GPT-5 Mini vs Kimi K2 0711
Updated October 21, 2026. 32 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 0711 for coding: it scores 64.7 on the Vibe Coding Index against 59.8 for GPT-5 Mini.
Pick GPT-5 Mini when output tokens cost 1.1x less, or when the context window is larger, 400K against 131K tokens.
- Shared results
- 32
- GPT-5 Mini only
- 66
- Kimi K2 0711 only
- 4
- Like-for-like categories
- 8 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 0711
Kimi K2 0711 scores 64.7 against 59.8.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5 Mini
GPT-5 Mini leads, 20.6 against 12.7.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5 Mini
GPT-5 Mini leads, 80.3% against 71.5%.
Same board, both measured
Math
AIME
GPT-5 Mini
GPT-5 Mini leads, 91.5% against 62.7%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5 Mini
GPT-5 Mini leads, 82.2% against 79.4%.
Same board, both measured
Web design
Design Arena: websites
GPT-5 Mini
GPT-5 Mini leads, 1125 against 1050.
Same board, both measured
Long documents
Listed context window
GPT-5 Mini
GPT-5 Mini takes 400K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Mini
GPT-5 Mini $0.0013, Kimi K2 0711 $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Mini has the number, $0.08.
Directional only
At a glance
- Coding index
- GPT-5 Mini 59.8 from 1 benchmark, Kimi K2 0711 64.7 from 2 benchmarks.
- Widest category
- Math, 19.7 points apart on average over 5 shared benchmarks.
- Widest single gap
- IFBench: GPT-5 Mini 75.4% against Kimi K2 0711 41.5%, 33.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Mini $2.00 against Kimi K2 0711 $2.30 per million output tokens, 1.1x apart.
- Context window
- GPT-5 Mini 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 Mini | Bars | Kimi K2 0711 | Ties |
|---|---|---|---|---|
| Coding | 5 | 1 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 5 | 0 | ||
| Knowledge | 6 | 0 | ||
| Web design | 5 | 0 | ||
| General | 3 | 1 | ||
| All shared boards | 30 | 2 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index51
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 59.1% | Only Kimi K2 0711 measured |
| SWE-bench Verified | 59.8% | 71.2% | Kimi K2 0711 |
| SWE-bench Multilingual | 39.7% | Not measured | Only GPT-5 Mini measured |
| LiveCodeBench (Vals AI) | 86.6% | 70.5% | GPT-5 Mini |
| SWE-bench Verified (Vals AI) | 60.8% | Not measured | Only GPT-5 Mini measured |
| Vibe Code Bench (Vals AI) | 14.2% | Not measured | Only GPT-5 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 83.8% | 55.6% | GPT-5 Mini |
| SciCode | 39.0% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 15.9% | GPT-5 Mini |
| Terminal-Bench | 34.8% | 27.8% | GPT-5 Mini |
| GSO-Bench | Not measured | 4.9% | Only Kimi K2 0711 measured |
| WeirdML | 52.7% | 39.4% | GPT-5 Mini |
| LMArena Text: coding | 1406 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: software and IT | 1394 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.6 | 12.7 | GPT-5 Mini |
| Epoch Capabilities Index | 145.3 | 140.0 | GPT-5 Mini |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 71.1% | 61.1% | GPT-5 Mini |
| Vending-Bench 2 | -$31 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| GPQA Diamond | 80.3% | 71.5% | GPT-5 Mini |
| MMMU Pro (Vals AI) | 78.9% | Not measured | Only GPT-5 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 82.8% | 76.6% | GPT-5 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 21.5% | 7.4% | GPT-5 Mini |
| GPQA Diamond (Epoch AI run) | 75.0% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI | 54.3% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI-2 | 4.4% | Not measured | Only GPT-5 Mini measured |
| SimpleBench | Not measured | 26.3% | Only Kimi K2 0711 measured |
| Chess puzzles | 24.0% | Not measured | Only GPT-5 Mini measured |
| Mystery game puzzles | 10.0% | Not measured | Only GPT-5 Mini measured |
| VPCT | 40.2% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: expert | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts in English | 1383 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: diagrams | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: homework | 1210 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| AIME | 91.5% | 62.7% | GPT-5 Mini |
| MATH 500 (Vals AI) | 94.8% | 94.2% | GPT-5 Mini |
| MGSM (Vals AI) | 92.6% | 91.0% | GPT-5 Mini |
| AA Math Index | 90.7 | 57.0 | GPT-5 Mini |
| AIME 2025 (Artificial Analysis run) | 90.7% | 57.0% | GPT-5 Mini |
| OTIS Mock AIME | 86.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | 46.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5 Mini measured |
| ProofBench | 9.0% | Not measured | Only GPT-5 Mini measured |
| MATH level 5 | 97.8% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: math | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: mathematical work | 1380 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| MMLU Pro | 82.2% | 79.4% | GPT-5 Mini |
| LegalBench (Vals AI) | 81.8% | 81.5% | GPT-5 Mini |
| CaseLaw (Vals AI) | 68.5% | Not measured | Only GPT-5 Mini measured |
| CorpFin (Vals AI) | 60.2% | 50.4% | GPT-5 Mini |
| TaxEval (Vals AI) | 75.2% | 70.2% | GPT-5 Mini |
| MortgageTax (Vals AI) | 66.9% | Not measured | Only GPT-5 Mini measured |
| MedQA (Vals AI) | 96.1% | 84.0% | GPT-5 Mini |
| MedCode (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MMLU Pro (Artificial Analysis run) | 83.7% | 82.4% | GPT-5 Mini |
| SimpleQA Verified | 21.6% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: science | 1371 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: medicine and healthcare | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: legal and government | 1375 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: business and finance | 1358 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| Design Arena: websites | 1125 | 1050 | GPT-5 Mini |
| Design Arena: UI components | 1106 | 1030 | GPT-5 Mini |
| Design Arena: game dev | 1130 | 974 | GPT-5 Mini |
| Design Arena: data viz | 1131 | 1018 | GPT-5 Mini |
| Design Arena: 3D | 1037 | Not measured | Only GPT-5 Mini measured |
| Design Arena: all code categories | 1115 | 1034 | GPT-5 Mini |
| Design Arena: SVG | 1091 | Not measured | Only GPT-5 Mini measured |
| Design Arena: ASCII art | 1124 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | GPT-5 Mini | Kimi K2 0711 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MedScribe (Vals AI) | 80.6% | Not measured | Only GPT-5 Mini measured |
| IFBench | 75.4% | 41.5% | GPT-5 Mini |
| Long context reasoning (AA-LCR) | 72.3% | 53.0% | GPT-5 Mini |
| DTBench | 80.5% | Not measured | Only GPT-5 Mini measured |
| LMCA | 34.2% | Not measured | Only GPT-5 Mini measured |
| Fiction.LiveBench | 69.4% | 61.1% | GPT-5 Mini |
| Creative writing (Lech Mazur) | 83.1% | 85.6% | Kimi K2 0711 |
| CL-bench | Not measured | 11.9% | Only Kimi K2 0711 measured |
| LMArena Text | 1373 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: instruction following | 1357 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: creative writing | 1325 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: English | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: non-English | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Chinese | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: German | 1366 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Japanese | 1341 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Korean | 1308 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: French | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Spanish | 1354 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Russian | 1362 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Polish | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: multi-turn | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: longer queries | 1355 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: writing and language | 1344 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: entertainment and media | 1340 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: English | 1216 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: Chinese | 1214 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: reading text | 1199 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: humor | 1205 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: captioning | 1217 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: creative writing | 1181 | Not measured | Only GPT-5 Mini 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 | GPT-5 Mini | 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 Mini costs less
Repository review
50K input + 3K output tokens
GPT-5 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5 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-5 Mini | 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 | $0.25 | $0.57 |
| Output $/Mtok | $2.00 | $2.30 |
| Coding index | 59.8 | 64.7 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.08 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Mini better than Kimi K2 0711 for coding?
Pick Kimi K2 0711 for coding: it scores 64.7 on the Vibe Coding Index against 59.8 for GPT-5 Mini. Pick GPT-5 Mini when output tokens cost 1.1x less, or when the context window is larger, 400K against 131K tokens.
Which is cheaper, GPT-5 Mini or Kimi K2 0711?
GPT-5 Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for GPT-5 Mini only.
Which has the bigger context window, GPT-5 Mini or Kimi K2 0711?
GPT-5 Mini, with 400K tokens against 131K.
How many benchmarks is the GPT-5 Mini vs Kimi K2 0711 comparison based on?
32 benchmarks have a result for both models as of October 21, 2026. GPT-5 Mini's coding index rests on 1 independent benchmark and Kimi K2 0711's on 2. Where only one model has a result, the page says so instead of naming a winner.