Gemini 3.1 Pro Preview vs Kimi K2.7 Code
Kimi K2.7 Code leads Gemini 3.1 Pro Preview on coding, 53.4 to 32.3 on the Vibe Coding Index, and Kimi K2.7 Code costs 3.0x less per output token ($4.00 vs $12.00 per million). Updated October 22, 2026; 47 benchmarks have a result for both.
vs boards won of 47 shared, 1 tied
Gemini 3.1 Pro Preview or Kimi K2.7 Code: which to pick
Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 32.3 for Gemini 3.1 Pro Preview.
Pick Gemini 3.1 Pro Preview for a larger context window (1.05M against 262K tokens) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.
Model AGemini 3.1 Pro PreviewGoogle32.3/1004 independent benchmarks$0.99 per solved taskModel BKimi K2.7 CodeMoonshot AI53.4/1004 independent benchmarks$0.35 per solved task
- Shared results
- 47
- Gemini 3.1 Pro Preview only
- 86
- Kimi K2.7 Code only
- 4
- 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
Kimi K2.7 Code
Kimi K2.7 Code scores 53.4 against 32.3.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview leads, 29.7 against 25.8.
Same board, both measured
Agentic work
AA Agentic Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 21.0 against 8.2.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 3.1 Pro Preview has a GPQA Diamond result, 95.5%.
Directional only
Math
AIME
No call
Only Gemini 3.1 Pro Preview has a AIME result, 98.1%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.1 Pro Preview has a MMLU Pro result, 91.0%.
Directional only
Web design
Design Arena: websites
Kimi K2.7 Code
Kimi K2.7 Code leads, 1263 against 1233.
Same board, both measured
Long documents
Listed context window
Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.7 Code
Gemini 3.1 Pro Preview $0.0080, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
Gemini 3.1 Pro Preview $0.99, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3.1 Pro Preview 32.3 from 4 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
- Widest category
- Knowledge, 37.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Chess puzzles: Gemini 3.1 Pro Preview 51.0% against Kimi K2.7 Code 14.0%, 37.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.1 Pro Preview $12.00 against Kimi K2.7 Code $4.00 per million output tokens, 3.0x apart.
- Context window
- Gemini 3.1 Pro Preview 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 3.1 Pro Preview | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 9 | 5 | 1 tie | |
| Intelligence | 1 | 0 | ||
| Agentic work | 2 | 10 | ||
| Reasoning | 5 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 2 | 6 | ||
| General | 2 | 0 | ||
| All shared boards | 25 | 21 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index95
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| LMArena WebDev | 1447 | 1474 | Kimi K2.7 Code |
| AA Coding Index | 68.8 | 60.8 | Gemini 3.1 Pro Preview |
| LiveCodeBench (Vals AI) | 88.5% | 82.0% | Gemini 3.1 Pro Preview |
| SWE-bench Verified (Vals AI) | 78.8% | 78.2% | Gemini 3.1 Pro Preview |
| Terminal-Bench 4 (Vals AI) | 2.5% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Vibe Code Bench (Vals AI) | 32.0% | 47.2% | Kimi K2.7 Code |
| Code migration (Vals AI) | 17.3% | 25.4% | Kimi K2.7 Code |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | 51.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Terminal-Bench 2.1 (Vals AI) | 70.8% | 67.0% | Gemini 3.1 Pro Preview |
| Vibe Code Bench 1-100 (Vals AI) | 6.7% | Not measured | Only Gemini 3.1 Pro Preview measured |
| SkillsBench (Vals AI) | Not measured | 50.0% | Only Kimi K2.7 Code measured |
| SciCode | 58.7% | 47.8% | Gemini 3.1 Pro Preview |
| Terminal-Bench Hard (Artificial Analysis run) | 53.8% | 44.7% | Gemini 3.1 Pro Preview |
| Terminal-Bench | 80.2% | Not measured | Only Gemini 3.1 Pro Preview measured |
| FrontierCode | Not measured | 30.1% | Only Kimi K2.7 Code measured |
| GSO-Bench | 22.6% | Not measured | Only Gemini 3.1 Pro Preview measured |
| WeirdML | 72.1% | 54.1% | Gemini 3.1 Pro Preview |
| MirrorCode | 8.9% | Not measured | Only Gemini 3.1 Pro Preview measured |
| ALE-Bench | 1160.6 | 886.2 | Gemini 3.1 Pro Preview |
| LMArena Text: coding | 1484 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: software and IT | 1487 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena WebDev: React | 1438 | 1475 | Kimi K2.7 Code |
| LMArena WebDev: HTML | 1490 | 1451 | Gemini 3.1 Pro Preview |
| LMArena WebDev: from an image | 1481 | 1513 | Kimi K2.7 Code |
| SciCode | 14.3% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 29.7 | 25.8 | Gemini 3.1 Pro Preview |
| Epoch Capabilities Index | Not measured | 150.1 | Only Kimi K2.7 Code measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index210
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | 8.2 | 21.0 | Kimi K2.7 Code |
| Design Arena: agents building web apps | 1125 | 1176 | Kimi K2.7 Code |
| Design Arena: agents building full-stack apps | 1068 | 1175 | Kimi K2.7 Code |
| Design Arena: agents building mobile apps | 1094 | 1143 | Kimi K2.7 Code |
| Design Arena: agents building Android apps | 1049 | 1138 | Kimi K2.7 Code |
| Design Arena: agents building Godot games | 1236 | 1147 | Gemini 3.1 Pro Preview |
| Design Arena: agents building games | 1113 | 1130 | Kimi K2.7 Code |
| Design Arena: HTML slides | 1103 | 1151 | Kimi K2.7 Code |
| Design Arena: PowerPoint slides | 1041 | 1129 | Kimi K2.7 Code |
| SREBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Finance Agent (Vals AI) | 43.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Tax Agent Bench (Vals AI) | 9.3% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Legal Research Bench (Vals AI) | 20.7% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Excel Modeling Benchmark (Vals AI) | 52.6% | Not measured | Only Gemini 3.1 Pro Preview measured |
| BioMysteryBench (Vals AI) | 60.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Terminal-Bench-Science (Vals AI) | 1.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Vals Science Index | 27.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| τ²-Bench Telecom | 95.6% | 90.1% | Gemini 3.1 Pro Preview |
| APEX-Agents | 35.1% | 37.6% | Kimi K2.7 Code |
| METR time horizons | 77.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| BALROG | 57.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| DeepResearch Bench | 47.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| PostTrainBench | 22.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Vending-Bench 2 | $911 | $5,083 | Kimi K2.7 Code |
| Neither model has a result on the other 17 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond | 95.5% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MysteryMechanism (Vals AI) | 20.7% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MMMU Pro (Vals AI) | 88.2% | Not measured | Only Gemini 3.1 Pro Preview measured |
| GPQA Diamond (Artificial Analysis run) | 94.1% | 89.6% | Gemini 3.1 Pro Preview |
| Humanity's Last Exam (Artificial Analysis run) | 47.0% | 35.0% | Gemini 3.1 Pro Preview |
| GPQA Diamond (Epoch AI run) | 94.4% | 87.9% | Gemini 3.1 Pro Preview |
| ARC-AGI | 98.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| ARC-AGI-2 | 77.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| SimpleBench | 79.6% | 57.9% | Gemini 3.1 Pro Preview |
| Chess puzzles | 51.0% | 14.0% | Gemini 3.1 Pro Preview |
| Mystery game puzzles | 34.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| EBR-bench | 14.3% | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: hard prompts | 1485 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: expert | 1483 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: hard prompts in English | 1480 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: diagrams | 1311 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: homework | 1316 | Not measured | Only Gemini 3.1 Pro Preview measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AIME | 98.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| OTIS Mock AIME | 95.6% | 95.6% | Gemini 3.1 Pro Preview |
| FrontierMath, tiers 1 to 3 | 59.6% | 54.0% | Gemini 3.1 Pro Preview |
| FrontierMath, tier 4 | 26.8% | 12.2% | Gemini 3.1 Pro Preview |
| ProofBench | 26.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: math | 1486 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: mathematical work | 1478 | Not measured | Only Gemini 3.1 Pro Preview measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| MMLU Pro | 91.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| LegalBench (Vals AI) | 87.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| CaseLaw (Vals AI) | 64.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| CorpFin (Vals AI) | 64.5% | Not measured | Only Gemini 3.1 Pro Preview measured |
| TaxEval (Vals AI) | 72.9% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MortgageTax (Vals AI) | 69.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MedQA (Vals AI) | 96.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MedCode (Vals AI) | 59.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| SimpleQA Verified | 73.5% | 36.5% | Gemini 3.1 Pro Preview |
| LMArena Text: science | 1497 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: medicine and healthcare | 1486 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: legal and government | 1487 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: business and finance | 1459 | Not measured | Only Gemini 3.1 Pro Preview measured |
| FACTS Benchmark Suite | 67.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index26
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | 1233 | 1263 | Kimi K2.7 Code |
| Design Arena: UI components | 1224 | 1255 | Kimi K2.7 Code |
| Design Arena: game dev | 1202 | 1220 | Kimi K2.7 Code |
| Design Arena: data viz | 1209 | 1227 | Kimi K2.7 Code |
| Design Arena: 3D | 1234 | 1240 | Kimi K2.7 Code |
| Design Arena: all code categories | 1231 | 1252 | Kimi K2.7 Code |
| Design Arena: SVG | 1285 | 1176 | Gemini 3.1 Pro Preview |
| Design Arena: ASCII art | 1270 | 1196 | Gemini 3.1 Pro Preview |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 53.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| SAGE (Vals AI) | 48.7% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MedScribe (Vals AI) | 76.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Vals Multimodal Index | 56.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| IFBench | 77.1% | 63.1% | Gemini 3.1 Pro Preview |
| Long context reasoning (AA-LCR) | 82.0% | 79.3% | Gemini 3.1 Pro Preview |
| DTBench | 97.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMCA | 53.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| CL-bench | 20.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code measured |
| Furniture assembly | 26.7% | Not measured | Only Gemini 3.1 Pro Preview measured |
| ExploitBench | 26.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| CL-bench Life | 16.9% | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text | 1480 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: instruction following | 1466 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: creative writing | 1482 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision | 1296 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: English | 1478 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: non-English | 1476 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: Chinese | 1527 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: German | 1490 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: Japanese | 1491 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: Korean | 1455 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: French | 1487 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: Spanish | 1481 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: Russian | 1497 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: Polish | 1498 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: multi-turn | 1487 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: longer queries | 1482 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: writing and language | 1481 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Text: entertainment and media | 1465 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: English | 1287 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: Chinese | 1364 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: reading text | 1304 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: humor | 1322 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: captioning | 1345 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: recognizing things | 1330 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: creative writing | 1324 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Document | 1444 | Not measured | Only Gemini 3.1 Pro Preview measured |
| Neither model has a result on the other 7 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.1 Pro Preview | 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
Gemini 3.1 Pro Preview$0.0080Fits in one request
Kimi K2.7 Code$0.0029Fits in one request
Kimi K2.7 Code costs less
Repository review
50K input + 3K output tokens
Gemini 3.1 Pro Preview$0.136Fits in one request
Kimi K2.7 Code$0.059Fits in one request
Kimi K2.7 Code costs less
Agent loop
200K input + 10K output tokens
Gemini 3.1 Pro Preview$0.520Fits in one request
Kimi K2.7 Code$0.230Fits in one request
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 3.1 Pro Preview | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | Moonshot AI | |
| Weights | No public weights listed | Open weights |
| Released | February 19, 2026 | June 12, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $2.00 | $0.95 |
| Output $/Mtok | $12.00 | $4.00 |
| Coding index | 32.3 | 53.4 |
| Independent measurements behind it | 4 | 4 |
| Cost per solved task | $0.99 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.1 Pro Preview better than Kimi K2.7 Code for coding?
Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 32.3 for Gemini 3.1 Pro Preview. Pick Gemini 3.1 Pro Preview for a larger context window (1.05M against 262K tokens) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.
Which is cheaper, Gemini 3.1 Pro Preview or Kimi K2.7 Code?
Gemini 3.1 Pro Preview costs $2.00 per million input tokens and $12.00 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Per solved SWE-bench Verified task, Gemini 3.1 Pro Preview costs $0.99 and Kimi K2.7 Code $0.35.
Which has the bigger context window, Gemini 3.1 Pro Preview or Kimi K2.7 Code?
Gemini 3.1 Pro Preview, with 1.05M tokens against 262K.
How many benchmarks is the Gemini 3.1 Pro Preview vs Kimi K2.7 Code comparison based on?
47 benchmarks have a result for both models as of October 22, 2026. Gemini 3.1 Pro Preview's coding index rests on 4 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.