LongCat 2.0 vs Mistral Small 4
LongCat 2.0 leads Mistral Small 4 on the Artificial Analysis Intelligence Index, 19.1 to 11.3, and Mistral Small 4 costs 2.0x less per output token ($0.60 vs $1.20 per million). Updated October 22, 2026; 8 benchmarks have a result for both.
LongCat 2.0 or Mistral Small 4: 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 262K tokens) and work measured by SciCode, where it leads.
- Shared results
- 8
- LongCat 2.0 only
- 0
- Mistral Small 4 only
- 7
- Like-for-like categories
- 5 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
LongCat 2.0
LongCat 2.0 leads, 19.1 against 11.3.
Same board, both measured
Agentic work
AA Agentic Index
LongCat 2.0
LongCat 2.0 leads, 14.0 against 0.8.
Same board, both measured
Long documents
Listed context window
LongCat 2.0
LongCat 2.0 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 4
LongCat 2.0 $0.0009, Mistral Small 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- LongCat 2.0 not benchmarked, Mistral Small 4 not benchmarked.
- Widest category
- General, 15.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): LongCat 2.0 33.7% against Mistral Small 4 9.9%, 23.8 points apart on a 0 to 100 scale.
- Output price
- LongCat 2.0 $1.20 against Mistral Small 4 $0.60 per million output tokens, 2.0x apart.
- Context window
- LongCat 2.0 takes 1.05M tokens, Mistral Small 4 262K.
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 | Mistral Small 4 | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 7 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Coding Index | 45.3 | 26.6 | LongCat 2.0 |
| Vibe Code Bench (Vals AI) | Not measured | 0.0% | Only Mistral Small 4 measured |
| SciCode | 36.3% | 38.8% | Mistral Small 4 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 17.4% | Only Mistral Small 4 measured |
| ALE-Bench | 793.5 | 497.6 | LongCat 2.0 |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 19.1 | 11.3 | LongCat 2.0 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Agentic Index | 14.0 | 0.8 | LongCat 2.0 |
| τ²-Bench Telecom | Not measured | 41.2% | Only Mistral Small 4 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 78.0% | 76.9% | LongCat 2.0 |
| Humanity's Last Exam (Artificial Analysis run) | 33.7% | 9.9% | LongCat 2.0 |
| Kagi LLM Benchmark | Not measured | 40.5% | Only Mistral Small 4 measured |
| Neither model has a result on the other 19 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | LongCat 2.0 | Mistral Small 4 | Leader |
|---|---|---|---|
| IFBench | Not measured | 48.2% | Only Mistral Small 4 measured |
| Long context reasoning (AA-LCR) | 65.0% | 49.7% | LongCat 2.0 |
| DTBench | Not measured | 70.9% | Only Mistral Small 4 measured |
| LMCA | Not measured | 20.6% | Only Mistral Small 4 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | Mistral Small 4 | 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
Mistral Small 4 costs less
Repository review
50K input + 3K output tokens
Mistral Small 4 costs less
Agent loop
200K input + 10K output tokens
Mistral Small 4 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 | Meituan LongCat 2.0 | Mistral Small 4 |
|---|---|---|
| Maker | Meituan | Mistral AI |
| Weights | Open weights | Open weights |
| Released | July 20, 2026 | March 16, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.30 | $0.15 |
| Output $/Mtok | $1.20 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is LongCat 2.0 better than Mistral Small 4 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 262K tokens) and work measured by SciCode, where it leads.
Which is cheaper, LongCat 2.0 or Mistral Small 4?
LongCat 2.0 costs $0.30 per million input tokens and $1.20 per million output tokens; Mistral Small 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, LongCat 2.0 or Mistral Small 4?
LongCat 2.0, with 1.05M tokens against 262K.
How many benchmarks is the LongCat 2.0 vs Mistral Small 4 comparison based on?
8 benchmarks have a result for both models as of October 22, 2026. LongCat 2.0's coding index rests on 0 independent benchmarks and Mistral Small 4's on 1. Where only one model has a result, the page says so instead of naming a winner.