GPT-4.1 vs Kimi K2 0905
Kimi K2 0905 leads GPT-4.1 on the Artificial Analysis Intelligence Index, 15.3 to 12.7, and Kimi K2 0905 costs 3.2x less per output token ($2.50 vs $8.00 per million). Updated October 22, 2026; 17 benchmarks have a result for both.
GPT-4.1 or Kimi K2 0905: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4.1 for a larger context window (1.05M against 262K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 17
- GPT-4.1 only
- 75
- Kimi K2 0905 only
- 0
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2 0905
Kimi K2 0905 leads, 15.3 against 12.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4.1 has a GPQA Diamond result, 65.4%.
Directional only
Math
AIME
No call
Only GPT-4.1 has a AIME result, 39.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 has a MMLU Pro result, 80.5%.
Directional only
Web design
Design Arena: websites
Kimi K2 0905
Kimi K2 0905 leads, 1088 against 1038.
Same board, both measured
Long documents
Listed context window
GPT-4.1
GPT-4.1 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2 0905
GPT-4.1 $0.0060, Kimi K2 0905 $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-4.1 has the number, $0.37.
Directional only
At a glance
- Coding index
- GPT-4.1 not benchmarked, Kimi K2 0905 not benchmarked.
- Widest category
- Agentic work, 26.3 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GPT-4.1 47.1% against Kimi K2 0905 73.4%, 26.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 $8.00 against Kimi K2 0905 $2.50 per million output tokens, 3.2x apart.
- Context window
- GPT-4.1 takes 1.05M tokens, Kimi K2 0905 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 | Bars | Kimi K2 0905 | Ties |
|---|---|---|---|---|
| Coding | 2 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 2 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| Web design | 0 | 2 | ||
| General | 2 | 1 | ||
| All shared boards | 5 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index22
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| Aider polyglot | 52.4% | Not measured | Only GPT-4.1 measured |
| SWE-bench Verified | 39.6% | Not measured | Only GPT-4.1 measured |
| SWE-bench Multimodal | 31.1% | Not measured | Only GPT-4.1 measured |
| LiveCodeBench (Vals AI) | 54.7% | Not measured | Only GPT-4.1 measured |
| LiveCodeBench (Artificial Analysis run) | 45.7% | 61.0% | Kimi K2 0905 |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | 23.5% | Kimi K2 0905 |
| WeirdML | 39.0% | 36.7% | GPT-4.1 |
| ALE-Bench | 558.1 | 267.1 | GPT-4.1 |
| LMArena Text: coding | 1390 | Not measured | Only GPT-4.1 measured |
| LMArena Text: software and IT | 1391 | Not measured | Only GPT-4.1 measured |
| SciCode | 4.6% | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | 15.3 | Kimi K2 0905 |
| Epoch Capabilities Index | 136.7 | Not measured | Only GPT-4.1 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 47.1% | 73.4% | Kimi K2 0905 |
| Berkeley Function Calling Leaderboard (BFCL) | 54.0% | Not measured | Only GPT-4.1 measured |
| BrowseComp-Plus | 36.4% | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| GPQA Diamond | 65.4% | Not measured | Only GPT-4.1 measured |
| MMMU Pro (Vals AI) | 72.4% | Not measured | Only GPT-4.1 measured |
| GPQA Diamond (Artificial Analysis run) | 66.6% | 76.7% | Kimi K2 0905 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 6.4% | Kimi K2 0905 |
| GPQA Diamond (Epoch AI run) | 66.9% | Not measured | Only GPT-4.1 measured |
| ARC-AGI | 5.5% | Not measured | Only GPT-4.1 measured |
| ARC-AGI-2 | 0.4% | Not measured | Only GPT-4.1 measured |
| SimpleBench | 27.0% | Not measured | Only GPT-4.1 measured |
| Chess puzzles | 3.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: hard prompts | 1384 | Not measured | Only GPT-4.1 measured |
| LMArena Text: expert | 1364 | Not measured | Only GPT-4.1 measured |
| LMArena Text: hard prompts in English | 1393 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: diagrams | 1215 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: homework | 1248 | Not measured | Only GPT-4.1 measured |
| Kagi LLM Benchmark | 52.3% | 52.2% | GPT-4.1 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| AIME | 39.6% | Not measured | Only GPT-4.1 measured |
| MATH 500 (Vals AI) | 87.2% | Not measured | Only GPT-4.1 measured |
| MGSM (Vals AI) | 87.7% | Not measured | Only GPT-4.1 measured |
| AA Math Index | 34.7 | 57.3 | Kimi K2 0905 |
| AIME 2025 (Artificial Analysis run) | 34.7% | 57.3% | Kimi K2 0905 |
| OTIS Mock AIME | 38.3% | Not measured | Only GPT-4.1 measured |
| FrontierMath, tiers 1 to 3 | 6.0% | Not measured | Only GPT-4.1 measured |
| MATH level 5 | 83.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: math | 1369 | Not measured | Only GPT-4.1 measured |
| LMArena Text: mathematical work | 1360 | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| MMLU Pro | 80.5% | Not measured | Only GPT-4.1 measured |
| LegalBench (Vals AI) | 83.1% | Not measured | Only GPT-4.1 measured |
| CaseLaw (Vals AI) | 69.9% | Not measured | Only GPT-4.1 measured |
| CorpFin (Vals AI) | 63.0% | Not measured | Only GPT-4.1 measured |
| TaxEval (Vals AI) | 75.1% | Not measured | Only GPT-4.1 measured |
| MortgageTax (Vals AI) | 65.9% | Not measured | Only GPT-4.1 measured |
| MedQA (Vals AI) | 91.2% | Not measured | Only GPT-4.1 measured |
| MMLU Pro (Artificial Analysis run) | 80.6% | 81.9% | Kimi K2 0905 |
| SimpleQA Verified | 31.1% | Not measured | Only GPT-4.1 measured |
| GeoBench | 72.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: science | 1382 | Not measured | Only GPT-4.1 measured |
| LMArena Text: medicine and healthcare | 1379 | Not measured | Only GPT-4.1 measured |
| LMArena Text: legal and government | 1399 | Not measured | Only GPT-4.1 measured |
| LMArena Text: business and finance | 1369 | Not measured | Only GPT-4.1 measured |
| FACTS Benchmark Suite | 45.8% | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| Design Arena: websites | 1038 | 1088 | Kimi K2 0905 |
| Design Arena: UI components | 997 | Not measured | Only GPT-4.1 measured |
| Design Arena: game dev | 1079 | Not measured | Only GPT-4.1 measured |
| Design Arena: data viz | 1104 | Not measured | Only GPT-4.1 measured |
| Design Arena: 3D | 849 | Not measured | Only GPT-4.1 measured |
| Design Arena: all code categories | 1025 | 1098 | Kimi K2 0905 |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | GPT-4.1 | Kimi K2 0905 | Leader |
|---|---|---|---|
| IFBench | 43.0% | 41.7% | GPT-4.1 |
| Long context reasoning (AA-LCR) | 68.3% | 53.0% | GPT-4.1 |
| DTBench | 68.3% | Not measured | Only GPT-4.1 measured |
| LMCA | 25.6% | Not measured | Only GPT-4.1 measured |
| Fiction.LiveBench | 63.9% | 66.7% | Kimi K2 0905 |
| LMArena Text | 1383 | Not measured | Only GPT-4.1 measured |
| LMArena Text: instruction following | 1367 | Not measured | Only GPT-4.1 measured |
| LMArena Text: creative writing | 1363 | Not measured | Only GPT-4.1 measured |
| LMArena Vision | 1210 | Not measured | Only GPT-4.1 measured |
| LMArena Text: English | 1392 | Not measured | Only GPT-4.1 measured |
| LMArena Text: non-English | 1370 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Chinese | 1382 | Not measured | Only GPT-4.1 measured |
| LMArena Text: German | 1381 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Japanese | 1319 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Korean | 1338 | Not measured | Only GPT-4.1 measured |
| LMArena Text: French | 1382 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Spanish | 1376 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Russian | 1377 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Polish | 1389 | Not measured | Only GPT-4.1 measured |
| LMArena Text: multi-turn | 1397 | Not measured | Only GPT-4.1 measured |
| LMArena Text: longer queries | 1385 | Not measured | Only GPT-4.1 measured |
| LMArena Text: writing and language | 1371 | Not measured | Only GPT-4.1 measured |
| LMArena Text: entertainment and media | 1365 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: English | 1209 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: Chinese | 1226 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: reading text | 1218 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: humor | 1196 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: captioning | 1207 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: recognizing things | 1208 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: creative writing | 1210 | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 | Kimi K2 0905 | 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 0905 costs less
Repository review
50K input + 3K output tokens
Kimi K2 0905 costs less
Agent loop
200K input + 10K output tokens
Kimi K2 0905 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 | MoonshotAI Kimi K2 0905 |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | April 14, 2025 | September 4, 2025 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $2.00 | $0.60 |
| Output $/Mtok | $8.00 | $2.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | $0.37 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 better than Kimi K2 0905 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 for a larger context window (1.05M against 262K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4.1 or Kimi K2 0905?
GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; Kimi K2 0905 costs $0.60 and $2.50. Cost per solved task is known for GPT-4.1 only.
Which has the bigger context window, GPT-4.1 or Kimi K2 0905?
GPT-4.1, with 1.05M tokens against 262K.
How many benchmarks is the GPT-4.1 vs Kimi K2 0905 comparison based on?
17 benchmarks have a result for both models as of October 22, 2026. GPT-4.1's coding index rests on 0 independent benchmarks and Kimi K2 0905's on 0. Where only one model has a result, the page says so instead of naming a winner.