Kimi K2 0711 vs o4 Mini
o4 Mini leads Kimi K2 0711 on the Artificial Analysis Intelligence Index, 16.7 to 12.7, and Kimi K2 0711 costs 1.9x less per output token ($2.30 vs $4.40 per million). Updated October 22, 2026; 35 benchmarks have a result for both.
Kimi K2 0711 or o4 Mini: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Kimi K2 0711 for output tokens 1.9x cheaper ($2.30 vs $4.40 per million) and work measured by Aider polyglot or LiveCodeBench (Vals AI), where it leads.
- Shared results
- 35
- Kimi K2 0711 only
- 2
- o4 Mini only
- 63
- 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
o4 Mini
o4 Mini leads, 16.7 against 12.7.
Same board, both measured
Reasoning
GPQA Diamond
o4 Mini
o4 Mini leads, 74.5% against 71.5%.
Same board, both measured
Math
AIME
o4 Mini
o4 Mini leads, 83.7% against 62.7%.
Same board, both measured
Knowledge
MMLU Pro
o4 Mini
o4 Mini leads, 80.6% against 79.4%.
Same board, both measured
Web design
Design Arena: websites
Kimi K2 0711
Kimi K2 0711 leads, 1050 against 985.
Same board, both measured
Long documents
Listed context window
o4 Mini
o4 Mini takes 200K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2 0711
Kimi K2 0711 $0.0017, o4 Mini $0.0033 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0711 not benchmarked, o4 Mini not benchmarked.
- Widest category
- Math, 18.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- AA Math Index: Kimi K2 0711 57.0 against o4 Mini 90.7, 33.7 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0711 $2.30 against o4 Mini $4.40 per million output tokens, 1.9x apart.
- Context window
- Kimi K2 0711 takes 131K tokens, o4 Mini 200K.
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 | Kimi K2 0711 | Bars | o4 Mini | Ties |
|---|---|---|---|---|
| Coding | 3 | 4 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 4 | 1 tie | |
| Knowledge | 1 | 5 | ||
| Web design | 4 | 1 | ||
| General | 1 | 3 | ||
| All shared boards | 10 | 24 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index34
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| Aider polyglot | 59.1% | 72.0% | o4 Mini |
| SWE-bench Verified | 71.2% | 64.6% | Kimi K2 0711 |
| SWE-bench Multimodal | Not measured | 33.9% | Only o4 Mini measured |
| LiveCodeBench (Vals AI) | 70.5% | 82.2% | o4 Mini |
| LiveCodeBench (Artificial Analysis run) | 55.6% | 85.9% | o4 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | 15.2% | Kimi K2 0711 |
| Terminal-Bench | 27.8% | Not measured | Only Kimi K2 0711 measured |
| GSO-Bench | 4.9% | 3.6% | Kimi K2 0711 |
| WeirdML | 39.4% | 52.6% | o4 Mini |
| LMArena Text: coding | Not measured | 1368 | Only o4 Mini measured |
| LMArena Text: software and IT | Not measured | 1367 | Only o4 Mini measured |
| SciCode | Not measured | 10.8% | Only o4 Mini measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | 16.7 | o4 Mini |
| Epoch Capabilities Index | 140.0 | 145.5 | o4 Mini |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 61.1% | 55.6% | Kimi K2 0711 |
| METR time horizons | Not measured | 63.9% | Only o4 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 53.2% | Only o4 Mini measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | 71.5% | 74.5% | o4 Mini |
| MMMU Pro (Vals AI) | Not measured | 79.7% | Only o4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 76.6% | 78.4% | o4 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | 16.5% | o4 Mini |
| GPQA Diamond (Epoch AI run) | Not measured | 79.6% | Only o4 Mini measured |
| ARC-AGI | Not measured | 58.7% | Only o4 Mini measured |
| ARC-AGI-2 | Not measured | 6.1% | Only o4 Mini measured |
| SimpleBench | 26.3% | 38.7% | o4 Mini |
| Chess puzzles | Not measured | 22.0% | Only o4 Mini measured |
| Mystery game puzzles | Not measured | 5.0% | Only o4 Mini measured |
| VPCT | Not measured | 57.5% | Only o4 Mini measured |
| LMArena Text: hard prompts | Not measured | 1351 | Only o4 Mini measured |
| LMArena Text: expert | Not measured | 1343 | Only o4 Mini measured |
| LMArena Text: hard prompts in English | Not measured | 1366 | Only o4 Mini measured |
| LMArena Vision: diagrams | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: homework | Not measured | 1234 | Only o4 Mini measured |
| Kagi LLM Benchmark | 64.4% | 67.6% | o4 Mini |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| AIME | 62.7% | 83.7% | o4 Mini |
| MATH 500 (Vals AI) | 94.2% | 94.2% | Tie |
| MGSM (Vals AI) | 91.0% | 93.4% | o4 Mini |
| AA Math Index | 57.0 | 90.7 | o4 Mini |
| AIME 2025 (Artificial Analysis run) | 57.0% | 90.7% | o4 Mini |
| OTIS Mock AIME | Not measured | 81.7% | Only o4 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 36.1% | Only o4 Mini measured |
| FrontierMath, tier 4 | Not measured | 4.9% | Only o4 Mini measured |
| MATH level 5 | Not measured | 97.8% | Only o4 Mini measured |
| LMArena Text: math | Not measured | 1389 | Only o4 Mini measured |
| LMArena Text: mathematical work | Not measured | 1379 | Only o4 Mini measured |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | 79.4% | 80.6% | o4 Mini |
| LegalBench (Vals AI) | 81.5% | 79.2% | Kimi K2 0711 |
| CorpFin (Vals AI) | 50.4% | 59.0% | o4 Mini |
| TaxEval (Vals AI) | 70.2% | 74.8% | o4 Mini |
| MortgageTax (Vals AI) | Not measured | 64.8% | Only o4 Mini measured |
| MedQA (Vals AI) | 84.0% | 96.0% | o4 Mini |
| MedCode (Vals AI) | Not measured | 33.8% | Only o4 Mini measured |
| MMLU Pro (Artificial Analysis run) | 82.4% | 83.2% | o4 Mini |
| SimpleQA Verified | Not measured | 19.6% | Only o4 Mini measured |
| GeoBench | Not measured | 64.0% | Only o4 Mini measured |
| LMArena Text: science | Not measured | 1354 | Only o4 Mini measured |
| LMArena Text: medicine and healthcare | Not measured | 1361 | Only o4 Mini measured |
| LMArena Text: legal and government | Not measured | 1350 | Only o4 Mini measured |
| LMArena Text: business and finance | Not measured | 1325 | Only o4 Mini measured |
| FACTS Benchmark Suite | Not measured | 28.1% | Only o4 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 index41
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 1050 | 985 | Kimi K2 0711 |
| Design Arena: UI components | 1027 | 983 | Kimi K2 0711 |
| Design Arena: game dev | 973 | 1003 | o4 Mini |
| Design Arena: data viz | 1018 | 991 | Kimi K2 0711 |
| Design Arena: 3D | Not measured | 854 | Only o4 Mini measured |
| Design Arena: all code categories | 1033 | 976 | Kimi K2 0711 |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Kimi K2 0711 | o4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.1% | Only o4 Mini measured |
| MedScribe (Vals AI) | Not measured | 69.1% | Only o4 Mini measured |
| IFBench | 41.5% | 68.7% | o4 Mini |
| Long context reasoning (AA-LCR) | 53.0% | 61.0% | o4 Mini |
| DTBench | Not measured | 77.6% | Only o4 Mini measured |
| LMCA | Not measured | 26.5% | Only o4 Mini measured |
| Fiction.LiveBench | 61.1% | 77.8% | o4 Mini |
| Creative writing (Lech Mazur) | 85.6% | 75.0% | Kimi K2 0711 |
| CL-bench | 11.9% | Not measured | Only Kimi K2 0711 measured |
| LMArena Text | Not measured | 1353 | Only o4 Mini measured |
| LMArena Text: instruction following | Not measured | 1320 | Only o4 Mini measured |
| LMArena Text: creative writing | Not measured | 1294 | Only o4 Mini measured |
| LMArena Vision | Not measured | 1194 | Only o4 Mini measured |
| LMArena Text: English | Not measured | 1367 | Only o4 Mini measured |
| LMArena Text: non-English | Not measured | 1337 | Only o4 Mini measured |
| LMArena Text: Chinese | Not measured | 1354 | Only o4 Mini measured |
| LMArena Text: German | Not measured | 1336 | Only o4 Mini measured |
| LMArena Text: Japanese | Not measured | 1308 | Only o4 Mini measured |
| LMArena Text: Korean | Not measured | 1312 | Only o4 Mini measured |
| LMArena Text: French | Not measured | 1364 | Only o4 Mini measured |
| LMArena Text: Spanish | Not measured | 1346 | Only o4 Mini measured |
| LMArena Text: Russian | Not measured | 1334 | Only o4 Mini measured |
| LMArena Text: Polish | Not measured | 1358 | Only o4 Mini measured |
| LMArena Text: multi-turn | Not measured | 1350 | Only o4 Mini measured |
| LMArena Text: longer queries | Not measured | 1315 | Only o4 Mini measured |
| LMArena Text: writing and language | Not measured | 1316 | Only o4 Mini measured |
| LMArena Text: entertainment and media | Not measured | 1308 | Only o4 Mini measured |
| LMArena Vision: English | Not measured | 1200 | Only o4 Mini measured |
| LMArena Vision: Chinese | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: reading text | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: humor | Not measured | 1199 | Only o4 Mini measured |
| LMArena Vision: captioning | Not measured | 1204 | Only o4 Mini measured |
| LMArena Vision: recognizing things | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: creative writing | Not measured | 1166 | Only o4 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 | Kimi K2 0711 | o4 Mini | 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 0711 costs less
Repository review
50K input + 3K output tokens
Kimi K2 0711 costs less
Agent loop
200K input + 10K output tokens
Kimi K2 0711 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 | MoonshotAI Kimi K2 0711 | OpenAI o4 Mini |
|---|---|---|
| Maker | Moonshot AI | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | July 11, 2025 | April 16, 2025 |
| Context window | 131K | 200K |
| Input $/Mtok | $0.57 | $1.10 |
| Output $/Mtok | $2.30 | $4.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2 0711 better than o4 Mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Kimi K2 0711 for output tokens 1.9x cheaper ($2.30 vs $4.40 per million) and work measured by Aider polyglot or LiveCodeBench (Vals AI), where it leads.
Which is cheaper, Kimi K2 0711 or o4 Mini?
Kimi K2 0711 costs $0.57 per million input tokens and $2.30 per million output tokens; o4 Mini costs $1.10 and $4.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Kimi K2 0711 or o4 Mini?
o4 Mini, with 200K tokens against 131K.
How many benchmarks is the Kimi K2 0711 vs o4 Mini comparison based on?
35 benchmarks have a result for both models as of October 22, 2026. Kimi K2 0711's coding index rests on 0 independent benchmarks and o4 Mini's on 0. Where only one model has a result, the page says so instead of naming a winner.