Kimi K2.7 Code vs Qwen3.5 397B A17B
Updated October 21, 2026. 24 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Kimi K2.7 Code for coding: it scores 39.1 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B.
Pick Qwen3.5 397B A17B when output tokens cost 1.4x less, or when what matters is τ²-Bench Telecom or IFBench, where it leads.
- Shared results
- 24
- Kimi K2.7 Code only
- 27
- Qwen3.5 397B A17B only
- 41
- Like-for-like categories
- 7 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
Kimi K2.7 Code
Kimi K2.7 Code scores 39.1 against 28.6.
One benchmark behind each score
Intelligence
AA Intelligence Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 25.8 against 21.4.
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
Kimi K2.7 Code
Kimi K2.7 Code leads, 1264 against 1191.
Same board, both measured
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5 397B A17B
Kimi K2.7 Code $0.0023, Qwen3.5 397B A17B $0.0016 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, Qwen3.5 397B A17B 28.6 from 1 benchmark.
- Widest category
- Math, 14.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- FrontierMath, tiers 1 to 3: Kimi K2.7 Code 54.0% against Qwen3.5 397B A17B 31.2%, 22.8 points apart on a 0 to 100 scale.
- Output price
- Kimi K2.7 Code $3.35 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.4x apart.
- Context window
- Both take 262K 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 | Kimi K2.7 Code | Bars | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 1 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Web design | 7 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 22 | 2 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index60
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena WebDev | 1474 | 1400 | Kimi K2.7 Code |
| 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 |
| SciCode | 47.8% | 44.8% | Kimi K2.7 Code |
| Terminal-Bench Hard (Artificial Analysis run) | 44.7% | 40.9% | 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 | 621.9 | Kimi K2.7 Code |
| LMArena Text: coding | Not measured | 1464 | Only Qwen3.5 397B A17B measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: React | 1475 | 1388 | Kimi K2.7 Code |
| LMArena WebDev: HTML | 1451 | 1410 | Kimi K2.7 Code |
| LMArena WebDev: from an image | 1513 | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.8 | 21.4 | Kimi K2.7 Code |
| Epoch Capabilities Index | 150.1 | 146.8 | Kimi K2.7 Code |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B | 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% | 95.6% | Qwen3.5 397B A17B |
| APEX-Agents | 37.6% | 24.9% | Kimi K2.7 Code |
| 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 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 89.6% | 89.3% | Kimi K2.7 Code |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 29.0% | Kimi K2.7 Code |
| GPQA Diamond (Epoch AI run) | 87.9% | 86.4% | 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 |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | Not measured | 1448 | Only Qwen3.5 397B A17B measured |
| LMArena Text: expert | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts in English | Not measured | 1450 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | 88.9% | Kimi K2.7 Code |
| FrontierMath, tiers 1 to 3 | 54.0% | 31.2% | Kimi K2.7 Code |
| FrontierMath, tier 4 | 12.2% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text: math | Not measured | 1453 | Only Qwen3.5 397B A17B measured |
| LMArena Text: mathematical work | Not measured | 1454 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| SimpleQA Verified | 36.5% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text: science | Not measured | 1457 | Only Qwen3.5 397B A17B measured |
| LMArena Text: medicine and healthcare | Not measured | 1455 | Only Qwen3.5 397B A17B measured |
| LMArena Text: legal and government | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1264 | 1191 | Kimi K2.7 Code |
| Design Arena: UI components | 1259 | 1163 | Kimi K2.7 Code |
| Design Arena: game dev | 1220 | 1141 | Kimi K2.7 Code |
| Design Arena: data viz | 1226 | 1175 | Kimi K2.7 Code |
| Design Arena: 3D | 1241 | 1161 | Kimi K2.7 Code |
| Design Arena: all code categories | 1253 | 1180 | Kimi K2.7 Code |
| Design Arena: SVG | 1176 | 1139 | Kimi K2.7 Code |
| 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 index11
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| IFBench | 63.1% | 78.8% | Qwen3.5 397B A17B |
| Long context reasoning (AA-LCR) | 79.3% | 77.3% | Kimi K2.7 Code |
| DTBench | Not measured | 87.5% | Only Qwen3.5 397B A17B measured |
| LMCA | Not measured | 37.9% | Only Qwen3.5 397B A17B measured |
| Surface Evolver Bench | 48.8% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text | Not measured | 1437 | Only Qwen3.5 397B A17B measured |
| LMArena Text: instruction following | Not measured | 1424 | Only Qwen3.5 397B A17B measured |
| LMArena Text: creative writing | Not measured | 1402 | Only Qwen3.5 397B A17B measured |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | Not measured | 1443 | Only Qwen3.5 397B A17B measured |
| LMArena Text: non-English | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Chinese | Not measured | 1498 | Only Qwen3.5 397B A17B measured |
| LMArena Text: German | Not measured | 1445 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Japanese | Not measured | 1429 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.5 397B A17B measured |
| LMArena Text: French | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Spanish | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Russian | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Polish | Not measured | 1447 | Only Qwen3.5 397B A17B measured |
| LMArena Text: multi-turn | Not measured | 1446 | Only Qwen3.5 397B A17B measured |
| LMArena Text: longer queries | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: writing and language | Not measured | 1415 | Only Qwen3.5 397B A17B measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B 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 | Kimi K2.7 Code | Qwen3.5 397B A17B | 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
Qwen3.5 397B A17B costs less
Repository review
50K input + 3K output tokens
Qwen3.5 397B A17B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | Open weights |
| Released | June 12, 2026 | February 16, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.6712 | $0.39 |
| Output $/Mtok | $3.35 | $2.34 |
| Coding index | 39.1 | 28.6 |
| 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 Qwen3.5 397B A17B for coding?
Pick Kimi K2.7 Code for coding: it scores 39.1 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B. Pick Qwen3.5 397B A17B when output tokens cost 1.4x less, or when what matters is τ²-Bench Telecom or IFBench, where it leads.
Which is cheaper, Kimi K2.7 Code or Qwen3.5 397B A17B?
Kimi K2.7 Code costs $0.6712 per million input tokens and $3.35 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for Kimi K2.7 Code only.
Which has the bigger context window, Kimi K2.7 Code or Qwen3.5 397B A17B?
Neither: both take 262K tokens.
How many benchmarks is the Kimi K2.7 Code vs Qwen3.5 397B A17B comparison based on?
24 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 Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.