Kimi K2.7 Code vs Qwen3 32B
Updated October 21, 2026. 11 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Kimi K2.7 Code and Qwen3 32B are level for coding, 39.1 against 40.0 on the Vibe Coding Index, so price and context decide.
Pick Kimi K2.7 Code when the context window is larger, 262K against 131K tokens, or when what matters is SciCode or Terminal-Bench Hard (Artificial Analysis run), where it leads. Pick Qwen3 32B when output tokens cost 12.0x less.
- Shared results
- 11
- Kimi K2.7 Code only
- 40
- Qwen3 32B only
- 31
- 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
No call
Level: 39.1 against 40.0, inside 2 points.
One benchmark behind each score
Intelligence
AA Intelligence Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 25.8 against 7.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Kimi K2.7 Code has a AA Agentic Index result, 21.0.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2.7 Code has a Design Arena: websites result, 1264.
Directional only
Long documents
Listed context window
Kimi K2.7 Code
Kimi K2.7 Code takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 32B
Kimi K2.7 Code $0.0023, Qwen3 32B $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2.7 Code has the number, $0.35.
Directional only
At a glance
- Coding index
- Kimi K2.7 Code 39.1 from 1 benchmark, Qwen3 32B 40.0 from 1 benchmark.
- Widest category
- Agentic work, 60.2 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Kimi K2.7 Code 79.3% against Qwen3 32B 0.0%, 79.3 points apart on a 0 to 100 scale.
- Output price
- Kimi K2.7 Code $3.35 against Qwen3 32B $0.28 per million output tokens, 12.0x apart.
- Context window
- Kimi K2.7 Code takes 262K tokens, Qwen3 32B 131K.
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 | Kimi K2.7 Code | Bars | Qwen3 32B | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 11 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index20
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 40.0% | Only Qwen3 32B measured |
| LMArena WebDev | 1474 | Not measured | Only Kimi K2.7 Code measured |
| AA Coding Index | 60.8 | Not measured | Only Kimi K2.7 Code measured |
| LiveCodeBench (Vals AI) | 82.0% | Not measured | Only Kimi K2.7 Code measured |
| SWE-bench Verified (Vals AI) | 78.2% | Not measured | Only Kimi K2.7 Code measured |
| Vibe Code Bench (Vals AI) | 47.2% | Not measured | Only Kimi K2.7 Code measured |
| Code migration (Vals AI) | 25.4% | Not measured | Only Kimi K2.7 Code measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Kimi K2.7 Code measured |
| Terminal-Bench 2.1 (Vals AI) | 67.0% | Not measured | Only Kimi K2.7 Code measured |
| SkillsBench (Vals AI) | 50.0% | Not measured | Only Kimi K2.7 Code measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 54.6% | Only Qwen3 32B measured |
| SciCode | 47.8% | 36.0% | Kimi K2.7 Code |
| Terminal-Bench Hard (Artificial Analysis run) | 44.7% | 3.0% | Kimi K2.7 Code |
| FrontierCode | 30.1% | Not measured | Only Kimi K2.7 Code measured |
| WeirdML | 54.1% | Not measured | Only Kimi K2.7 Code measured |
| ALE-Bench | 886.2 | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text: coding | Not measured | 1357 | Only Qwen3 32B measured |
| LMArena Text: software and IT | Not measured | 1366 | Only Qwen3 32B measured |
| LMArena WebDev: React | 1475 | Not measured | Only Kimi K2.7 Code measured |
| LMArena WebDev: HTML | 1451 | Not measured | Only Kimi K2.7 Code measured |
| LMArena WebDev: from an image | 1513 | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.8 | 7.3 | Kimi K2.7 Code |
| Epoch Capabilities Index | 150.1 | 138.4 | Kimi K2.7 Code |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| AA Agentic Index | 21.0 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: agents building web apps | 1176 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: agents building full-stack apps | 1175 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: agents building mobile apps | 1143 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: agents building Android apps | 1143 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: agents building Godot games | 1147 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: agents building games | 1130 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: HTML slides | 1201 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: PowerPoint slides | 1154 | Not measured | Only Kimi K2.7 Code measured |
| τ²-Bench Telecom | 90.1% | 29.8% | Kimi K2.7 Code |
| APEX-Agents | 37.6% | Not measured | Only Kimi K2.7 Code measured |
| Vending-Bench 2 | $5,083 | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 89.6% | 66.8% | Kimi K2.7 Code |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 7.4% | Kimi K2.7 Code |
| GPQA Diamond (Epoch AI run) | 87.9% | 65.7% | Kimi K2.7 Code |
| SimpleBench | 57.9% | Not measured | Only Kimi K2.7 Code measured |
| Chess puzzles | 14.0% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text: hard prompts | Not measured | 1334 | Only Qwen3 32B measured |
| LMArena Text: expert | Not measured | 1362 | Only Qwen3 32B measured |
| LMArena Text: hard prompts in English | Not measured | 1350 | Only Qwen3 32B measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 73.0 | Only Qwen3 32B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.0% | Only Qwen3 32B measured |
| OTIS Mock AIME | 95.6% | 66.9% | Kimi K2.7 Code |
| FrontierMath, tiers 1 to 3 | 54.0% | Not measured | Only Kimi K2.7 Code measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text: math | Not measured | 1399 | Only Qwen3 32B measured |
| LMArena Text: mathematical work | Not measured | 1420 | Only Qwen3 32B measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 79.8% | Only Qwen3 32B measured |
| SimpleQA Verified | 36.5% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text: science | Not measured | 1372 | Only Qwen3 32B measured |
| LMArena Text: medicine and healthcare | Not measured | 1368 | Only Qwen3 32B measured |
| LMArena Text: legal and government | Not measured | 1324 | Only Qwen3 32B measured |
| LMArena Text: business and finance | Not measured | 1318 | Only Qwen3 32B measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| Design Arena: websites | 1264 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: UI components | 1259 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: game dev | 1220 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: data viz | 1226 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: 3D | 1241 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: all code categories | 1253 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: SVG | 1176 | Not measured | Only Kimi K2.7 Code measured |
| Design Arena: ASCII art | 1196 | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2.7 Code | Qwen3 32B | Leader |
|---|---|---|---|
| IFBench | 63.1% | 36.3% | Kimi K2.7 Code |
| Long context reasoning (AA-LCR) | 79.3% | 0.0% | Kimi K2.7 Code |
| DTBench | Not measured | 67.5% | Only Qwen3 32B measured |
| LMCA | Not measured | 17.3% | Only Qwen3 32B measured |
| Fiction.LiveBench | Not measured | 74.2% | Only Qwen3 32B measured |
| Surface Evolver Bench | 48.8% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text | Not measured | 1340 | Only Qwen3 32B measured |
| LMArena Text: instruction following | Not measured | 1305 | Only Qwen3 32B measured |
| LMArena Text: creative writing | Not measured | 1297 | Only Qwen3 32B measured |
| LMArena Text: English | Not measured | 1359 | Only Qwen3 32B measured |
| LMArena Text: non-English | Not measured | 1317 | Only Qwen3 32B measured |
| LMArena Text: Chinese | Not measured | 1357 | Only Qwen3 32B measured |
| LMArena Text: German | Not measured | 1341 | Only Qwen3 32B measured |
| LMArena Text: Russian | Not measured | 1311 | Only Qwen3 32B measured |
| LMArena Text: multi-turn | Not measured | 1331 | Only Qwen3 32B measured |
| LMArena Text: longer queries | Not measured | 1327 | Only Qwen3 32B measured |
| LMArena Text: writing and language | Not measured | 1298 | Only Qwen3 32B measured |
| LMArena Text: entertainment and media | Not measured | 1279 | Only Qwen3 32B measured |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3 32B | 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
Qwen3 32B costs less
Repository review
50K input + 3K output tokens
Qwen3 32B costs less
Agent loop
200K input + 10K output tokens
Qwen3 32B 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 | MoonshotAI Kimi K2.7 Code | Qwen3 32B |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | Open weights |
| Released | June 12, 2026 | April 28, 2025 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.6712 | $0.08 |
| Output $/Mtok | $3.35 | $0.28 |
| Coding index | 39.1 | 40.0 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.35 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2.7 Code better than Qwen3 32B for coding?
Kimi K2.7 Code and Qwen3 32B are level for coding, 39.1 against 40.0 on the Vibe Coding Index, so price and context decide. Pick Kimi K2.7 Code when the context window is larger, 262K against 131K tokens, or when what matters is SciCode or Terminal-Bench Hard (Artificial Analysis run), where it leads. Pick Qwen3 32B when output tokens cost 12.0x less.
Which is cheaper, Kimi K2.7 Code or Qwen3 32B?
Kimi K2.7 Code costs $0.6712 per million input tokens and $3.35 per million output tokens; Qwen3 32B costs $0.08 and $0.28. Cost per solved task is known for Kimi K2.7 Code only.
Which has the bigger context window, Kimi K2.7 Code or Qwen3 32B?
Kimi K2.7 Code, with 262K tokens against 131K.
How many benchmarks is the Kimi K2.7 Code vs Qwen3 32B comparison based on?
11 benchmarks have a result for both models as of October 21, 2026. Kimi K2.7 Code's coding index rests on 1 independent benchmark and Qwen3 32B's on 1. Where only one model has a result, the page says so instead of naming a winner.