Kimi K2.7 Code vs Qwen2.5 VL 72B Instruct
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- 53.4
- Overall
- 25.8
- Output $/M
- $4.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.00
Decision reading
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; Qwen2.5 VL 72B Instruct has none, so the two cannot be ranked on coding.
Qwen2.5 VL 72B Instruct has the edge where output tokens cost 4.0x less.
- Shared results
- 0
- Kimi K2.7 Code only
- 51
- Qwen2.5 VL 72B Instruct only
- 5
- Like-for-like categories
- 0 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, six public coding benchmarks
No call
Only Kimi K2.7 Code has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Kimi K2.7 Code has a AA Intelligence Index result, 25.8.
Directional only
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
No call
Only Kimi K2.7 Code has a Design Arena: websites result, 1264.
Directional only
Long documents
Listed context window
Kimi K2.7 Code
Kimi K2.7 Code takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 VL 72B Instruct
Kimi K2.7 Code $0.0029, Qwen2.5 VL 72B Instruct $0.0013 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 53.4 from 4 benchmarks, Qwen2.5 VL 72B Instruct not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- Kimi K2.7 Code $4.00 against Qwen2.5 VL 72B Instruct $1.00 per million output tokens, 4.0x apart.
- Context window
- Kimi K2.7 Code takes 262K tokens, Qwen2.5 VL 72B Instruct 128K.
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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index17 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| LMArena WebDev | 1474 | Not measured | Only Kimi K2.7 Code measured |
| 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% | Not measured | Only Kimi K2.7 Code measured |
| 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 WebDev: React | 1475 | Not measured | Only Kimi K2.7 Code measured |
| LMArena WebDev: HTML | 1451 | Not measured | Only Kimi K2.7 Code measured |
| LMArena WebDev: from an image | 1513 | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.8 | Not measured | Only Kimi K2.7 Code measured |
| Epoch Capabilities Index | 150.1 | Not measured | Only Kimi K2.7 Code measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | 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 | 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 |
| τ²-Bench Telecom | 90.1% | Not measured | Only Kimi K2.7 Code measured |
| APEX-Agents | 37.6% | Not measured | Only Kimi K2.7 Code measured |
| OSWorld | Not measured | 5.0% | Only Qwen2.5 VL 72B Instruct measured |
| Vending-Bench 2 | $5,083 | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 89.6% | Not measured | Only Kimi K2.7 Code measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | Not measured | Only Kimi K2.7 Code measured |
| GPQA Diamond (Epoch AI run) | 87.9% | Not measured | Only Kimi K2.7 Code measured |
| SimpleBench | 57.9% | Not measured | Only Kimi K2.7 Code measured |
| Chess puzzles | 14.0% | Not measured | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | 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 |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| SimpleQA Verified | 36.5% | Not measured | Only Kimi K2.7 Code measured |
| GeoBench | Not measured | 62.0% | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | 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 |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Kimi K2.7 Code | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| IFBench | 63.1% | Not measured | Only Kimi K2.7 Code measured |
| Long context reasoning (AA-LCR) | 79.3% | Not measured | Only Kimi K2.7 Code measured |
| Surface Evolver Bench | 48.8% | Not measured | Only Kimi K2.7 Code measured |
| LMArena Vision | Not measured | 1107 | Only Qwen2.5 VL 72B Instruct measured |
| LMArena Vision: English | Not measured | 1115 | Only Qwen2.5 VL 72B Instruct measured |
| LMArena Vision: Chinese | Not measured | 1107 | Only Qwen2.5 VL 72B Instruct 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 K2.7 Code | Qwen2.5 VL 72B Instruct | 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
Qwen2.5 VL 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 VL 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 VL 72B Instruct 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 | Qwen2.5 VL 72B Instruct |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | Open weights |
| Released | June 12, 2026 | February 1, 2025 |
| Context window | 262K | 128K |
| Input $/Mtok | $0.95 | $0.80 |
| Output $/Mtok | $4.00 | $1.00 |
| Coding index | 53.4 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $0.35 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2.7 Code better than Qwen2.5 VL 72B Instruct for coding?
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; Qwen2.5 VL 72B Instruct has none, so the two cannot be ranked on coding. Qwen2.5 VL 72B Instruct has the edge where output tokens cost 4.0x less.
Which is cheaper, Kimi K2.7 Code or Qwen2.5 VL 72B Instruct?
Kimi K2.7 Code costs $0.95 per million input tokens and $4.00 per million output tokens; Qwen2.5 VL 72B Instruct costs $0.80 and $1.00. Cost per solved task is known for Kimi K2.7 Code only.
Which has the bigger context window, Kimi K2.7 Code or Qwen2.5 VL 72B Instruct?
Kimi K2.7 Code, with 262K tokens against 128K.
How many benchmarks is the Kimi K2.7 Code vs Qwen2.5 VL 72B Instruct comparison based on?
0 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 Qwen2.5 VL 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.