Kimi K2.7 Code vs Qwen3.8 27B
Qwen3.8 27B leads Kimi K2.7 Code on coding, 74.2 to 53.4 on the Vibe Coding Index, and Qwen3.8 27B costs 1.6x less per output token ($2.55 vs $4.00 per million). Updated October 21, 2026; 21 benchmarks have a result for both.
Kimi K2.7 Code or Qwen3.8 27B: which to pick
Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 53.4 for Kimi K2.7 Code.
Pick Kimi K2.7 Code for a lower cost per solved task ($0.35 against $1.26) and work measured by Code migration (Vals AI) or Terminal-Bench 2.1 (Vals AI), where it leads.
- Shared results
- 21
- Kimi K2.7 Code only
- 30
- Qwen3.8 27B only
- 64
- Like-for-like categories
- 5 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
Qwen3.8 27B
Qwen3.8 27B scores 74.2 against 53.4.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
Qwen3.8 27B
Qwen3.8 27B leads, 33.7 against 25.8.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 27B
Qwen3.8 27B leads, 45.8 against 21.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Qwen3.8 27B has a GPQA Diamond result, 88.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 27B has a MMLU Pro result, 84.3%.
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
Qwen3.8 27B
Qwen3.8 27B takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 27B
Kimi K2.7 Code $0.0029, Qwen3.8 27B $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
Kimi K2.7 Code $0.35, Qwen3.8 27B $1.26.
Published attempt cost and pass rate
At a glance
- Coding index
- Kimi K2.7 Code 53.4 from 4 benchmarks, Qwen3.8 27B 74.2 from 4 benchmarks.
- Widest category
- Agentic work, 17.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Agentic Index: Kimi K2.7 Code 21.0 against Qwen3.8 27B 45.8, 24.8 points apart on a 0 to 100 scale.
- Output price
- Kimi K2.7 Code $4.00 against Qwen3.8 27B $2.55 per million output tokens, 1.6x apart.
- Context window
- Kimi K2.7 Code takes 262K tokens, Qwen3.8 27B 1M.
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 | Qwen3.8 27B | Ties |
|---|---|---|---|---|
| Coding | 4 | 8 | 1 tie | |
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 1 | 1 | ||
| General | 1 | 1 | ||
| All shared boards | 6 | 14 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index48
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 86.8% | Only Qwen3.8 27B measured |
| LMArena WebDev | 1474 | 1593 | Qwen3.8 27B |
| AA Coding Index | 60.8 | 68.1 | Qwen3.8 27B |
| LiveCodeBench (Vals AI) | 82.0% | 84.0% | Qwen3.8 27B |
| SWE-bench Verified (Vals AI) | 78.2% | 86.0% | Qwen3.8 27B |
| Vibe Code Bench (Vals AI) | 47.2% | 64.8% | Qwen3.8 27B |
| Code migration (Vals AI) | 25.4% | 14.2% | Kimi K2.7 Code |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | Not measured | 39.1% | Only Qwen3.8 27B measured |
| Terminal-Bench 2.1 (Vals AI) | 67.0% | 58.4% | Kimi K2.7 Code |
| SkillsBench (Vals AI) | 50.0% | 38.1% | Kimi K2.7 Code |
| CyberBench (Vals AI) | Not measured | 67.8% | Only Qwen3.8 27B measured |
| SciCode | 47.8% | 46.6% | Kimi K2.7 Code |
| Terminal-Bench Hard (Artificial Analysis run) | 44.7% | Not measured | Only Kimi K2.7 Code measured |
| 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 | 1483 | Only Qwen3.8 27B measured |
| LMArena Text: software and IT | Not measured | 1478 | Only Qwen3.8 27B measured |
| LMArena WebDev: React | 1475 | 1602 | Qwen3.8 27B |
| LMArena WebDev: HTML | 1451 | 1570 | Qwen3.8 27B |
| LMArena WebDev: from an image | 1513 | 1577 | Qwen3.8 27B |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.8 | 33.7 | Qwen3.8 27B |
| Epoch Capabilities Index | 150.1 | 151.7 | Qwen3.8 27B |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | Leader |
|---|---|---|---|
| AA Agentic Index | 21.0 | 45.8 | Qwen3.8 27B |
| 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 | 1137 | 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 | 1131 | 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 |
| LiveBench research | Not measured | 59.4% | Only Qwen3.8 27B measured |
| LiveBench browser | Not measured | 32.0% | Only Qwen3.8 27B measured |
| LiveBench long agentic | Not measured | 27.9% | Only Qwen3.8 27B measured |
| Finance Agent (Vals AI) | Not measured | 48.5% | Only Qwen3.8 27B measured |
| Tax Agent Bench (Vals AI) | Not measured | 30.9% | Only Qwen3.8 27B measured |
| Legal Research Bench (Vals AI) | Not measured | 36.1% | Only Qwen3.8 27B measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 59.7% | Only Qwen3.8 27B measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only Qwen3.8 27B measured |
| τ²-Bench Telecom | 90.1% | Not measured | Only Kimi K2.7 Code measured |
| APEX-Agents | 37.6% | 47.5% | Qwen3.8 27B |
| Vending-Bench 2 | $5,083 | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 88.9% | Only Qwen3.8 27B measured |
| LiveBench reasoning | Not measured | 80.0% | Only Qwen3.8 27B measured |
| MMMU Pro (Vals AI) | Not measured | 83.9% | Only Qwen3.8 27B measured |
| GPQA Diamond (Artificial Analysis run) | 89.6% | 90.5% | Qwen3.8 27B |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 33.9% | Kimi K2.7 Code |
| GPQA Diamond (Epoch AI run) | 87.9% | Not measured | Only Kimi K2.7 Code measured |
| ARC-AGI | Not measured | 87.5% | Only Qwen3.8 27B measured |
| ARC-AGI-2 | Not measured | 42.4% | Only Qwen3.8 27B measured |
| 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 | 1459 | Only Qwen3.8 27B measured |
| LMArena Text: expert | Not measured | 1479 | Only Qwen3.8 27B measured |
| LMArena Text: hard prompts in English | Not measured | 1461 | Only Qwen3.8 27B measured |
| LMArena Vision: diagrams | Not measured | 1285 | Only Qwen3.8 27B measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | Not measured | Only Kimi K2.7 Code measured |
| 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 |
| ProofBench | Not measured | 16.0% | Only Qwen3.8 27B measured |
| LMArena Text: math | Not measured | 1455 | Only Qwen3.8 27B measured |
| LMArena Text: mathematical work | Not measured | 1458 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.3% | Only Qwen3.8 27B measured |
| LegalBench (Vals AI) | Not measured | 82.4% | Only Qwen3.8 27B measured |
| TaxEval (Vals AI) | Not measured | 70.8% | Only Qwen3.8 27B measured |
| MortgageTax (Vals AI) | Not measured | 64.9% | Only Qwen3.8 27B measured |
| MedCode (Vals AI) | Not measured | 28.7% | Only Qwen3.8 27B measured |
| SimpleQA Verified | 36.5% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Text: science | Not measured | 1467 | Only Qwen3.8 27B measured |
| LMArena Text: medicine and healthcare | Not measured | 1437 | Only Qwen3.8 27B measured |
| LMArena Text: legal and government | Not measured | 1447 | Only Qwen3.8 27B measured |
| LMArena Text: business and finance | Not measured | 1438 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | 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 | 1227 | 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 |
| LiveBench design | Not measured | 75.9% | Only Qwen3.8 27B measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.6% | Only Qwen3.8 27B measured |
| SAGE (Vals AI) | Not measured | 52.4% | Only Qwen3.8 27B measured |
| MedScribe (Vals AI) | Not measured | 83.8% | Only Qwen3.8 27B measured |
| IFBench | 63.1% | Not measured | Only Kimi K2.7 Code measured |
| Long context reasoning (AA-LCR) | 79.3% | 82.0% | Qwen3.8 27B |
| DTBench | Not measured | 88.0% | Only Qwen3.8 27B measured |
| LMCA | Not measured | 41.4% | Only Qwen3.8 27B measured |
| Surface Evolver Bench | 48.8% | 45.0% | Kimi K2.7 Code |
| LMArena Text | Not measured | 1440 | Only Qwen3.8 27B measured |
| LMArena Text: instruction following | Not measured | 1436 | Only Qwen3.8 27B measured |
| LMArena Text: creative writing | Not measured | 1383 | Only Qwen3.8 27B measured |
| LMArena Vision | Not measured | 1269 | Only Qwen3.8 27B measured |
| LMArena Text: English | Not measured | 1448 | Only Qwen3.8 27B measured |
| LMArena Text: non-English | Not measured | 1428 | Only Qwen3.8 27B measured |
| LMArena Text: Chinese | Not measured | 1501 | Only Qwen3.8 27B measured |
| LMArena Text: German | Not measured | 1443 | Only Qwen3.8 27B measured |
| LMArena Text: Japanese | Not measured | 1387 | Only Qwen3.8 27B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.8 27B measured |
| LMArena Text: French | Not measured | 1465 | Only Qwen3.8 27B measured |
| LMArena Text: Spanish | Not measured | 1449 | Only Qwen3.8 27B measured |
| LMArena Text: Russian | Not measured | 1415 | Only Qwen3.8 27B measured |
| LMArena Text: Polish | Not measured | 1439 | Only Qwen3.8 27B measured |
| LMArena Text: multi-turn | Not measured | 1440 | Only Qwen3.8 27B measured |
| LMArena Text: longer queries | Not measured | 1448 | Only Qwen3.8 27B measured |
| LMArena Text: writing and language | Not measured | 1405 | Only Qwen3.8 27B measured |
| LMArena Text: entertainment and media | Not measured | 1393 | Only Qwen3.8 27B measured |
| LMArena Vision: English | Not measured | 1267 | Only Qwen3.8 27B measured |
| LMArena Vision: Chinese | Not measured | 1326 | Only Qwen3.8 27B measured |
| LMArena Vision: reading text | Not measured | 1281 | Only Qwen3.8 27B measured |
| LMArena Vision: humor | Not measured | 1235 | Only Qwen3.8 27B measured |
| LMArena Vision: creative writing | Not measured | 1237 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen3.8 27B | 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
Qwen3.8 27B costs less
Repository review
50K input + 3K output tokens
Qwen3.8 27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 27B 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 | Qwen3.8 27B |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | Open weights |
| Released | June 12, 2026 | August 14, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.95 | $0.425 |
| Output $/Mtok | $4.00 | $2.55 |
| Coding index | 53.4 | 74.2 |
| Independent measurements behind it | 4 | 4 |
| Cost per solved task | $0.35 | $1.26 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2.7 Code better than Qwen3.8 27B for coding?
Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 53.4 for Kimi K2.7 Code. Pick Kimi K2.7 Code for a lower cost per solved task ($0.35 against $1.26) and work measured by Code migration (Vals AI) or Terminal-Bench 2.1 (Vals AI), where it leads.
Which is cheaper, Kimi K2.7 Code or Qwen3.8 27B?
Kimi K2.7 Code costs $0.95 per million input tokens and $4.00 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Per solved SWE-bench Verified task, Kimi K2.7 Code costs $0.35 and Qwen3.8 27B $1.26.
Which has the bigger context window, Kimi K2.7 Code or Qwen3.8 27B?
Qwen3.8 27B, with 1M tokens against 262K.
How many benchmarks is the Kimi K2.7 Code vs Qwen3.8 27B comparison based on?
21 benchmarks have a result for both models as of October 21, 2026. Kimi K2.7 Code's coding index rests on 4 independent benchmarks and Qwen3.8 27B's on 4. Where only one model has a result, the page says so instead of naming a winner.