LongCat 2.0 vs MiniMax M2.1
MiniMax M2.1 leads LongCat 2.0 on the Artificial Analysis Intelligence Index, 20.9 to 19.1, at about the same output price ($1.20 vs $1.20 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
LongCat 2.0 or MiniMax M2.1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick LongCat 2.0 for a larger context window (1.05M against 205K tokens) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 5
- LongCat 2.0 only
- 3
- MiniMax M2.1 only
- 29
- Like-for-like categories
- 4 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
MiniMax M2.1
MiniMax M2.1 leads, 20.9 against 19.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only LongCat 2.0 has a AA Agentic Index result, 14.0.
Directional only
Reasoning
GPQA Diamond
No call
Only MiniMax M2.1 has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only MiniMax M2.1 has a AIME result, 77.9%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.1 has a MMLU Pro result, 87.0%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2.1 has a Design Arena: websites result, 1201.
Directional only
Long documents
Listed context window
LongCat 2.0
LongCat 2.0 takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
LongCat 2.0 $0.0009, MiniMax M2.1 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.1 has the number, $0.59.
Directional only
At a glance
- Coding index
- LongCat 2.0 not benchmarked, MiniMax M2.1 not benchmarked.
- Widest category
- Reasoning, 7.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): LongCat 2.0 33.7% against MiniMax M2.1 23.2%, 10.5 points apart on a 0 to 100 scale.
- Output price
- Both cost $1.20 per million output tokens.
- Context window
- LongCat 2.0 takes 1.05M 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 | LongCat 2.0 | Bars | MiniMax M2.1 | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 1 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 2 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Coding Index | 45.3 | Not measured | Only LongCat 2.0 measured |
| LiveCodeBench (Vals AI) | Not measured | 81.8% | Only MiniMax M2.1 measured |
| SWE-bench Verified (Vals AI) | Not measured | 74.8% | Only MiniMax M2.1 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 81.0% | Only MiniMax M2.1 measured |
| SciCode | 36.3% | Not measured | Only LongCat 2.0 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 28.8% | Only MiniMax M2.1 measured |
| Terminal-Bench | Not measured | 36.6% | Only MiniMax M2.1 measured |
| ALE-Bench | 793.5 | 623.8 | LongCat 2.0 |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 19.1 | 20.9 | MiniMax M2.1 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Agentic Index | 14.0 | Not measured | Only LongCat 2.0 measured |
| τ²-Bench Telecom | Not measured | 85.4% | Only MiniMax M2.1 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 78.5% | Only MiniMax M2.1 measured |
| GPQA Diamond (Artificial Analysis run) | 78.0% | 83.0% | MiniMax M2.1 |
| Humanity's Last Exam (Artificial Analysis run) | 33.7% | 23.2% | LongCat 2.0 |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| AIME | Not measured | 77.9% | Only MiniMax M2.1 measured |
| 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 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.0% | Only MiniMax M2.1 measured |
| LegalBench (Vals AI) | Not measured | 75.5% | Only MiniMax M2.1 measured |
| CaseLaw (Vals AI) | Not measured | 55.8% | Only MiniMax M2.1 measured |
| CorpFin (Vals AI) | Not measured | 58.9% | Only MiniMax M2.1 measured |
| TaxEval (Vals AI) | Not measured | 66.3% | Only MiniMax M2.1 measured |
| MedQA (Vals AI) | Not measured | 91.2% | Only MiniMax M2.1 measured |
| MedCode (Vals AI) | Not measured | 34.1% | Only MiniMax M2.1 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 87.5% | Only MiniMax M2.1 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1201 | Only MiniMax M2.1 measured |
| Design Arena: UI components | Not measured | 1220 | Only MiniMax M2.1 measured |
| Design Arena: game dev | Not measured | 1134 | Only MiniMax M2.1 measured |
| Design Arena: data viz | Not measured | 1206 | Only MiniMax M2.1 measured |
| Design Arena: 3D | Not measured | 1164 | Only MiniMax M2.1 measured |
| Design Arena: all code categories | Not measured | 1190 | Only MiniMax M2.1 measured |
| Design Arena: SVG | Not measured | 1131 | Only MiniMax M2.1 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | LongCat 2.0 | MiniMax M2.1 | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | Not measured | 80.8% | Only MiniMax M2.1 measured |
| IFBench | Not measured | 69.9% | Only MiniMax M2.1 measured |
| Long context reasoning (AA-LCR) | 65.0% | 67.7% | MiniMax M2.1 |
| Neither model has a result on the other 45 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | 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
Same cost
Repository review
50K input + 3K output tokens
Same cost
Agent loop
200K input + 10K output tokens
Same cost
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 | Meituan LongCat 2.0 | MiniMax M2.1 |
|---|---|---|
| Maker | Meituan | MiniMax |
| Weights | Open weights | Open weights |
| Released | July 20, 2026 | December 23, 2025 |
| Context window | 1.05M | 205K |
| Input $/Mtok | $0.30 | $0.30 |
| Output $/Mtok | $1.20 | $1.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is LongCat 2.0 better than MiniMax M2.1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick LongCat 2.0 for a larger context window (1.05M against 205K tokens) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, LongCat 2.0 or MiniMax M2.1?
LongCat 2.0 costs $0.30 per million input tokens and $1.20 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.1 only.
Which has the bigger context window, LongCat 2.0 or MiniMax M2.1?
LongCat 2.0, with 1.05M tokens against 205K.
How many benchmarks is the LongCat 2.0 vs MiniMax M2.1 comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. LongCat 2.0's coding index rests on 0 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.