Nova Premier 1.0 vs LongCat 2.0
LongCat 2.0 leads Nova Premier 1.0 on the Artificial Analysis Intelligence Index, 19.1 to 9.2, and LongCat 2.0 costs 10.4x less per output token ($1.20 vs $12.50 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Nova Premier 1.0 or LongCat 2.0: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for work measured by ALE-Bench or AA Intelligence Index, where it leads.
- Shared results
- 5
- Nova Premier 1.0 only
- 9
- LongCat 2.0 only
- 3
- 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
LongCat 2.0
LongCat 2.0 leads, 19.1 against 9.2.
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
Web design
Design Arena: websites
No call
Only Nova Premier 1.0 has a Design Arena: websites result, 835.
Directional only
Long documents
Listed context window
LongCat 2.0
LongCat 2.0 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
LongCat 2.0
Nova Premier 1.0 $0.0088, LongCat 2.0 $0.0009 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, LongCat 2.0 not benchmarked.
- Widest category
- General, 30.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Nova Premier 1.0 34.3% against LongCat 2.0 65.0%, 30.7 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against LongCat 2.0 $1.20 per million output tokens, 10.4x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, LongCat 2.0 1.05M.
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 | Nova Premier 1.0 | Bars | LongCat 2.0 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 45.3 | Only LongCat 2.0 measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only Nova Premier 1.0 measured |
| SciCode | Not measured | 36.3% | Only LongCat 2.0 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | Not measured | Only Nova Premier 1.0 measured |
| ALE-Bench | 147.4 | 793.5 | 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 index01
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 19.1 | LongCat 2.0 |
| 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 | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 14.0 | Only LongCat 2.0 measured |
| τ²-Bench Telecom | 38.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 56.9% | 78.0% | LongCat 2.0 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 33.7% | LongCat 2.0 |
| Kagi LLM Benchmark | 44.8% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| AA Math Index | 17.3 | Not measured | Only Nova Premier 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 17.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 17 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | Leader |
|---|---|---|---|
| IFBench | 36.2% | Not measured | Only Nova Premier 1.0 measured |
| Long context reasoning (AA-LCR) | 34.3% | 65.0% | LongCat 2.0 |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | LongCat 2.0 | 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
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 | Amazon Nova Premier 1.0 | Meituan LongCat 2.0 |
|---|---|---|
| Maker | Amazon | Meituan |
| Weights | No public weights listed | Open weights |
| Released | October 31, 2025 | July 20, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $2.50 | $0.30 |
| Output $/Mtok | $12.50 | $1.20 |
| 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 Nova Premier 1.0 better than LongCat 2.0 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for work measured by ALE-Bench or AA Intelligence Index, where it leads.
Which is cheaper, Nova Premier 1.0 or LongCat 2.0?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; LongCat 2.0 costs $0.30 and $1.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or LongCat 2.0?
LongCat 2.0, with 1.05M tokens against 1M.
How many benchmarks is the Nova Premier 1.0 vs LongCat 2.0 comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and LongCat 2.0's on 0. Where only one model has a result, the page says so instead of naming a winner.