Kimi K3.1 Pro vs Qwen3.7 Max
Kimi K3.1 Pro leads Qwen3.7 Max on coding, 82.2 to 54.1 on the Vibe Coding Index, and Qwen3.7 Max costs 2.3x less per output token ($4.425 vs $10.00 per million). Updated October 29, 2026; 18 benchmarks have a result for both.
Kimi K3.1 Pro or Qwen3.7 Max: which to pick
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 54.1 for Qwen3.7 Max.
Pick Qwen3.7 Max for output tokens 2.3x cheaper ($4.425 vs $10.00 per million).
- Shared results
- 18
- Kimi K3.1 Pro only
- 17
- Qwen3.7 Max only
- 41
- 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 54.1.
4 and 3 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 Qwen3.7 Max has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.7 Max has a GPQA Diamond result, 90.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.7 Max has a MMLU Pro result, 89.3%.
Directional only
Web design
Design Arena: websites
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 1325 against 1274.
Same board, both measured
General
Vals Index
No call
Only Kimi K3.1 Pro has a Vals Index result, 62.5%.
Directional only
Long documents
Listed context window
Kimi K3.1 Pro
Kimi K3.1 Pro takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Max
Kimi K3.1 Pro $0.0070, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.7 Max has the number, $4.69.
Directional only
At a glance
- Coding index
- Kimi K3.1 Pro 82.2 from 4 benchmarks, Qwen3.7 Max 54.1 from 3 benchmarks.
- Widest category
- Math, 65.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ProofBench: Kimi K3.1 Pro 91.0% against Qwen3.7 Max 26.0%, 65.0 points apart on a 0 to 100 scale.
- Output price
- Kimi K3.1 Pro $10.00 against Qwen3.7 Max $4.425 per million output tokens, 2.3x apart.
- Context window
- Kimi K3.1 Pro takes 1.05M tokens, Qwen3.7 Max 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 K3.1 Pro | Bars | Qwen3.7 Max | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 1 | 0 | ||
| Math | 1 | 0 | ||
| Web design | 7 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 18 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| LiveBench coding | 81.8% | Not measured | Only Kimi K3.1 Pro measured |
| LMArena WebDev | 1695 | 1515 | Kimi K3.1 Pro |
| AA Coding Index | Not measured | 66.0 | Only Qwen3.7 Max measured |
| LiveCodeBench (Vals AI) | Not measured | 87.1% | Only Qwen3.7 Max measured |
| SWE-bench Verified (Vals AI) | Not measured | 68.8% | Only Qwen3.7 Max measured |
| Terminal-Bench 4 (Vals AI) | 63.6% | Not measured | Only Kimi K3.1 Pro measured |
| Vibe Code Bench (Vals AI) | 84.9% | 47.7% | Kimi K3.1 Pro |
| Code migration (Vals AI) | Not measured | 13.1% | Only Qwen3.7 Max measured |
| IOI (Vals AI) | 81.9% | Not measured | Only Kimi K3.1 Pro measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 61.0% | Only Qwen3.7 Max measured |
| SciCode | 60.8% | 49.5% | Kimi K3.1 Pro |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only Qwen3.7 Max measured |
| ALE-Bench | 1932.8 | 1189.4 | Kimi K3.1 Pro |
| LMArena WebDev: React | 1701 | 1513 | Kimi K3.1 Pro |
| LMArena WebDev: HTML | 1706 | 1512 | Kimi K3.1 Pro |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 46.0 | Not measured | Only Kimi K3.1 Pro measured |
| Epoch Capabilities Index | Not measured | 154.0 | Only Qwen3.7 Max measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Qwen3.7 Max measured |
| Design Arena: agents building web apps | Not measured | 1209 | Only Qwen3.7 Max measured |
| Design Arena: agents building full-stack apps | Not measured | 1191 | Only Qwen3.7 Max measured |
| Design Arena: agents building mobile apps | Not measured | 1156 | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | Not measured | 1155 | Only Qwen3.7 Max measured |
| Design Arena: agents building Godot games | Not measured | 1187 | Only Qwen3.7 Max measured |
| Design Arena: agents building games | Not measured | 1124 | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | Not measured | 1055 | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | Not measured | 1149 | Only Qwen3.7 Max measured |
| LiveBench research | 77.9% | Not measured | Only Kimi K3.1 Pro measured |
| LiveBench browser | 75.9% | Not measured | Only Kimi K3.1 Pro measured |
| LiveBench long agentic | 39.1% | Not measured | Only Kimi K3.1 Pro measured |
| Finance Agent (Vals AI) | Not measured | 47.8% | Only Qwen3.7 Max measured |
| Tax Agent Bench (Vals AI) | 24.9% | 15.8% | Kimi K3.1 Pro |
| Legal Research Bench (Vals AI) | 37.5% | 25.5% | Kimi K3.1 Pro |
| Harvey's Legal Agent Benchmark (Vals AI) | 11.7% | Not measured | Only Kimi K3.1 Pro measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.0% | Only Qwen3.7 Max measured |
| BioMysteryBench (Vals AI) | 75.6% | Not measured | Only Kimi K3.1 Pro measured |
| Terminal-Bench-Science (Vals AI) | 31.4% | Not measured | Only Kimi K3.1 Pro measured |
| Vals Science Index | 44.4% | Not measured | Only Kimi K3.1 Pro measured |
| τ²-Bench Telecom | Not measured | 94.7% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.2% | Only Qwen3.7 Max measured |
| LiveBench reasoning | 91.1% | Not measured | Only Kimi K3.1 Pro measured |
| MysteryMechanism (Vals AI) | 26.1% | Not measured | Only Kimi K3.1 Pro measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.3% | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | 52.5% | 40.5% | Kimi K3.1 Pro |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only Qwen3.7 Max measured |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | Not measured | 26.0% | Only Qwen3.7 Max measured |
| Mystery game puzzles | Not measured | 32.0% | Only Qwen3.7 Max measured |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max 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 K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 95.6% | Only Qwen3.7 Max measured |
| FrontierMath, tiers 1 to 3 | Not measured | 64.6% | Only Qwen3.7 Max measured |
| FrontierMath, tier 4 | Not measured | 34.1% | Only Qwen3.7 Max measured |
| ProofBench | 91.0% | 26.0% | Kimi K3.1 Pro |
| MathArena | 59.6% | Not measured | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.3% | Only Qwen3.7 Max measured |
| LegalBench (Vals AI) | Not measured | 84.9% | Only Qwen3.7 Max measured |
| CorpFin (Vals AI) | Not measured | 63.7% | Only Qwen3.7 Max measured |
| TaxEval (Vals AI) | Not measured | 75.3% | Only Qwen3.7 Max measured |
| MedCode (Vals AI) | Not measured | 38.8% | Only Qwen3.7 Max measured |
| SimpleQA Verified | Not measured | 55.8% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1325 | 1274 | Kimi K3.1 Pro |
| Design Arena: UI components | 1400 | 1265 | Kimi K3.1 Pro |
| Design Arena: game dev | 1410 | 1264 | Kimi K3.1 Pro |
| Design Arena: data viz | 1300 | 1276 | Kimi K3.1 Pro |
| Design Arena: 3D | 1451 | 1262 | Kimi K3.1 Pro |
| Design Arena: all code categories | 1354 | 1274 | Kimi K3.1 Pro |
| Design Arena: SVG | 1328 | 1214 | Kimi K3.1 Pro |
| Design Arena: ASCII art | Not measured | 1208 | Only Qwen3.7 Max measured |
| LiveBench design | 77.8% | Not measured | Only Kimi K3.1 Pro measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | Leader |
|---|---|---|---|
| Vals Index | 62.5% | Not measured | Only Kimi K3.1 Pro measured |
| LiveBench data analysis | 79.1% | Not measured | Only Kimi K3.1 Pro measured |
| MedScribe (Vals AI) | Not measured | 79.4% | Only Qwen3.7 Max measured |
| IFBench | Not measured | 80.5% | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | 86.3% | 79.0% | Kimi K3.1 Pro |
| DTBench | Not measured | 92.3% | Only Qwen3.7 Max measured |
| LMCA | Not measured | 44.0% | Only Qwen3.7 Max measured |
| EQ-Bench 4 | Not measured | 1100 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 40 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K3.1 Pro | Qwen3.7 Max | 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
Qwen3.7 Max costs less
Repository review
50K input + 3K output tokens
Qwen3.7 Max costs less
Agent loop
200K input + 10K output tokens
Qwen3.7 Max 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 K3.1 Pro | Qwen3.7 Max |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | October 23, 2026 | May 21, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $2.00 | $1.475 |
| Output $/Mtok | $10.00 | $4.425 |
| Coding index | 82.2 | 54.1 |
| Independent measurements behind it | 4 | 3 |
| Cost per solved task | Not computable | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K3.1 Pro better than Qwen3.7 Max for coding?
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 54.1 for Qwen3.7 Max. Pick Qwen3.7 Max for output tokens 2.3x cheaper ($4.425 vs $10.00 per million).
Which is cheaper, Kimi K3.1 Pro or Qwen3.7 Max?
Kimi K3.1 Pro costs $2.00 per million input tokens and $10.00 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, Kimi K3.1 Pro or Qwen3.7 Max?
Kimi K3.1 Pro, with 1.05M tokens against 1M.
How many benchmarks is the Kimi K3.1 Pro vs Qwen3.7 Max comparison based on?
18 benchmarks have a result for both models as of October 29, 2026. Kimi K3.1 Pro's coding index rests on 4 independent benchmarks and Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.