Model Comparison

Gemini 3.5 Flash-Lite vs Nemotron Nano 9B v2Which is better in 2026?

Comparing Gemini 3.5 Flash-Lite and Nemotron Nano 9B v2 across benchmarks, pricing, and capabilities.

Verdict: Gemini 3.5 Flash-Lite vs Nemotron Nano 9B v2 — which is better?

Gemini 3.5 Flash-Lite (by Google) and Nemotron Nano 9B v2 (by NVIDIA) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose Gemini 3.5 Flash-Lite if…

  • you want the most recent training data — it shipped Jul 2026

Choose Nemotron Nano 9B v2 if…

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

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemini 3.5 Flash-Lite and Nemotron Nano 9B v2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 3.5 Flash-Lite specifies input context (1,048,576 tokens). Only Gemini 3.5 Flash-Lite specifies output context (65,536 tokens).

Google
Gemini 3.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Sun Jul 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 3.5 Flash-Lite supports multimodal inputs, whereas Nemotron Nano 9B v2 does not.

Gemini 3.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 3.5 Flash-Lite

Text
Images
Audio
Video

Nemotron Nano 9B v2

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.5 Flash-Lite is licensed under a proprietary license, while Nemotron Nano 9B v2 uses NVIDIA Open Model License Agreement .

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 3.5 Flash-Lite

Proprietary

Closed source

Nemotron Nano 9B v2

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

Gemini 3.5 Flash-Lite was released on 2026-07-21, while Nemotron Nano 9B v2 was released on 2025-08-18.

Gemini 3.5 Flash-Lite is 11 months newer than Nemotron Nano 9B v2.

Gemini 3.5 Flash-Lite

Jul 21, 2026

4 days ago

11mo newer
Nemotron Nano 9B v2

Aug 18, 2025

11 months ago

Knowledge Cutoff

When training data ends

Gemini 3.5 Flash-Lite has a knowledge cutoff of 2026-03-31, while Nemotron Nano 9B v2 has a cutoff of 2024-09-01.

Gemini 3.5 Flash-Lite has more recent training data (up to 2026-03-31), making it potentially better informed about events through that date compared to Nemotron Nano 9B v2 (2024-09-01).

Gemini 3.5 Flash-Lite

Mar 2026

1.5 yr newer
Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
NVIDIA
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemini 3.5 Flash-Lite and Nemotron Nano 9B v2 side-by-side, then vote on the output you prefer.

Gemini 3.5 Flash-Lite
✓ Preferred
Nemotron Nano 9B v2
Open in Playground
AI Model Comparison Table
Feature
Google
Gemini 3.5 Flash-Lite
NVIDIA
Nemotron Nano 9B v2

FAQ

Common questions about Gemini 3.5 Flash-Lite vs Nemotron Nano 9B v2.

Which is better, Gemini 3.5 Flash-Lite or Nemotron Nano 9B v2?

Gemini 3.5 Flash-Lite (Google) and Nemotron Nano 9B v2 (NVIDIA) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemini 3.5 Flash-Lite compare to Nemotron Nano 9B v2 in benchmarks?

Gemini 3.5 Flash-Lite scores CharXiv-R: 76.5%, OSWorld-Verified: 74.0%, SWE-Bench Pro: 54.2%, Terminal-Bench 2.1: 54.0%, MLE-Bench: 39.2%. 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 Gemini 3.5 Flash-Lite and Nemotron Nano 9B v2?

Gemini 3.5 Flash-Lite 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 Gemini 3.5 Flash-Lite and Nemotron Nano 9B v2?

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

Who makes Gemini 3.5 Flash-Lite and Nemotron Nano 9B v2?

Gemini 3.5 Flash-Lite is developed by Google and Nemotron Nano 9B v2 is developed by NVIDIA.

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