GPT-4.1 Mini vs Kimi K2.7 Code
Kimi K2.7 Code leads GPT-4.1 Mini on the Artificial Analysis Intelligence Index, 25.8 to 10.2, and GPT-4.1 Mini costs 2.5x less per output token ($1.60 vs $4.00 per million). Updated October 21, 2026; 22 benchmarks have a result for both.
GPT-4.1 Mini or Kimi K2.7 Code: which to pick
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GPT-4.1 Mini has none, so the two cannot be ranked on coding.
Pick GPT-4.1 Mini for output tokens 2.5x cheaper ($1.60 vs $4.00 per million) and a larger context window (1.05M against 262K tokens).
- Shared results
- 22
- GPT-4.1 Mini only
- 64
- Kimi K2.7 Code only
- 29
- 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
Only Kimi K2.7 Code has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 25.8 against 10.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Kimi K2.7 Code has a AA Agentic Index result, 21.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4.1 Mini has a GPQA Diamond result, 67.9%.
Directional only
Math
AIME
No call
Only GPT-4.1 Mini has a AIME result, 49.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 Mini has a MMLU Pro result, 77.2%.
Directional only
Web design
Design Arena: websites
Kimi K2.7 Code
Kimi K2.7 Code leads, 1264 against 997.
Same board, both measured
Long documents
Listed context window
GPT-4.1 Mini
GPT-4.1 Mini takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4.1 Mini
GPT-4.1 Mini $0.0012, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
GPT-4.1 Mini $1.818, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-4.1 Mini not benchmarked, Kimi K2.7 Code 53.4 from 4 benchmarks.
- Widest category
- Math, 49.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- OTIS Mock AIME: GPT-4.1 Mini 44.7% against Kimi K2.7 Code 95.6%, 50.8 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 Mini $1.60 against Kimi K2.7 Code $4.00 per million output tokens, 2.5x apart.
- Context window
- GPT-4.1 Mini 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 | GPT-4.1 Mini | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| Web design | 0 | 6 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Aider polyglot | 32.4% | Not measured | Only GPT-4.1 Mini measured |
| SWE-bench Verified | 23.9% | Not measured | Only GPT-4.1 Mini measured |
| LMArena WebDev | Not measured | 1474 | Only Kimi K2.7 Code measured |
| AA Coding Index | 20.2 | 60.8 | Kimi K2.7 Code |
| LiveCodeBench (Vals AI) | 58.2% | 82.0% | Kimi K2.7 Code |
| SWE-bench Verified (Vals AI) | Not measured | 78.2% | Only Kimi K2.7 Code measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.2% | Only Kimi K2.7 Code measured |
| 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) | 48.3% | Not measured | Only GPT-4.1 Mini measured |
| SciCode | Not measured | 47.8% | Only Kimi K2.7 Code measured |
| Terminal-Bench Hard (Artificial Analysis run) | 7.6% | 44.7% | Kimi K2.7 Code |
| FrontierCode | Not measured | 30.1% | Only Kimi K2.7 Code measured |
| WeirdML | 37.6% | 54.1% | Kimi K2.7 Code |
| ALE-Bench | Not measured | 886.2 | Only Kimi K2.7 Code measured |
| LMArena Text: coding | 1367 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: software and IT | 1360 | Not measured | Only GPT-4.1 Mini measured |
| LMArena WebDev: React | Not measured | 1475 | Only Kimi K2.7 Code measured |
| LMArena WebDev: HTML | Not measured | 1451 | Only Kimi K2.7 Code measured |
| LMArena WebDev: from an image | Not measured | 1513 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.2 | 25.8 | Kimi K2.7 Code |
| Epoch Capabilities Index | 134.9 | 150.1 | Kimi K2.7 Code |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.0 | Only Kimi K2.7 Code measured |
| 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 | 1137 | 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 | 1131 | 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 | 52.9% | 90.1% | Kimi K2.7 Code |
| APEX-Agents | Not measured | 37.6% | Only Kimi K2.7 Code measured |
| Vending-Bench 2 | Not measured | $5,083 | Only Kimi K2.7 Code measured |
| Berkeley Function Calling Leaderboard (BFCL) | 50.4% | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond | 67.9% | Not measured | Only GPT-4.1 Mini measured |
| MMMU Pro (Vals AI) | 70.5% | Not measured | Only GPT-4.1 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 66.4% | 89.6% | Kimi K2.7 Code |
| Humanity's Last Exam (Artificial Analysis run) | 5.0% | 35.0% | Kimi K2.7 Code |
| GPQA Diamond (Epoch AI run) | 65.8% | 87.9% | Kimi K2.7 Code |
| ARC-AGI | 3.5% | Not measured | Only GPT-4.1 Mini measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4.1 Mini measured |
| SimpleBench | Not measured | 57.9% | Only Kimi K2.7 Code measured |
| Chess puzzles | 1.0% | 14.0% | Kimi K2.7 Code |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: hard prompts | 1349 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: expert | 1338 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: hard prompts in English | 1362 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: diagrams | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: homework | 1214 | Not measured | Only GPT-4.1 Mini measured |
| Kagi LLM Benchmark | 48.6% | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AIME | 49.4% | Not measured | Only GPT-4.1 Mini measured |
| MATH 500 (Vals AI) | 88.0% | Not measured | Only GPT-4.1 Mini measured |
| MGSM (Vals AI) | 87.8% | Not measured | Only GPT-4.1 Mini measured |
| AA Math Index | 46.3 | Not measured | Only GPT-4.1 Mini measured |
| AIME 2025 (Artificial Analysis run) | 46.3% | Not measured | Only GPT-4.1 Mini measured |
| OTIS Mock AIME | 44.7% | 95.6% | Kimi K2.7 Code |
| FrontierMath, tiers 1 to 3 | 6.7% | 54.0% | Kimi K2.7 Code |
| FrontierMath, tier 4 | Not measured | 12.2% | Only Kimi K2.7 Code measured |
| MATH level 5 | 87.3% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: math | 1343 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: mathematical work | 1347 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-4.1 Mini measured |
| LegalBench (Vals AI) | 78.0% | Not measured | Only GPT-4.1 Mini measured |
| CorpFin (Vals AI) | 57.9% | Not measured | Only GPT-4.1 Mini measured |
| TaxEval (Vals AI) | 71.9% | Not measured | Only GPT-4.1 Mini measured |
| MortgageTax (Vals AI) | 65.5% | Not measured | Only GPT-4.1 Mini measured |
| MedQA (Vals AI) | 84.6% | Not measured | Only GPT-4.1 Mini measured |
| MMLU Pro (Artificial Analysis run) | 78.1% | Not measured | Only GPT-4.1 Mini measured |
| SimpleQA Verified | 12.7% | 36.5% | Kimi K2.7 Code |
| LMArena Text: science | 1328 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: medicine and healthcare | 1324 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: legal and government | 1343 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: business and finance | 1322 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | 997 | 1264 | Kimi K2.7 Code |
| Design Arena: UI components | 961 | 1259 | Kimi K2.7 Code |
| Design Arena: game dev | 1071 | 1220 | Kimi K2.7 Code |
| Design Arena: data viz | 1034 | 1227 | Kimi K2.7 Code |
| Design Arena: 3D | 837 | 1241 | Kimi K2.7 Code |
| Design Arena: all code categories | 994 | 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 | GPT-4.1 Mini | Kimi K2.7 Code | Leader |
|---|---|---|---|
| IFBench | 38.3% | 63.1% | Kimi K2.7 Code |
| Long context reasoning (AA-LCR) | 44.0% | 79.3% | Kimi K2.7 Code |
| DTBench | 68.8% | Not measured | Only GPT-4.1 Mini measured |
| LMCA | 21.1% | Not measured | Only GPT-4.1 Mini measured |
| Fiction.LiveBench | 44.4% | Not measured | Only GPT-4.1 Mini measured |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code measured |
| LMArena Text | 1341 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: instruction following | 1333 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: creative writing | 1299 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision | 1181 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: English | 1356 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: non-English | 1318 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Chinese | 1329 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: German | 1350 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Japanese | 1290 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Korean | 1298 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: French | 1358 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Spanish | 1319 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Russian | 1324 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Polish | 1326 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: multi-turn | 1354 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: longer queries | 1344 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: writing and language | 1319 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: entertainment and media | 1300 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: English | 1191 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: Chinese | 1186 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: reading text | 1188 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: humor | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: captioning | 1174 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: recognizing things | 1187 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: creative writing | 1182 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 Mini | 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
GPT-4.1 Mini costs less
Repository review
50K input + 3K output tokens
GPT-4.1 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-4.1 Mini 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 | OpenAI GPT-4.1 Mini | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | April 14, 2025 | June 12, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.40 | $0.95 |
| Output $/Mtok | $1.60 | $4.00 |
| Coding index | Not benchmarked | 53.4 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | $1.818 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 Mini better than Kimi K2.7 Code for coding?
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GPT-4.1 Mini has none, so the two cannot be ranked on coding. Pick GPT-4.1 Mini for output tokens 2.5x cheaper ($1.60 vs $4.00 per million) and a larger context window (1.05M against 262K tokens).
Which is cheaper, GPT-4.1 Mini or Kimi K2.7 Code?
GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Per solved SWE-bench Verified task, GPT-4.1 Mini costs $1.818 and Kimi K2.7 Code $0.35.
Which has the bigger context window, GPT-4.1 Mini or Kimi K2.7 Code?
GPT-4.1 Mini, with 1.05M tokens against 262K.
How many benchmarks is the GPT-4.1 Mini vs Kimi K2.7 Code comparison based on?
22 benchmarks have a result for both models as of October 21, 2026. GPT-4.1 Mini's coding index rests on 0 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.