LongCat 2.0 vs Pareto 26.9
LongCat 2.0 costs 6.3x less per output token than Pareto 26.9 ($1.20 vs $7.50 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.20
- Coding
- No data
- Overall
- No data
- Output $/M
- $7.50
LongCat 2.0 or Pareto 26.9: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick LongCat 2.0 for output tokens 6.3x cheaper ($1.20 vs $7.50 per million) and a larger context window (1.05M against 262K tokens).
No benchmark has tested both yet. LongCat 2.0 has results on AA Coding Index, SciCode and ALE-Bench; Pareto 26.9 has none yet. Compare them on price and context instead.
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
No call
Only LongCat 2.0 has a AA Intelligence Index result, 19.1.
Directional only
Agentic work
AA Agentic Index
No call
Only LongCat 2.0 has a AA Agentic Index result, 14.0.
Directional only
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
LongCat 2.0
LongCat 2.0 $0.0009, Pareto 26.9 $0.0063 per turn.
List prices
At a glance
- Coding index
- LongCat 2.0 not benchmarked, Pareto 26.9 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- LongCat 2.0 $1.20 against Pareto 26.9 $7.50 per million output tokens, 6.3x apart.
- Context window
- LongCat 2.0 takes 1.05M tokens, Pareto 26.9 262K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards measured
| Benchmark | LongCat 2.0 | Pareto 26.9 | Leader |
|---|---|---|---|
| AA Coding Index | 45.3 | Not measured | Only LongCat 2.0 measured |
| SciCode | 36.3% | Not measured | Only LongCat 2.0 measured |
| ALE-Bench | 793.5 | Not measured | Only LongCat 2.0 measured |
| Neither model has a result on the other 40 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | LongCat 2.0 | Pareto 26.9 | Leader |
|---|---|---|---|
| AA Intelligence Index | 19.1 | Not measured | Only LongCat 2.0 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | LongCat 2.0 | Pareto 26.9 | Leader |
|---|---|---|---|
| AA Agentic Index | 14.0 | Not measured | Only LongCat 2.0 measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | LongCat 2.0 | Pareto 26.9 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 78.0% | Not measured | Only LongCat 2.0 measured |
| Humanity's Last Exam (Artificial Analysis run) | 33.7% | Not measured | Only LongCat 2.0 measured |
| Neither model has a result on the other 21 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | LongCat 2.0 | Pareto 26.9 | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | 65.0% | Not measured | Only LongCat 2.0 measured |
| Neither model has a result on the other 47 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
LongCat 2.0 costs less
Repository review
50K input + 3K output tokens
LongCat 2.0 costs less
Agent loop
200K input + 10K output tokens
LongCat 2.0 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 | Pareto 26.9 |
|---|---|---|
| Maker | Meituan | Unbiased |
| Weights | Open weights | No public weights listed |
| Released | July 20, 2026 | October 13, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.30 | $2.50 |
| Output $/Mtok | $1.20 | $7.50 |
| 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 LongCat 2.0 better than Pareto 26.9 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick LongCat 2.0 for output tokens 6.3x cheaper ($1.20 vs $7.50 per million) and a larger context window (1.05M against 262K tokens).
Which is cheaper, LongCat 2.0 or Pareto 26.9?
LongCat 2.0 costs $0.30 per million input tokens and $1.20 per million output tokens; Pareto 26.9 costs $2.50 and $7.50. Cost per solved task is known for neither of them.
Which has the bigger context window, LongCat 2.0 or Pareto 26.9?
LongCat 2.0, with 1.05M tokens against 262K.
Has any benchmark tested both LongCat 2.0 and Pareto 26.9?
No benchmark has tested both yet. LongCat 2.0 has results on AA Coding Index, SciCode and ALE-Bench; Pareto 26.9 has none yet. Compare them on price and context instead. Data as of October 22, 2026.