Gemini 2.5 Pro vs Kimi K2.7 Code
Updated October 21, 2026. 28 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Kimi K2.7 Code for coding: it scores 39.1 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro, though on 1 benchmark against 2.
Pick Gemini 2.5 Pro when the context window is larger, 1.05M against 262K tokens.
- Shared results
- 28
- Gemini 2.5 Pro only
- 59
- Kimi K2.7 Code only
- 23
- Like-for-like categories
- 7 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, four public coding benchmarks
Kimi K2.7 Code
Kimi K2.7 Code scores 39.1 against 37.0.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 25.8 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 21.0 against 1.6.
Same board, both measured
Web design
Design Arena: websites
Kimi K2.7 Code
Kimi K2.7 Code leads, 1264 against 1167.
Same board, both measured
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.7 Code
Gemini 2.5 Pro $0.0063, Kimi K2.7 Code $0.0023 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
Gemini 2.5 Pro $0.64, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Pro 37.0 from 2 benchmarks, Kimi K2.7 Code 39.1 from 1 benchmark.
- Widest category
- Agentic work, 27.8 points apart on average over 3 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 2.5 Pro 0.4% against Kimi K2.7 Code 47.2%, 46.8 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against Kimi K2.7 Code $3.35 per million output tokens, 3.0x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, Kimi K2.7 Code 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 | Gemini 2.5 Pro | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 0 | 9 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 3 | ||
| Web design | 0 | 6 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 28 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index09
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | 1474 | Kimi K2.7 Code |
| AA Coding Index | 33.3 | 60.8 | Kimi K2.7 Code |
| LiveCodeBench (Vals AI) | Not measured | 82.0% | Only Kimi K2.7 Code measured |
| SWE-bench Verified (Vals AI) | 54.4% | 78.2% | Kimi K2.7 Code |
| Vibe Code Bench (Vals AI) | 0.4% | 47.2% | Kimi K2.7 Code |
| Code migration (Vals AI) | Not measured | 25.4% | Only Kimi K2.7 Code measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Kimi K2.7 Code measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.0% | Only Kimi K2.7 Code measured |
| SkillsBench (Vals AI) | Not measured | 50.0% | Only Kimi K2.7 Code measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 47.8% | Kimi K2.7 Code |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 44.7% | Kimi K2.7 Code |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierCode | Not measured | 30.1% | Only Kimi K2.7 Code measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | 54.1% | Kimi K2.7 Code |
| ALE-Bench | Not measured | 886.2 | Only Kimi K2.7 Code measured |
| LMArena Text: coding | 1452 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: software and IT | 1459 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev: React | Not measured | 1475 | Only Kimi K2.7 Code measured |
| LMArena WebDev: HTML | 1235 | 1451 | Kimi K2.7 Code |
| LMArena WebDev: from an image | 1285 | 1513 | Kimi K2.7 Code |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 25.8 | Kimi K2.7 Code |
| Epoch Capabilities Index | 145.1 | 150.1 | Kimi K2.7 Code |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 21.0 | Kimi K2.7 Code |
| Design Arena: agents building web apps | Not measured | 1176 | Only Kimi K2.7 Code measured |
| Design Arena: agents building full-stack apps | Not measured | 1175 | Only Kimi K2.7 Code measured |
| Design Arena: agents building mobile apps | Not measured | 1143 | Only Kimi K2.7 Code measured |
| Design Arena: agents building Android apps | Not measured | 1143 | Only Kimi K2.7 Code measured |
| Design Arena: agents building Godot games | Not measured | 1147 | Only Kimi K2.7 Code measured |
| Design Arena: agents building games | Not measured | 1130 | Only Kimi K2.7 Code measured |
| Design Arena: HTML slides | Not measured | 1201 | Only Kimi K2.7 Code measured |
| Design Arena: PowerPoint slides | Not measured | 1154 | Only Kimi K2.7 Code measured |
| τ²-Bench Telecom | 54.1% | 90.1% | Kimi K2.7 Code |
| APEX-Agents | Not measured | 37.6% | Only Kimi K2.7 Code measured |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | $5,083 | Kimi K2.7 Code |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.4% | 89.6% | Kimi K2.7 Code |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 35.0% | Kimi K2.7 Code |
| GPQA Diamond (Epoch AI run) | 85.3% | 87.9% | Kimi K2.7 Code |
| ARC-AGI | 41.0% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleBench | Not measured | 57.9% | Only Kimi K2.7 Code measured |
| Chess puzzles | Not measured | 14.0% | Only Kimi K2.7 Code measured |
| LMArena Text: hard prompts | 1455 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: expert | 1452 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: hard prompts in English | 1453 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: diagrams | 1274 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: homework | 1281 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | 95.6% | Kimi K2.7 Code |
| FrontierMath, tiers 1 to 3 | 24.6% | 54.0% | Kimi K2.7 Code |
| FrontierMath, tier 4 | 0.0% | 12.2% | Kimi K2.7 Code |
| LMArena Text: math | 1450 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: mathematical work | 1454 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | Not measured | Only Gemini 2.5 Pro measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedCode (Vals AI) | 50.6% | Not measured | Only Gemini 2.5 Pro measured |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleQA Verified | Not measured | 36.5% | Only Kimi K2.7 Code measured |
| LMArena Text: science | 1480 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: medicine and healthcare | 1476 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: legal and government | 1480 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: business and finance | 1439 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1264 | Kimi K2.7 Code |
| Design Arena: UI components | 1139 | 1259 | Kimi K2.7 Code |
| Design Arena: game dev | 1112 | 1220 | Kimi K2.7 Code |
| Design Arena: data viz | 1222 | 1226 | Kimi K2.7 Code |
| Design Arena: 3D | 1080 | 1241 | Kimi K2.7 Code |
| Design Arena: all code categories | 1152 | 1253 | Kimi K2.7 Code |
| Design Arena: SVG | Not measured | 1176 | Only Kimi K2.7 Code measured |
| Design Arena: ASCII art | Not measured | 1196 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedScribe (Vals AI) | 73.5% | Not measured | Only Gemini 2.5 Pro measured |
| IFBench | 48.7% | 63.1% | Kimi K2.7 Code |
| Long context reasoning (AA-LCR) | 69.0% | 79.3% | Kimi K2.7 Code |
| DTBench | 82.4% | Not measured | Only Gemini 2.5 Pro measured |
| LMCA | 34.8% | Not measured | Only Gemini 2.5 Pro measured |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code measured |
| LMArena Text | 1458 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: instruction following | 1437 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: creative writing | 1454 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision | 1263 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: English | 1458 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: non-English | 1452 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Chinese | 1507 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: German | 1487 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Japanese | 1461 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Korean | 1434 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: French | 1473 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Spanish | 1474 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Russian | 1461 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Polish | 1479 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: multi-turn | 1453 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: longer queries | 1449 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: writing and language | 1454 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: entertainment and media | 1441 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: English | 1261 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: Chinese | 1300 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | 1270 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: humor | 1262 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | 1265 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | Kimi K2.7 Code | 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
Kimi K2.7 Code costs less
Repository review
50K input + 3K output tokens
Kimi K2.7 Code costs less
Agent loop
200K input + 10K output tokens
Kimi K2.7 Code 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 | Google Gemini 2.5 Pro | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | Moonshot AI | |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | June 12, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.25 | $0.6712 |
| Output $/Mtok | $10.00 | $3.35 |
| Coding index | 37.0 | 39.1 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.64 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than Kimi K2.7 Code for coding?
Pick Kimi K2.7 Code for coding: it scores 39.1 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro, though on 1 benchmark against 2. Pick Gemini 2.5 Pro when the context window is larger, 1.05M against 262K tokens.
Which is cheaper, Gemini 2.5 Pro or Kimi K2.7 Code?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Kimi K2.7 Code costs $0.6712 and $3.35. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and Kimi K2.7 Code $0.35.
Which has the bigger context window, Gemini 2.5 Pro or Kimi K2.7 Code?
Gemini 2.5 Pro, with 1.05M tokens against 262K.
How many benchmarks is the Gemini 2.5 Pro vs Kimi K2.7 Code comparison based on?
28 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 2 independent benchmarks and Kimi K2.7 Code's on 1. Where only one model has a result, the page says so instead of naming a winner.