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LongCat-2.5 vs Nemotron Nano 9B v2

LongCat-2.5 leads the LLM Stats Score 50.0 to 17.9.

Meituan · NVIDIA · Updated for 2026

Which is better?

LongCat-2.5 leads the overall LLM Stats Score 50.0 to 17.9, ranking #20 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose LongCat-2.5

  • overall performance matters — it scores 50.0 and ranks #20 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Nov 2026

Choose Nemotron Nano 9B v2

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

LongCat-2.5
Meituan
Nemotron Nano 9B v2
NVIDIA
Core performance indexes
LLM Stats Score
50.0
#20
17.9
#250
Reasoning
48.3
#21
16.7
#249
Coding
38.6
#27
14.4
#162
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
LongCat-2.5
Nemotron Nano 9B v2
Math
37.2#37
16.4#221
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for LongCat-2.5 · 6 for Nemotron Nano 9B v2

No common benchmarks found

LongCat-2.5 and Nemotron Nano 9B v2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1591.1B diff

LongCat-2.5 has 1591.1B more parameters than Nemotron Nano 9B v2, making it 17877.5% larger.

Meituan
LongCat-2.5
1.6Tparameters
NVIDIA
Nemotron Nano 9B v2
8.9Bparameters
1600.0B
LongCat-2.5
8.9B
Nemotron Nano 9B v2

Context Window

Maximum input and output token capacity

Only LongCat-2.5 specifies input context (1,048,576 tokens). Only LongCat-2.5 specifies output context (131,072 tokens).

Meituan
LongCat-2.5
Input1,048,576 tokens
Output131,072 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Mon Nov 02 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

LongCat-2.5 supports multimodal inputs, whereas Nemotron Nano 9B v2 does not.

LongCat-2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-2.5

Text
Images
Audio
Video

Nemotron Nano 9B v2

Text
Images
Audio
Video

Release Timeline

When each model was launched

LongCat-2.5 was released on 2026-11-01, while Nemotron Nano 9B v2 was released on 2025-08-18.

LongCat-2.5 is 15 months newer than Nemotron Nano 9B v2.

LongCat-2.5

Nov 1, 2026

0 days ago

1.2yr newer
Nemotron Nano 9B v2

Aug 18, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Nemotron Nano 9B v2 has a documented knowledge cutoff of 2024-09-01, while LongCat-2.5's cutoff date is not specified.

We can confirm Nemotron Nano 9B v2's training data extends to 2024-09-01, but cannot make a direct comparison without LongCat-2.5's cutoff date.

LongCat-2.5

—

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against LongCat-2.5 and Nemotron Nano 9B v2 side-by-side, then vote on the output you prefer.

LongCat-2.5
✓ Preferred
Nemotron Nano 9B v2
Open in Playground

FAQ

Common questions about LongCat-2.5 vs Nemotron Nano 9B v2.

Which is better, LongCat-2.5 or Nemotron Nano 9B v2?

LongCat-2.5 leads the LLM Stats Score 50.0 to 17.9. LongCat-2.5 is made by Meituan and Nemotron Nano 9B v2 is made by NVIDIA. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does LongCat-2.5 compare to Nemotron Nano 9B v2 in benchmarks?

LongCat-2.5 scores MathVision: 96.5%, BrowseComp: 91.9%, CharXiv-R: 90.2%, Terminal-Bench 2.1: 88.4%, Video-MME: 85.2%. Nemotron Nano 9B v2 scores MATH-500: 97.8%, IFEval: 90.3%, AIME 2025: 72.1%, LiveCodeBench: 71.1%, BFCL_v3_MultiTurn: 66.9%.

What are the context window sizes for LongCat-2.5 and Nemotron Nano 9B v2?

LongCat-2.5 supports 1.0M tokens and Nemotron Nano 9B v2 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between LongCat-2.5 and Nemotron Nano 9B v2?

Key differences include LLM Stats Score (50.0 vs 17.9), multimodal support (yes vs no), licensing (Unknown vs NVIDIA Open Model License Agreement ). See the full comparison above for benchmark-by-benchmark results.

Who makes LongCat-2.5 and Nemotron Nano 9B v2?

LongCat-2.5 is developed by Meituan and Nemotron Nano 9B v2 is developed by NVIDIA.

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