Kimi K2 0905 vs Qwen3.6 27B
Qwen3.6 27B leads Kimi K2 0905 on the Artificial Analysis Intelligence Index, 21.4 to 15.3, at about the same output price ($2.70 vs $2.50 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
Kimi K2 0905 or Qwen3.6 27B: which to pick
Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Kimi K2 0905 has none, so the two cannot be ranked on coding.
Pick Kimi K2 0905 for output tokens 1.1x cheaper ($2.50 vs $2.70 per million).
- Shared results
- 7
- Kimi K2 0905 only
- 10
- Qwen3.6 27B only
- 17
- 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
No call
Only Qwen3.6 27B has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.6 27B
Qwen3.6 27B leads, 21.4 against 15.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.6 27B has a AA Agentic Index result, 18.5.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 0905 has a Design Arena: websites result, 1088.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 27B
Kimi K2 0905 $0.0019, Qwen3.6 27B $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.6 27B has the number, $1.30.
Directional only
At a glance
- Coding index
- Kimi K2 0905 not benchmarked, Qwen3.6 27B 36.8 from 2 benchmarks.
- Widest category
- General, 25.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- IFBench: Kimi K2 0905 41.7% against Qwen3.6 27B 67.6%, 25.9 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0905 $2.50 against Qwen3.6 27B $2.70 per million output tokens, 1.1x 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 0905 | Bars | Qwen3.6 27B | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Kimi K2 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 53.7 | Only Qwen3.6 27B measured |
| SWE-bench Verified (Vals AI) | Not measured | 70.0% | Only Qwen3.6 27B measured |
| Vibe Code Bench (Vals AI) | Not measured | 11.9% | Only Qwen3.6 27B measured |
| LiveCodeBench (Artificial Analysis run) | 61.0% | Not measured | Only Kimi K2 0905 measured |
| SciCode | Not measured | 42.8% | Only Qwen3.6 27B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | 34.8% | Qwen3.6 27B |
| WeirdML | 36.7% | Not measured | Only Kimi K2 0905 measured |
| ALE-Bench | 267.1 | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Kimi K2 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.3 | 21.4 | Qwen3.6 27B |
| Epoch Capabilities Index | Not measured | 146.2 | Only Qwen3.6 27B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Kimi K2 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 18.5 | Only Qwen3.6 27B measured |
| τ²-Bench Telecom | 73.4% | 94.2% | Qwen3.6 27B |
| 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 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 76.7% | 84.2% | Qwen3.6 27B |
| Humanity's Last Exam (Artificial Analysis run) | 6.4% | 23.1% | Qwen3.6 27B |
| GPQA Diamond (Epoch AI run) | Not measured | 85.9% | Only Qwen3.6 27B measured |
| Mystery game puzzles | Not measured | 7.0% | Only Qwen3.6 27B measured |
| Kagi LLM Benchmark | 52.2% | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Kimi K2 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Math Index | 57.3 | Not measured | Only Kimi K2 0905 measured |
| AIME 2025 (Artificial Analysis run) | 57.3% | Not measured | Only Kimi K2 0905 measured |
| OTIS Mock AIME | Not measured | 91.1% | Only Qwen3.6 27B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 35.1% | Only Qwen3.6 27B measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Kimi K2 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | Not measured | 53.2% | Only Qwen3.6 27B measured |
| CorpFin (Vals AI) | Not measured | 62.3% | Only Qwen3.6 27B measured |
| TaxEval (Vals AI) | Not measured | 71.3% | Only Qwen3.6 27B measured |
| MortgageTax (Vals AI) | Not measured | 68.3% | Only Qwen3.6 27B measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K2 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| Design Arena: websites | 1088 | Not measured | Only Kimi K2 0905 measured |
| Design Arena: all code categories | 1098 | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 7 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Kimi K2 0905 | Qwen3.6 27B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 45.6% | Only Qwen3.6 27B measured |
| IFBench | 41.7% | 67.6% | Qwen3.6 27B |
| Long context reasoning (AA-LCR) | 53.0% | 77.3% | Qwen3.6 27B |
| DTBench | Not measured | 78.1% | Only Qwen3.6 27B measured |
| LMCA | Not measured | 34.5% | Only Qwen3.6 27B measured |
| Fiction.LiveBench | 66.7% | Not measured | Only Kimi K2 0905 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 K2 0905 | Qwen3.6 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
Qwen3.6 27B costs less
Repository review
50K input + 3K output tokens
Qwen3.6 27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 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 0905 | Qwen3.6 27B |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | Open weights |
| Released | September 4, 2025 | April 27, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.60 | $0.45 |
| Output $/Mtok | $2.50 | $2.70 |
| Coding index | Not benchmarked | 36.8 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $1.30 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2 0905 better than Qwen3.6 27B for coding?
Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Kimi K2 0905 has none, so the two cannot be ranked on coding. Pick Kimi K2 0905 for output tokens 1.1x cheaper ($2.50 vs $2.70 per million).
Which is cheaper, Kimi K2 0905 or Qwen3.6 27B?
Kimi K2 0905 costs $0.60 per million input tokens and $2.50 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.
Which has the bigger context window, Kimi K2 0905 or Qwen3.6 27B?
Neither: both take 262K tokens.
How many benchmarks is the Kimi K2 0905 vs Qwen3.6 27B comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. Kimi K2 0905's coding index rests on 0 independent benchmarks and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.