and Kimi K2 Thinking $0.61.
Which has the bigger context window, GLM 5.3 or Kimi K2 Thinking?
GLM 5.3, with 1.05M tokens against 262K.
How many benchmarks is the GLM 5.3 vs Kimi K2 Thinking comparison based on?
14 benchmarks have a result for both models as of October 22, 2026. GLM 5.3's coding index rests on 6 independent benchmarks and Kimi K2 Thinking's on 1. Where only one model has a result, the page says so instead of naming a winner.