LongCat 2.0 vs Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads LongCat 2.0 on the Artificial Analysis Intelligence Index, 26.5 to 19.1, and Nemotron 3.5 Super VL costs 2.4x less per output token ($0.50 vs $1.20 per million). Updated October 22, 2026; 4 benchmarks have a result for both.
LongCat 2.0 or Nemotron 3.5 Super VL: 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 1.05M tokens) and work measured by SciCode or AA Intelligence Index, where it leads.
- Shared results
- 4
- LongCat 2.0 only
- 4
- Nemotron 3.5 Super VL only
- 12
- 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
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads, 26.5 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
Web design
Design Arena: websites
No call
Only Nemotron 3.5 Super VL has a Design Arena: websites result, 1173.
Directional only
Long documents
Listed context window
LongCat 2.0
LongCat 2.0 takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Super VL
LongCat 2.0 $0.0009, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
At a glance
- Coding index
- LongCat 2.0 not benchmarked, Nemotron 3.5 Super VL not benchmarked.
- Widest category
- Coding, 11.5 points apart on average over 1 shared benchmark.
- Widest single gap
- SciCode: LongCat 2.0 36.3% against Nemotron 3.5 Super VL 47.8%, 11.5 points apart on a 0 to 100 scale.
- Output price
- LongCat 2.0 $1.20 against Nemotron 3.5 Super VL $0.50 per million output tokens, 2.4x apart.
- Context window
- LongCat 2.0 takes 1.05M tokens, Nemotron 3.5 Super VL 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 | LongCat 2.0 | Bars | Nemotron 3.5 Super VL | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 1 | 0 | ||
| General | 0 | 1 | ||
| All shared boards | 1 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 65.5% | Only Nemotron 3.5 Super VL measured |
| AA Coding Index | 45.3 | Not measured | Only LongCat 2.0 measured |
| SciCode | 36.3% | 47.8% | Nemotron 3.5 Super VL |
| ALE-Bench | 793.5 | Not measured | Only LongCat 2.0 measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 19.1 | 26.5 | Nemotron 3.5 Super VL |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Agentic Index | 14.0 | Not measured | Only LongCat 2.0 measured |
| LiveBench research | Not measured | 70.9% | Only Nemotron 3.5 Super VL measured |
| LiveBench browser | Not measured | 4.0% | Only Nemotron 3.5 Super VL measured |
| LiveBench long agentic | Not measured | 15.8% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| GPQA Diamond (Artificial Analysis run) | 78.0% | Not measured | Only LongCat 2.0 measured |
| Humanity's Last Exam (Artificial Analysis run) | 33.7% | 30.7% | LongCat 2.0 |
| Neither model has a result on the other 20 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Neither model has a result on 14 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Neither model has a result on 20 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1173 | Only Nemotron 3.5 Super VL measured |
| Design Arena: UI components | Not measured | 1149 | Only Nemotron 3.5 Super VL measured |
| Design Arena: game dev | Not measured | 1110 | Only Nemotron 3.5 Super VL measured |
| Design Arena: 3D | Not measured | 1128 | Only Nemotron 3.5 Super VL measured |
| Design Arena: all code categories | Not measured | 1154 | Only Nemotron 3.5 Super VL measured |
| LiveBench design | Not measured | 60.7% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| Long context reasoning (AA-LCR) | 65.0% | 69.0% | Nemotron 3.5 Super VL |
| Neither model has a result on the other 46 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | LongCat 2.0 | Nemotron 3.5 Super VL | 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
Nemotron 3.5 Super VL costs less
Repository review
50K input + 3K output tokens
Nemotron 3.5 Super VL costs less
Agent loop
200K input + 10K output tokens
Nemotron 3.5 Super VL 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 | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | Meituan | NVIDIA |
| Weights | Open weights | Open weights |
| Released | July 20, 2026 | October 15, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.30 | $0.15 |
| Output $/Mtok | $1.20 | $0.50 |
| 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 Nemotron 3.5 Super VL 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 1.05M tokens) and work measured by SciCode or AA Intelligence Index, where it leads.
Which is cheaper, LongCat 2.0 or Nemotron 3.5 Super VL?
LongCat 2.0 costs $0.30 per million input tokens and $1.20 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, LongCat 2.0 or Nemotron 3.5 Super VL?
LongCat 2.0, with 1.05M tokens against 1.05M.
How many benchmarks is the LongCat 2.0 vs Nemotron 3.5 Super VL comparison based on?
4 benchmarks have a result for both models as of October 22, 2026. LongCat 2.0's coding index rests on 0 independent benchmarks and Nemotron 3.5 Super VL's on 1. Where only one model has a result, the page says so instead of naming a winner.