Kimi K2 0711 vs Qwen3 235B A22B Instruct 2507
Kimi K2 0711 leads Qwen3 235B A22B Instruct 2507 on the Artificial Analysis Intelligence Index, 12.7 to 12.0, and Qwen3 235B A22B Instruct 2507 costs 3.1x less per output token ($0.75 vs $2.30 per million). Updated October 22, 2026; 17 benchmarks have a result for both.
Kimi K2 0711 or Qwen3 235B A22B Instruct 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Kimi K2 0711 for work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 17
- Kimi K2 0711 only
- 20
- Qwen3 235B A22B Instruct 2507 only
- 7
- Like-for-like categories
- 8 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2 0711
Kimi K2 0711 leads, 12.7 against 12.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Kimi K2 0711 has a GPQA Diamond result, 71.5%.
Directional only
Math
AIME
No call
Only Kimi K2 0711 has a AIME result, 62.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 0711 has a MMLU Pro result, 79.4%.
Directional only
Web design
Design Arena: websites
Qwen3 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 leads, 1058 against 1050.
Same board, both measured
Long documents
Listed context window
Qwen3 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 235B A22B Instruct 2507
Kimi K2 0711 $0.0017, Qwen3 235B A22B Instruct 2507 $0.0005 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0711 not benchmarked, Qwen3 235B A22B Instruct 2507 not benchmarked.
- Widest category
- Math, 34.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): Kimi K2 0711 57.0% against Qwen3 235B A22B Instruct 2507 91.0%, 34.0 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0711 $2.30 against Qwen3 235B A22B Instruct 2507 $0.75 per million output tokens, 3.1x apart.
- Context window
- Kimi K2 0711 takes 131K tokens, Qwen3 235B A22B Instruct 2507 262K.
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 0711 | Bars | Qwen3 235B A22B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| Web design | 2 | 3 | ||
| General | 0 | 2 | ||
| All shared boards | 6 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| Aider polyglot | 59.1% | Not measured | Only Kimi K2 0711 measured |
| SWE-bench Verified | 71.2% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Vals AI) | 70.5% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Artificial Analysis run) | 55.6% | 78.8% | Qwen3 235B A22B Instruct 2507 |
| SciCode | Not measured | 41.4% | Only Qwen3 235B A22B Instruct 2507 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | 15.2% | Kimi K2 0711 |
| Terminal-Bench | 27.8% | Not measured | Only Kimi K2 0711 measured |
| GSO-Bench | 4.9% | Not measured | Only Kimi K2 0711 measured |
| WeirdML | 39.4% | 38.7% | Kimi K2 0711 |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | 12.0 | Kimi K2 0711 |
| Epoch Capabilities Index | 140.0 | Not measured | Only Kimi K2 0711 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 61.1% | 53.2% | Kimi K2 0711 |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 52.1% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond | 71.5% | Not measured | Only Kimi K2 0711 measured |
| GPQA Diamond (Artificial Analysis run) | 76.6% | 79.0% | Qwen3 235B A22B Instruct 2507 |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | 15.9% | Qwen3 235B A22B Instruct 2507 |
| ARC-AGI | Not measured | 11.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| ARC-AGI-2 | Not measured | 1.3% | Only Qwen3 235B A22B Instruct 2507 measured |
| SimpleBench | 26.3% | Not measured | Only Kimi K2 0711 measured |
| Kagi LLM Benchmark | 64.4% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AIME | 62.7% | Not measured | Only Kimi K2 0711 measured |
| MATH 500 (Vals AI) | 94.2% | Not measured | Only Kimi K2 0711 measured |
| MGSM (Vals AI) | 91.0% | Not measured | Only Kimi K2 0711 measured |
| AA Math Index | 57.0 | 91.0 | Qwen3 235B A22B Instruct 2507 |
| AIME 2025 (Artificial Analysis run) | 57.0% | 91.0% | Qwen3 235B A22B Instruct 2507 |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| MMLU Pro | 79.4% | Not measured | Only Kimi K2 0711 measured |
| LegalBench (Vals AI) | 81.5% | Not measured | Only Kimi K2 0711 measured |
| CorpFin (Vals AI) | 50.4% | Not measured | Only Kimi K2 0711 measured |
| TaxEval (Vals AI) | 70.2% | Not measured | Only Kimi K2 0711 measured |
| MedQA (Vals AI) | 84.0% | Not measured | Only Kimi K2 0711 measured |
| MMLU Pro (Artificial Analysis run) | 82.4% | 84.3% | Qwen3 235B A22B Instruct 2507 |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | 1050 | 1058 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: UI components | 1027 | 962 | Kimi K2 0711 |
| Design Arena: game dev | 973 | 951 | Kimi K2 0711 |
| Design Arena: data viz | 1018 | 1070 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: 3D | Not measured | 994 | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: all code categories | 1033 | 1038 | Qwen3 235B A22B Instruct 2507 |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| IFBench | 41.5% | 51.2% | Qwen3 235B A22B Instruct 2507 |
| Long context reasoning (AA-LCR) | 53.0% | 72.0% | Qwen3 235B A22B Instruct 2507 |
| DTBench | Not measured | 78.4% | Only Qwen3 235B A22B Instruct 2507 measured |
| LMCA | Not measured | 23.5% | Only Qwen3 235B A22B Instruct 2507 measured |
| Fiction.LiveBench | 61.1% | Not measured | Only Kimi K2 0711 measured |
| Creative writing (Lech Mazur) | 85.6% | Not measured | Only Kimi K2 0711 measured |
| CL-bench | 11.9% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 39 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2 0711 | Qwen3 235B A22B Instruct 2507 | 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 235B A22B Instruct 2507 costs less
Repository review
50K input + 3K output tokens
Qwen3 235B A22B Instruct 2507 costs less
Agent loop
200K input + 10K output tokens
Qwen3 235B A22B Instruct 2507 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 0711 | Qwen3 235B A22B Instruct 2507 |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | Open weights |
| Released | July 11, 2025 | July 21, 2025 |
| Context window | 131K | 262K |
| Input $/Mtok | $0.57 | $0.15 |
| Output $/Mtok | $2.30 | $0.75 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2 0711 better than Qwen3 235B A22B Instruct 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Kimi K2 0711 for work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, Kimi K2 0711 or Qwen3 235B A22B Instruct 2507?
Kimi K2 0711 costs $0.57 per million input tokens and $2.30 per million output tokens; Qwen3 235B A22B Instruct 2507 costs $0.15 and $0.75. Cost per solved task is known for neither of them.
Which has the bigger context window, Kimi K2 0711 or Qwen3 235B A22B Instruct 2507?
Qwen3 235B A22B Instruct 2507, with 262K tokens against 131K.
How many benchmarks is the Kimi K2 0711 vs Qwen3 235B A22B Instruct 2507 comparison based on?
17 benchmarks have a result for both models as of October 22, 2026. Kimi K2 0711's coding index rests on 0 independent benchmarks and Qwen3 235B A22B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.