GLM 5.3 Flash vs Kimi K3.1 Pro
Kimi K3.1 Pro leads GLM 5.3 Flash on coding, 82.2 to 57.7 on the Vibe Coding Index, and GLM 5.3 Flash costs 20.0x less per output token ($0.50 vs $10.00 per million). Updated October 29, 2026; 30 benchmarks have a result for both.
GLM 5.3 Flash or Kimi K3.1 Pro: which to pick
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 57.7 for GLM 5.3 Flash, though on 4 benchmarks against 6.
Pick GLM 5.3 Flash for output tokens 20.0x cheaper ($0.50 vs $10.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
- Shared results
- 30
- GLM 5.3 Flash only
- 72
- Kimi K3.1 Pro only
- 5
- 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
Kimi K3.1 Pro
Kimi K3.1 Pro scores 82.2 against 57.7.
6 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Kimi K3.1 Pro has a AA Intelligence Index result, 46.0.
Directional only
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
No call
Only GLM 5.3 Flash has a GPQA Diamond result, 86.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 5.3 Flash has a MMLU Pro result, 86.1%.
Directional only
Web design
Design Arena: websites
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 1325 against 1271.
Same board, both measured
General
Vals Index
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 62.5% against 50.9%.
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 Flash
GLM 5.3 Flash $0.0004, Kimi K3.1 Pro $0.0070 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GLM 5.3 Flash has the number, $0.02.
Directional only
At a glance
- Coding index
- GLM 5.3 Flash 57.7 from 6 benchmarks, Kimi K3.1 Pro 82.2 from 4 benchmarks.
- Widest category
- Math, 70.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ProofBench: GLM 5.3 Flash 21.0% against Kimi K3.1 Pro 91.0%, 70.0 points apart on a 0 to 100 scale.
- Output price
- GLM 5.3 Flash $0.50 against Kimi K3.1 Pro $10.00 per million output tokens, 20.0x 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 Flash | Bars | Kimi K3.1 Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 9 | ||
| Agentic work | 2 | 5 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 1 | ||
| Web design | 0 | 8 | ||
| General | 0 | 3 | ||
| All shared boards | 2 | 28 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index09
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| LiveBench coding | 80.6% | 81.8% | Kimi K3.1 Pro |
| LMArena WebDev | 1607 | 1695 | Kimi K3.1 Pro |
| AA Coding Index | 71.5 | Not measured | Only GLM 5.3 Flash measured |
| LiveCodeBench (Vals AI) | 80.5% | Not measured | Only GLM 5.3 Flash measured |
| SWE-bench Verified (Vals AI) | 92.0% | Not measured | Only GLM 5.3 Flash measured |
| Terminal-Bench 4 (Vals AI) | 37.4% | 63.6% | Kimi K3.1 Pro |
| Vibe Code Bench (Vals AI) | 30.8% | 84.9% | Kimi K3.1 Pro |
| 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% | 81.9% | Kimi K3.1 Pro |
| 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 |
| SciCode | 51.6% | 60.8% | Kimi K3.1 Pro |
| FrontierCode | 31.8% | Not measured | Only GLM 5.3 Flash measured |
| FrontierSWE | 18.1% | Not measured | Only GLM 5.3 Flash measured |
| ALE-Bench | 303.6 | 1932.8 | Kimi K3.1 Pro |
| LMArena Text: coding | 1509 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: software and IT | 1502 | Not measured | Only GLM 5.3 Flash measured |
| LMArena WebDev: React | 1624 | 1701 | Kimi K3.1 Pro |
| LMArena WebDev: HTML | 1577 | 1706 | Kimi K3.1 Pro |
| LMArena WebDev: from an image | 1578 | Not measured | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 46.0 | Only Kimi K3.1 Pro measured |
| Epoch Capabilities Index | 153.1 | Not measured | Only GLM 5.3 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 50.9 | Not measured | Only GLM 5.3 Flash measured |
| LiveBench research | 70.1% | 77.9% | Kimi K3.1 Pro |
| LiveBench browser | 59.8% | 75.9% | Kimi K3.1 Pro |
| LiveBench long agentic | 19.0% | 39.1% | Kimi K3.1 Pro |
| 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% | 24.9% | GLM 5.3 Flash |
| Legal Research Bench (Vals AI) | 45.2% | 37.5% | GLM 5.3 Flash |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.4% | 11.7% | Kimi K3.1 Pro |
| Excel Modeling Benchmark (Vals AI) | 55.9% | Not measured | Only GLM 5.3 Flash measured |
| BioMysteryBench (Vals AI) | Not measured | 75.6% | Only Kimi K3.1 Pro measured |
| Terminal-Bench-Science (Vals AI) | 2.9% | 31.4% | Kimi K3.1 Pro |
| Vals Science Index | Not measured | 44.4% | Only Kimi K3.1 Pro measured |
| APEX-Agents | 52.8% | Not measured | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 86.4% | Not measured | Only GLM 5.3 Flash measured |
| LiveBench reasoning | 77.6% | 91.1% | Kimi K3.1 Pro |
| MysteryMechanism (Vals AI) | Not measured | 26.1% | Only Kimi K3.1 Pro measured |
| MMMU Pro (Vals AI) | 86.0% | Not measured | Only GLM 5.3 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 91.2% | Not measured | Only GLM 5.3 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.9% | 52.5% | Kimi K3.1 Pro |
| 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 | 1492 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: expert | 1514 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: hard prompts in English | 1489 | 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 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| 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% | 91.0% | Kimi K3.1 Pro |
| LMArena Text: math | 1502 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: mathematical work | 1496 | Not measured | Only GLM 5.3 Flash measured |
| MathArena | Not measured | 59.6% | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| MMLU Pro | 86.1% | Not measured | Only GLM 5.3 Flash measured |
| LegalBench (Vals AI) | 83.9% | Not measured | Only GLM 5.3 Flash measured |
| TaxEval (Vals AI) | 75.6% | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: science | 1484 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: medicine and healthcare | 1478 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: legal and government | 1475 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: business and finance | 1461 | Not measured | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1271 | 1325 | Kimi K3.1 Pro |
| Design Arena: UI components | 1308 | 1400 | Kimi K3.1 Pro |
| Design Arena: game dev | 1275 | 1410 | Kimi K3.1 Pro |
| Design Arena: data viz | 1260 | 1300 | Kimi K3.1 Pro |
| Design Arena: 3D | 1314 | 1451 | Kimi K3.1 Pro |
| Design Arena: all code categories | 1279 | 1354 | Kimi K3.1 Pro |
| Design Arena: SVG | 1281 | 1328 | Kimi K3.1 Pro |
| Design Arena: ASCII art | 1270 | Not measured | Only GLM 5.3 Flash measured |
| LiveBench design | 77.2% | 77.8% | Kimi K3.1 Pro |
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Vals Index | 50.9% | 62.5% | Kimi K3.1 Pro |
| LiveBench data analysis | 76.4% | 79.1% | Kimi K3.1 Pro |
| SAGE (Vals AI) | 89.3% | Not measured | Only GLM 5.3 Flash measured |
| MedScribe (Vals AI) | 88.9% | Not measured | Only GLM 5.3 Flash measured |
| Long context reasoning (AA-LCR) | 80.0% | 86.3% | Kimi K3.1 Pro |
| Surface Evolver Bench | 52.5% | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text | 1473 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: instruction following | 1481 | 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 | 1475 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: non-English | 1463 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Chinese | 1530 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: German | 1455 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Japanese | 1450 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Korean | 1442 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: French | 1488 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Spanish | 1473 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Russian | 1467 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: Polish | 1452 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: multi-turn | 1471 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: longer queries | 1484 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: writing and language | 1456 | Not measured | Only GLM 5.3 Flash measured |
| LMArena Text: entertainment and media | 1442 | 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 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5.3 Flash | Kimi K3.1 Pro | 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 K3.1 Pro |
|---|---|---|
| Maker | Z.ai | Moonshot AI |
| Weights | Open weights | No public weights listed |
| Released | August 26, 2026 | October 23, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.15 | $2.00 |
| Output $/Mtok | $0.50 | $10.00 |
| Coding index | 57.7 | 82.2 |
| Independent measurements behind it | 6 | 4 |
| Cost per solved task | $0.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 Flash better than Kimi K3.1 Pro for coding?
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 57.7 for GLM 5.3 Flash, though on 4 benchmarks against 6. Pick GLM 5.3 Flash for output tokens 20.0x cheaper ($0.50 vs $10.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
Which is cheaper, GLM 5.3 Flash or Kimi K3.1 Pro?
GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Kimi K3.1 Pro costs $2.00 and $10.00. Cost per solved task is known for GLM 5.3 Flash only.
Which has the bigger context window, GLM 5.3 Flash or Kimi K3.1 Pro?
Neither: both take 1.05M tokens.
How many benchmarks is the GLM 5.3 Flash vs Kimi K3.1 Pro comparison based on?
30 benchmarks have a result for both models as of October 29, 2026. GLM 5.3 Flash's coding index rests on 6 independent benchmarks and Kimi K3.1 Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.