GPT-5 Nano vs Kimi K2 0711
GPT-5 Nano leads Kimi K2 0711 on the Artificial Analysis Intelligence Index, 13.0 to 12.7, and GPT-5 Nano costs 5.7x less per output token ($0.40 vs $2.30 per million). Updated October 21, 2026; 31 benchmarks have a result for both.
GPT-5 Nano or Kimi K2 0711: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5 Nano for output tokens 5.7x cheaper ($0.40 vs $2.30 per million) and a larger context window (400K against 131K tokens).
- Shared results
- 31
- GPT-5 Nano only
- 56
- Kimi K2 0711 only
- 6
- 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
GPT-5 Nano
GPT-5 Nano leads, 13.0 against 12.7.
Same board, both measured
Reasoning
GPQA Diamond
Kimi K2 0711
Kimi K2 0711 leads, 71.5% against 63.4%.
Same board, both measured
Math
AIME
GPT-5 Nano
GPT-5 Nano leads, 81.2% against 62.7%.
Same board, both measured
Knowledge
MMLU Pro
Kimi K2 0711
Kimi K2 0711 leads, 79.4% against 76.1%.
Same board, both measured
Web design
Design Arena: websites
GPT-5 Nano
GPT-5 Nano leads, 1101 against 1050.
Same board, both measured
Long documents
Listed context window
GPT-5 Nano
GPT-5 Nano takes 400K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Nano
GPT-5 Nano $0.0003, Kimi K2 0711 $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Nano has the number, $0.109.
Directional only
At a glance
- Coding index
- GPT-5 Nano not benchmarked, Kimi K2 0711 not benchmarked.
- Widest category
- Agentic work, 24.6 points apart on average over 1 shared benchmark.
- Widest single gap
- SWE-bench Verified: GPT-5 Nano 34.8% against Kimi K2 0711 71.2%, 36.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Nano $0.40 against Kimi K2 0711 $2.30 per million output tokens, 5.7x apart.
- Context window
- GPT-5 Nano takes 400K tokens, Kimi K2 0711 131K.
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-5 Nano | Bars | Kimi K2 0711 | Ties |
|---|---|---|---|---|
| Coding | 2 | 4 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 3 | ||
| Math | 3 | 2 | ||
| Knowledge | 1 | 4 | ||
| Web design | 5 | 0 | ||
| General | 1 | 2 | ||
| All shared boards | 14 | 17 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index24
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 59.1% | Only Kimi K2 0711 measured |
| SWE-bench Verified | 34.8% | 71.2% | Kimi K2 0711 |
| LiveCodeBench (Vals AI) | 70.2% | 70.5% | Kimi K2 0711 |
| LiveCodeBench (Artificial Analysis run) | 78.9% | 55.6% | GPT-5 Nano |
| Terminal-Bench Hard (Artificial Analysis run) | 17.4% | 15.9% | GPT-5 Nano |
| Terminal-Bench | 21.8% | 27.8% | Kimi K2 0711 |
| GSO-Bench | Not measured | 4.9% | Only Kimi K2 0711 measured |
| WeirdML | 38.1% | 39.4% | Kimi K2 0711 |
| LMArena Text: coding | 1351 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: software and IT | 1345 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.0 | 12.7 | GPT-5 Nano |
| Epoch Capabilities Index | 139.2 | 140.0 | Kimi K2 0711 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 36.5% | 61.1% | Kimi K2 0711 |
| Berkeley Function Calling Leaderboard (BFCL) | 51.4% | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| GPQA Diamond | 63.4% | 71.5% | Kimi K2 0711 |
| MMMU Pro (Vals AI) | 70.9% | Not measured | Only GPT-5 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 67.6% | 76.6% | Kimi K2 0711 |
| Humanity's Last Exam (Artificial Analysis run) | 9.5% | 7.4% | GPT-5 Nano |
| GPQA Diamond (Epoch AI run) | 69.4% | Not measured | Only GPT-5 Nano measured |
| ARC-AGI | 20.7% | Not measured | Only GPT-5 Nano measured |
| ARC-AGI-2 | 2.6% | Not measured | Only GPT-5 Nano measured |
| SimpleBench | Not measured | 26.3% | Only Kimi K2 0711 measured |
| Chess puzzles | 22.0% | Not measured | Only GPT-5 Nano measured |
| Mystery game puzzles | 9.0% | Not measured | Only GPT-5 Nano measured |
| VPCT | 37.2% | Not measured | Only GPT-5 Nano measured |
| LMArena Text: hard prompts | 1328 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: expert | 1321 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: hard prompts in English | 1338 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: diagrams | 1141 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: homework | 1157 | Not measured | Only GPT-5 Nano measured |
| Kagi LLM Benchmark | 62.2% | 64.4% | Kimi K2 0711 |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| AIME | 81.2% | 62.7% | GPT-5 Nano |
| MATH 500 (Vals AI) | 93.8% | 94.2% | Kimi K2 0711 |
| MGSM (Vals AI) | 89.3% | 91.0% | Kimi K2 0711 |
| AA Math Index | 83.7 | 57.0 | GPT-5 Nano |
| AIME 2025 (Artificial Analysis run) | 83.7% | 57.0% | GPT-5 Nano |
| OTIS Mock AIME | 81.1% | Not measured | Only GPT-5 Nano measured |
| FrontierMath, tiers 1 to 3 | 20.0% | Not measured | Only GPT-5 Nano measured |
| FrontierMath, tier 4 | 2.4% | Not measured | Only GPT-5 Nano measured |
| ProofBench | 12.0% | Not measured | Only GPT-5 Nano measured |
| MATH level 5 | 95.2% | Not measured | Only GPT-5 Nano measured |
| LMArena Text: math | 1317 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: mathematical work | 1326 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| MMLU Pro | 76.1% | 79.4% | Kimi K2 0711 |
| LegalBench (Vals AI) | 50.1% | 81.5% | Kimi K2 0711 |
| CaseLaw (Vals AI) | 52.6% | Not measured | Only GPT-5 Nano measured |
| CorpFin (Vals AI) | Not measured | 50.4% | Only Kimi K2 0711 measured |
| TaxEval (Vals AI) | 67.4% | 70.2% | Kimi K2 0711 |
| MortgageTax (Vals AI) | 53.6% | Not measured | Only GPT-5 Nano measured |
| MedQA (Vals AI) | 93.3% | 84.0% | GPT-5 Nano |
| MedCode (Vals AI) | 30.4% | Not measured | Only GPT-5 Nano measured |
| MMLU Pro (Artificial Analysis run) | 78.0% | 82.4% | Kimi K2 0711 |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5 Nano measured |
| LMArena Text: science | 1318 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: medicine and healthcare | 1335 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: legal and government | 1298 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: business and finance | 1311 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| Design Arena: websites | 1101 | 1050 | GPT-5 Nano |
| Design Arena: UI components | 1067 | 1030 | GPT-5 Nano |
| Design Arena: game dev | 1045 | 974 | GPT-5 Nano |
| Design Arena: data viz | 1056 | 1018 | GPT-5 Nano |
| Design Arena: 3D | 966 | Not measured | Only GPT-5 Nano measured |
| Design Arena: all code categories | 1084 | 1033 | GPT-5 Nano |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5 Nano | Kimi K2 0711 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 30.4% | Not measured | Only GPT-5 Nano measured |
| MedScribe (Vals AI) | 72.9% | Not measured | Only GPT-5 Nano measured |
| IFBench | 67.6% | 41.5% | GPT-5 Nano |
| Long context reasoning (AA-LCR) | 45.0% | 53.0% | Kimi K2 0711 |
| DTBench | 62.7% | Not measured | Only GPT-5 Nano measured |
| LMCA | 7.9% | Not measured | Only GPT-5 Nano measured |
| Fiction.LiveBench | 44.4% | 61.1% | Kimi K2 0711 |
| Creative writing (Lech Mazur) | Not measured | 85.6% | Only Kimi K2 0711 measured |
| CL-bench | Not measured | 11.9% | Only Kimi K2 0711 measured |
| LMArena Text | 1320 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: instruction following | 1306 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: creative writing | 1249 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision | 1159 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: English | 1321 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: non-English | 1313 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Chinese | 1356 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: German | 1327 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Japanese | 1227 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Korean | 1269 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Spanish | 1360 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Russian | 1296 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Polish | 1314 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: multi-turn | 1311 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: longer queries | 1312 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: writing and language | 1283 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: entertainment and media | 1268 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: English | 1170 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: Chinese | 1176 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: reading text | 1152 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: humor | 1110 | Not measured | Only GPT-5 Nano 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-5 Nano | Kimi K2 0711 | 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-5 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5 Nano 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-5 Nano | MoonshotAI Kimi K2 0711 |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | August 7, 2025 | July 11, 2025 |
| Context window | 400K | 131K |
| Input $/Mtok | $0.05 | $0.57 |
| Output $/Mtok | $0.40 | $2.30 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | $0.109 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Nano better than Kimi K2 0711 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5 Nano for output tokens 5.7x cheaper ($0.40 vs $2.30 per million) and a larger context window (400K against 131K tokens).
Which is cheaper, GPT-5 Nano or Kimi K2 0711?
GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for GPT-5 Nano only.
Which has the bigger context window, GPT-5 Nano or Kimi K2 0711?
GPT-5 Nano, with 400K tokens against 131K.
How many benchmarks is the GPT-5 Nano vs Kimi K2 0711 comparison based on?
31 benchmarks have a result for both models as of October 21, 2026. GPT-5 Nano's coding index rests on 0 independent benchmarks and Kimi K2 0711's on 0. Where only one model has a result, the page says so instead of naming a winner.