GLM 5.3 Flash vs Kimi K2 Thinking
Updated October 21, 2026. 13 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 63.4 for Kimi K2 Thinking.
Pick Kimi K2 Thinking when the benchmark that matters is ALE-Bench, where it leads.
- Shared results
- 13
- GLM 5.3 Flash only
- 89
- Kimi K2 Thinking only
- 17
- Like-for-like categories
- 6 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
GLM 5.3 Flash
GLM 5.3 Flash scores 71.0 against 63.4.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 41.8 against 22.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GLM 5.3 Flash has a AA Agentic Index result, 50.9.
Directional only
Reasoning
GPQA Diamond
GLM 5.3 Flash
GLM 5.3 Flash leads, 86.4% 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 Flash
GLM 5.3 Flash leads, 86.1% against 81.1%.
Same board, both measured
Web design
Design Arena: websites
GLM 5.3 Flash
GLM 5.3 Flash leads, 1272 against 1113.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 Flash has a Vals Index result, 50.9%.
Directional only
Long documents
Listed context window
GLM 5.3 Flash
GLM 5.3 Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 Flash
GLM 5.3 Flash $0.0004, Kimi K2 Thinking $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3 Flash
GLM 5.3 Flash $0.02, Kimi K2 Thinking $0.61.
Published attempt cost and pass rate
At a glance
- Coding index
- GLM 5.3 Flash 71.0 from 2 benchmarks, Kimi K2 Thinking 63.4 from 1 benchmark.
- Widest category
- Web design, 19.9 points apart on average over 1 shared benchmark.
- Widest single gap
- SWE-bench Verified (Vals AI): GLM 5.3 Flash 92.0% against Kimi K2 Thinking 60.2%, 31.8 points apart on a 0 to 100 scale.
- Output price
- GLM 5.3 Flash $0.50 against Kimi K2 Thinking $2.50 per million output tokens, 5.0x apart.
- Context window
- GLM 5.3 Flash 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 Flash | Bars | Kimi K2 Thinking | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 3 | 0 | ||
| Knowledge | 3 | 0 | ||
| Web design | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 12 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index21
| Benchmark | GLM 5.3 Flash | Kimi K2 Thinking | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 63.4% | Only Kimi K2 Thinking measured |
| LiveBench coding | 80.6% | Not measured | Only GLM 5.3 Flash measured |
| LMArena WebDev | 1607 | Not measured | Only GLM 5.3 Flash measured |
| AA Coding Index | 71.5 | Not measured | Only GLM 5.3 Flash measured |
| LiveCodeBench (Vals AI) | 80.5% | 63.1% | GLM 5.3 Flash |
| SWE-bench Verified (Vals AI) | 92.0% | 60.2% | GLM 5.3 Flash |
| Terminal-Bench 4 (Vals AI) | 37.4% | Not measured | Only GLM 5.3 Flash measured |
| Vibe Code Bench (Vals AI) | 30.8% | Not measured | Only GLM 5.3 Flash measured |
| Code migration (Vals AI) | 20.5% | Not measured | Only GLM 5.3 Flash measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only GLM 5.3 Flash measured |
| IOI (Vals AI) | 52.5% | Not measured | Only GLM 5.3 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 62.9% | Not measured | Only GLM 5.3 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | 16.0% | Not measured | Only GLM 5.3 Flash measured |
| SkillsBench (Vals AI) | 40.2% | Not measured | Only GLM 5.3 Flash measured |
| CyberBench (Vals AI) | 67.9% | Not measured | Only GLM 5.3 Flash measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 85.3% | Only Kimi K2 Thinking measured |
| SciCode | 51.6% | Not measured | Only GLM 5.3 Flash 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 | 31.8% | Not measured | Only GLM 5.3 Flash measured |
| FrontierSWE | 18.1% | Not measured | Only GLM 5.3 Flash measured |
| WeirdML | Not measured | 42.8% | Only Kimi K2 Thinking measured |
| ALE-Bench | 303.6 | 597.5 | Kimi K2 Thinking |
| LMArena Text: coding | 1507 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: software and IT | 1500 | Not measured | Only GLM 5.3 Flash measured |
| LMArena WebDev: React | 1624 | Not measured | Only GLM 5.3 Flash measured |
| LMArena WebDev: HTML | 1577 | Not measured | Only GLM 5.3 Flash measured |
| LMArena WebDev: from an image | 1578 | Not measured | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 10 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5.3 Flash | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Intelligence Index | 41.8 | 22.0 | GLM 5.3 Flash |
| Epoch Capabilities Index | 153.1 | 145.8 | GLM 5.3 Flash |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | GLM 5.3 Flash | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Agentic Index | 50.9 | Not measured | Only GLM 5.3 Flash measured |
| LiveBench research | 70.1% | Not measured | Only GLM 5.3 Flash measured |
| LiveBench browser | 84.0% | Not measured | Only GLM 5.3 Flash measured |
| LiveBench long agentic | 28.4% | Not measured | Only GLM 5.3 Flash measured |
| SREBench (Vals AI) | 0.8% | Not measured | Only GLM 5.3 Flash measured |
| Finance Agent (Vals AI) | 57.9% | Not measured | Only GLM 5.3 Flash measured |
| Tax Agent Bench (Vals AI) | 31.6% | Not measured | Only GLM 5.3 Flash measured |
| Legal Research Bench (Vals AI) | 45.2% | Not measured | Only GLM 5.3 Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.4% | Not measured | Only GLM 5.3 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 55.9% | Not measured | Only GLM 5.3 Flash measured |
| Terminal-Bench-Science (Vals AI) | 2.9% | Not measured | Only GLM 5.3 Flash measured |
| τ²-Bench Telecom | Not measured | 93.0% | Only Kimi K2 Thinking measured |
| APEX-Agents | 52.8% | Not measured | Only GLM 5.3 Flash measured |
| METR time horizons | Not measured | 59.2% | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GLM 5.3 Flash | Kimi K2 Thinking | Leader |
|---|---|---|---|
| GPQA Diamond | 86.4% | 78.5% | GLM 5.3 Flash |
| LiveBench reasoning | 77.6% | Not measured | Only GLM 5.3 Flash measured |
| MMMU Pro (Vals AI) | 86.0% | Not measured | Only GLM 5.3 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 91.2% | 83.8% | GLM 5.3 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 39.9% | 23.8% | GLM 5.3 Flash |
| GPQA Diamond (Epoch AI run) | 90.2% | Not measured | Only GLM 5.3 Flash measured |
| ARC-AGI | 91.0% | Not measured | Only GLM 5.3 Flash measured |
| ARC-AGI-2 | 65.8% | Not measured | Only GLM 5.3 Flash measured |
| Chess puzzles | 21.0% | Not measured | Only GLM 5.3 Flash measured |
| Mystery game puzzles | 8.0% | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: hard prompts | 1490 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: expert | 1511 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: hard prompts in English | 1488 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision: diagrams | 1317 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision: homework | 1318 | Not measured | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GLM 5.3 Flash | 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 | 93.9% | Not measured | Only GLM 5.3 Flash measured |
| FrontierMath, tiers 1 to 3 | 55.8% | Not measured | Only GLM 5.3 Flash measured |
| FrontierMath, tier 4 | 17.1% | Not measured | Only GLM 5.3 Flash measured |
| ProofBench | 21.0% | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: math | 1503 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: mathematical work | 1497 | Not measured | Only GLM 5.3 Flash 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 Flash | Kimi K2 Thinking | Leader |
|---|---|---|---|
| MMLU Pro | 86.1% | 81.1% | GLM 5.3 Flash |
| LegalBench (Vals AI) | 83.9% | 80.2% | GLM 5.3 Flash |
| 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) | 75.6% | 71.7% | GLM 5.3 Flash |
| MedQA (Vals AI) | Not measured | 92.6% | Only Kimi K2 Thinking measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 84.8% | Only Kimi K2 Thinking measured |
| LMArena Text: science | 1484 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: medicine and healthcare | 1475 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: legal and government | 1473 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: business and finance | 1460 | Not measured | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5.3 Flash | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Design Arena: websites | 1272 | 1113 | GLM 5.3 Flash |
| Design Arena: UI components | 1316 | Not measured | Only GLM 5.3 Flash measured |
| Design Arena: game dev | 1279 | Not measured | Only GLM 5.3 Flash measured |
| Design Arena: data viz | 1262 | Not measured | Only GLM 5.3 Flash measured |
| Design Arena: 3D | 1316 | Not measured | Only GLM 5.3 Flash measured |
| Design Arena: all code categories | 1282 | Not measured | Only GLM 5.3 Flash measured |
| Design Arena: SVG | 1284 | Not measured | Only GLM 5.3 Flash measured |
| Design Arena: ASCII art | 1269 | Not measured | Only GLM 5.3 Flash measured |
| LiveBench design | 77.2% | Not measured | Only GLM 5.3 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5.3 Flash | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Vals Index | 50.9% | Not measured | Only GLM 5.3 Flash measured |
| LiveBench data analysis | 76.4% | Not measured | Only GLM 5.3 Flash measured |
| MedScribe (Vals AI) | 88.9% | Not measured | Only GLM 5.3 Flash measured |
| IFBench | Not measured | 68.1% | Only Kimi K2 Thinking measured |
| Long context reasoning (AA-LCR) | 80.0% | 72.0% | GLM 5.3 Flash |
| CL-bench | Not measured | 17.6% | Only Kimi K2 Thinking measured |
| Surface Evolver Bench | 52.5% | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text | 1471 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: instruction following | 1478 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: creative writing | 1441 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision | 1294 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: English | 1474 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: non-English | 1462 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Chinese | 1531 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: German | 1462 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Japanese | 1444 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Korean | 1436 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: French | 1491 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Spanish | 1475 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Russian | 1465 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Polish | 1450 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: multi-turn | 1469 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: longer queries | 1481 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: writing and language | 1455 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: entertainment and media | 1440 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision: English | 1295 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision: Chinese | 1363 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision: reading text | 1299 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision: humor | 1279 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Vision: creative writing | 1270 | Not measured | Only GLM 5.3 Flash measured |
| 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 5.3 Flash | 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
GLM 5.3 Flash costs less
Repository review
50K input + 3K output tokens
GLM 5.3 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 5.3 Flash 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 Flash | MoonshotAI Kimi K2 Thinking |
|---|---|---|
| Maker | Z.ai | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | August 26, 2026 | November 6, 2025 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.15 | $0.60 |
| Output $/Mtok | $0.50 | $2.50 |
| Coding index | 71.0 | 63.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.02 | $0.61 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 Flash better than Kimi K2 Thinking for coding?
Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 63.4 for Kimi K2 Thinking. Pick Kimi K2 Thinking when the benchmark that matters is ALE-Bench, where it leads.
Which is cheaper, GLM 5.3 Flash or Kimi K2 Thinking?
GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Kimi K2 Thinking costs $0.60 and $2.50. Per solved SWE-bench Verified task, GLM 5.3 Flash costs $0.02 and Kimi K2 Thinking $0.61.
Which has the bigger context window, GLM 5.3 Flash or Kimi K2 Thinking?
GLM 5.3 Flash, with 1.05M tokens against 262K.
How many benchmarks is the GLM 5.3 Flash vs Kimi K2 Thinking comparison based on?
13 benchmarks have a result for both models as of October 21, 2026. GLM 5.3 Flash's coding index rests on 2 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.