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GLM-5.3-Flash vs Nemotron Nano 9B v2

Comparing GLM-5.3-Flash and Nemotron Nano 9B v2 across benchmarks, pricing, and capabilities.

Zhipu AI · NVIDIA · Updated for 2026

Which is better?

GLM-5.3-Flash and Nemotron Nano 9B v2 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose GLM-5.3-Flash

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

Choose Nemotron Nano 9B v2

  • you are already invested in the NVIDIA ecosystem

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
Released
Aug 2026
Aug 2025
License
MIT
NVIDIA Open Model License Agreement

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3-Flash and Nemotron Nano 9B v2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

311.1B diff

GLM-5.3-Flash has 311.1B more parameters than Nemotron Nano 9B v2, making it 3495.5% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
NVIDIA
Nemotron Nano 9B v2
8.9Bparameters
320.0B
GLM-5.3-Flash
8.9B
Nemotron Nano 9B v2

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-5.3-Flash supports multimodal inputs, whereas Nemotron Nano 9B v2 does not.

GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5.3-Flash

Text
Images
Audio
Video

Nemotron Nano 9B v2

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, 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.

GLM-5.3-Flash

MIT

Open weights

Nemotron Nano 9B v2

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Nemotron Nano 9B v2 was released on 2025-08-18.

GLM-5.3-Flash is 12 months newer than Nemotron Nano 9B v2.

GLM-5.3-Flash

Aug 26, 2026

0 days ago

1.0yr newer
Nemotron Nano 9B v2

Aug 18, 2025

1.0 years ago

Knowledge Cutoff

When training data ends

Nemotron Nano 9B v2 has a documented knowledge cutoff of 2024-09-01, while GLM-5.3-Flash'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 GLM-5.3-Flash's cutoff date.

GLM-5.3-Flash

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GLM-5.3-Flash and Nemotron Nano 9B v2 side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Nemotron Nano 9B v2
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Nemotron Nano 9B v2.

Which is better, GLM-5.3-Flash or Nemotron Nano 9B v2?

GLM-5.3-Flash (Zhipu AI) 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 GLM-5.3-Flash compare to Nemotron Nano 9B v2 in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. 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 GLM-5.3-Flash and Nemotron Nano 9B v2?

GLM-5.3-Flash 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 GLM-5.3-Flash and Nemotron Nano 9B v2?

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

Who makes GLM-5.3-Flash and Nemotron Nano 9B v2?

GLM-5.3-Flash is developed by Zhipu AI and Nemotron Nano 9B v2 is developed by NVIDIA.