Kimi K2.5 vs MiniMax M2.1
Kimi K2.5 leads MiniMax M2.1 on the Artificial Analysis Intelligence Index, 23.5 to 20.9, and MiniMax M2.1 costs 2.4x less per output token ($1.20 vs $2.85 per million). Updated October 22, 2026; 27 benchmarks have a result for both.
Kimi K2.5 or MiniMax M2.1: which to pick
Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding.
Pick MiniMax M2.1 for output tokens 2.4x cheaper ($1.20 vs $2.85 per million) and work measured by SWE-bench Verified (Vals AI) or MMLU Pro, where it leads.
- Shared results
- 27
- Kimi K2.5 only
- 72
- MiniMax M2.1 only
- 7
- 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 K2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2.5
Kimi K2.5 leads, 23.5 against 20.9.
Same board, both measured
Reasoning
GPQA Diamond
Kimi K2.5
Kimi K2.5 leads, 84.1% against 78.5%.
Same board, both measured
Math
AIME
Kimi K2.5
Kimi K2.5 leads, 95.6% against 77.9%.
Same board, both measured
Knowledge
MMLU Pro
MiniMax M2.1
MiniMax M2.1 leads, 87.0% against 85.9%.
Same board, both measured
Web design
Design Arena: websites
Kimi K2.5
Kimi K2.5 leads, 1248 against 1201.
Same board, both measured
Long documents
Listed context window
Kimi K2.5
Kimi K2.5 takes 262K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.1
Kimi K2.5 $0.0020, MiniMax M2.1 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.5
Kimi K2.5 $0.24, MiniMax M2.1 $0.59.
Published attempt cost and pass rate
At a glance
- Coding index
- Kimi K2.5 38.6 from 3 benchmarks, MiniMax M2.1 not benchmarked.
- Widest category
- Math, 17.7 points apart on average over 1 shared benchmark.
- Widest single gap
- AIME: Kimi K2.5 95.6% against MiniMax M2.1 77.9%, 17.7 points apart on a 0 to 100 scale.
- Output price
- Kimi K2.5 $2.85 against MiniMax M2.1 $1.20 per million output tokens, 2.4x apart.
- Context window
- Kimi K2.5 takes 262K tokens, MiniMax M2.1 205K.
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 K2.5 | Bars | MiniMax M2.1 | Ties |
|---|---|---|---|---|
| Coding | 4 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 1 | 0 | ||
| Knowledge | 5 | 1 | ||
| Web design | 7 | 0 | ||
| General | 2 | 1 | ||
| All shared boards | 24 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index41
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| SWE-bench Verified | 70.8% | Not measured | Only Kimi K2.5 measured |
| SWE-bench Multilingual | 67.3% | Not measured | Only Kimi K2.5 measured |
| LMArena WebDev | 1437 | Not measured | Only Kimi K2.5 measured |
| AA Coding Index | 46.8 | Not measured | Only Kimi K2.5 measured |
| LiveCodeBench (Vals AI) | 83.9% | 81.8% | Kimi K2.5 |
| SWE-bench Verified (Vals AI) | 70.0% | 74.8% | MiniMax M2.1 |
| Vibe Code Bench (Vals AI) | 17.5% | Not measured | Only Kimi K2.5 measured |
| Code migration (Vals AI) | 7.0% | Not measured | Only Kimi K2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 42.0% | Not measured | Only Kimi K2.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 81.0% | Only MiniMax M2.1 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | 28.8% | Kimi K2.5 |
| Terminal-Bench | 43.2% | 36.6% | Kimi K2.5 |
| WeirdML | 45.6% | Not measured | Only Kimi K2.5 measured |
| ALE-Bench | 821.6 | 623.8 | Kimi K2.5 |
| LMArena Text: coding | 1483 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: software and IT | 1471 | Not measured | Only Kimi K2.5 measured |
| LMArena WebDev: React | 1429 | Not measured | Only Kimi K2.5 measured |
| LMArena WebDev: HTML | 1426 | Not measured | Only Kimi K2.5 measured |
| LMArena WebDev: from an image | 1439 | Not measured | Only Kimi K2.5 measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 20.9 | Kimi K2.5 |
| Epoch Capabilities Index | 148.1 | Not measured | Only Kimi K2.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1136 | Not measured | Only Kimi K2.5 measured |
| Design Arena: agents building full-stack apps | 1114 | Not measured | Only Kimi K2.5 measured |
| Design Arena: agents building mobile apps | 1147 | Not measured | Only Kimi K2.5 measured |
| Design Arena: agents building Android apps | 1118 | Not measured | Only Kimi K2.5 measured |
| Design Arena: agents building Godot games | 1219 | Not measured | Only Kimi K2.5 measured |
| Finance Agent (Vals AI) | 35.8% | Not measured | Only Kimi K2.5 measured |
| Legal Research Bench (Vals AI) | 15.9% | Not measured | Only Kimi K2.5 measured |
| Excel Modeling Benchmark (Vals AI) | 28.5% | Not measured | Only Kimi K2.5 measured |
| τ²-Bench Telecom | 95.9% | 85.4% | Kimi K2.5 |
| OSWorld | 63.3% | Not measured | Only Kimi K2.5 measured |
| Vending-Bench 2 | $1,198 | Not measured | Only Kimi K2.5 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| GPQA Diamond | 84.1% | 78.5% | Kimi K2.5 |
| MMMU Pro (Vals AI) | 84.3% | Not measured | Only Kimi K2.5 measured |
| GPQA Diamond (Artificial Analysis run) | 87.9% | 83.0% | Kimi K2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 30.7% | 23.2% | Kimi K2.5 |
| ARC-AGI | 65.3% | Not measured | Only Kimi K2.5 measured |
| ARC-AGI-2 | 11.8% | Not measured | Only Kimi K2.5 measured |
| SimpleBench | 46.8% | Not measured | Only Kimi K2.5 measured |
| LMArena Text: hard prompts | 1453 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: expert | 1466 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: hard prompts in English | 1460 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: diagrams | 1282 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: homework | 1297 | Not measured | Only Kimi K2.5 measured |
| Kagi LLM Benchmark | 78.5% | Not measured | Only Kimi K2.5 measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| AIME | 95.6% | 77.9% | Kimi K2.5 |
| MATH 500 (Vals AI) | Not measured | 89.0% | Only MiniMax M2.1 measured |
| MGSM (Vals AI) | Not measured | 87.8% | Only MiniMax M2.1 measured |
| AA Math Index | Not measured | 82.7 | Only MiniMax M2.1 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 82.7% | Only MiniMax M2.1 measured |
| LMArena Text: math | 1470 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: mathematical work | 1473 | Not measured | Only Kimi K2.5 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| MMLU Pro | 85.9% | 87.0% | MiniMax M2.1 |
| LegalBench (Vals AI) | Not measured | 75.5% | Only MiniMax M2.1 measured |
| CaseLaw (Vals AI) | 58.7% | 55.8% | Kimi K2.5 |
| CorpFin (Vals AI) | 68.3% | 58.9% | Kimi K2.5 |
| TaxEval (Vals AI) | 74.2% | 66.3% | Kimi K2.5 |
| MortgageTax (Vals AI) | 66.5% | Not measured | Only Kimi K2.5 measured |
| MedQA (Vals AI) | 94.4% | 91.2% | Kimi K2.5 |
| MedCode (Vals AI) | 39.3% | 34.1% | Kimi K2.5 |
| MMLU Pro (Artificial Analysis run) | Not measured | 87.5% | Only MiniMax M2.1 measured |
| SimpleQA Verified | 34.3% | Not measured | Only Kimi K2.5 measured |
| LMArena Text: science | 1459 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: medicine and healthcare | 1448 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: legal and government | 1441 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: business and finance | 1427 | Not measured | Only Kimi K2.5 measured |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1248 | 1201 | Kimi K2.5 |
| Design Arena: UI components | 1234 | 1220 | Kimi K2.5 |
| Design Arena: game dev | 1206 | 1134 | Kimi K2.5 |
| Design Arena: data viz | 1219 | 1206 | Kimi K2.5 |
| Design Arena: 3D | 1204 | 1164 | Kimi K2.5 |
| Design Arena: all code categories | 1236 | 1190 | Kimi K2.5 |
| Design Arena: SVG | 1149 | 1131 | Kimi K2.5 |
| Design Arena: ASCII art | 1166 | Not measured | Only Kimi K2.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Kimi K2.5 | MiniMax M2.1 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 49.9% | Not measured | Only Kimi K2.5 measured |
| MedScribe (Vals AI) | 76.4% | 80.8% | MiniMax M2.1 |
| IFBench | 70.2% | 69.9% | Kimi K2.5 |
| Long context reasoning (AA-LCR) | 78.0% | 67.7% | Kimi K2.5 |
| Fiction.LiveBench | 86.1% | Not measured | Only Kimi K2.5 measured |
| CL-bench | 19.3% | Not measured | Only Kimi K2.5 measured |
| CL-bench Life | 13.2% | Not measured | Only Kimi K2.5 measured |
| LMArena Text | 1445 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: instruction following | 1431 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: creative writing | 1422 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision | 1269 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: English | 1453 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: non-English | 1433 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: Chinese | 1494 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: German | 1441 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: Japanese | 1423 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: Korean | 1412 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: French | 1454 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: Spanish | 1450 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: Russian | 1435 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: Polish | 1445 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: multi-turn | 1444 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: longer queries | 1445 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: writing and language | 1425 | Not measured | Only Kimi K2.5 measured |
| LMArena Text: entertainment and media | 1417 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: English | 1274 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: Chinese | 1328 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: reading text | 1276 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: humor | 1284 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: captioning | 1257 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: recognizing things | 1285 | Not measured | Only Kimi K2.5 measured |
| LMArena Vision: creative writing | 1269 | Not measured | Only Kimi K2.5 measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2.5 | MiniMax M2.1 | 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
MiniMax M2.1 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.1 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.1 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 K2.5 | MiniMax M2.1 |
|---|---|---|
| Maker | Moonshot AI | MiniMax |
| Weights | Open weights | Open weights |
| Released | January 27, 2026 | December 23, 2025 |
| Context window | 262K | 205K |
| Input $/Mtok | $0.532 | $0.30 |
| Output $/Mtok | $2.85 | $1.20 |
| Coding index | 38.6 | Not benchmarked |
| Independent measurements behind it | 3 | 1 |
| Cost per solved task | $0.24 | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2.5 better than MiniMax M2.1 for coding?
Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding. Pick MiniMax M2.1 for output tokens 2.4x cheaper ($1.20 vs $2.85 per million) and work measured by SWE-bench Verified (Vals AI) or MMLU Pro, where it leads.
Which is cheaper, Kimi K2.5 or MiniMax M2.1?
Kimi K2.5 costs $0.532 per million input tokens and $2.85 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Per solved SWE-bench Verified task, Kimi K2.5 costs $0.24 and MiniMax M2.1 $0.59.
Which has the bigger context window, Kimi K2.5 or MiniMax M2.1?
Kimi K2.5, with 262K tokens against 205K.
How many benchmarks is the Kimi K2.5 vs MiniMax M2.1 comparison based on?
27 benchmarks have a result for both models as of October 22, 2026. Kimi K2.5's coding index rests on 3 independent benchmarks and MiniMax M2.1's on 1. Where only one model has a result, the page says so instead of naming a winner.