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GLM-4.5V vs Llama 3.1 Nemotron 70B Instruct

Comparing GLM-4.5V and Llama 3.1 Nemotron 70B Instruct across benchmarks, pricing, and capabilities.

Zhipu AI · NVIDIA · Updated for 2026

Which is better?

GLM-4.5V and Llama 3.1 Nemotron 70B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose GLM-4.5V

  • you want the most recent training data — it shipped Aug 2025

Choose Llama 3.1 Nemotron 70B Instruct

  • you are already invested in the NVIDIA ecosystem

At a glance

The differences that matter most.

GLM-4.5V
Zhipu AI
Llama 3.1 Nemotron 70B Instruct
NVIDIA
Benchmark wins
—
—
Input price
$0.55 / M
— / M
Output price
$2.19 / M
— / M
Context window
131,072
—

Individual benchmarks

0 reported for GLM-4.5V · 11 for Llama 3.1 Nemotron 70B Instruct

No common benchmarks found

GLM-4.5V and Llama 3.1 Nemotron 70B Instructdon'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

38.0B diff

GLM-4.5V has 38.0B more parameters than Llama 3.1 Nemotron 70B Instruct, making it 54.3% larger.

Zhipu AI
GLM-4.5V
108.0Bparameters
NVIDIA
Llama 3.1 Nemotron 70B Instruct
70.0Bparameters
108.0B
GLM-4.5V
70.0B
Llama 3.1 Nemotron 70B Instruct

Context Window

Maximum input and output token capacity

Only GLM-4.5V specifies input context (131,072 tokens). Only GLM-4.5V specifies output context (131,072 tokens).

Zhipu AI
GLM-4.5V
Input131,072 tokens
Output131,072 tokens
NVIDIA
Llama 3.1 Nemotron 70B Instruct
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GLM-4.5V supports multimodal inputs, whereas Llama 3.1 Nemotron 70B Instruct does not.

GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.5V

Text
Images
Audio
Video

Llama 3.1 Nemotron 70B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.5V is licensed under MIT, while Llama 3.1 Nemotron 70B Instruct uses Llama 3.1 Community License.

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

GLM-4.5V

MIT

Open weights

Llama 3.1 Nemotron 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

GLM-4.5V was released on 2025-08-11, while Llama 3.1 Nemotron 70B Instruct was released on 2024-10-01.

GLM-4.5V is 10 months newer than Llama 3.1 Nemotron 70B Instruct.

GLM-4.5V

Aug 11, 2025

1.1 years ago

10mo newer
Llama 3.1 Nemotron 70B Instruct

Oct 1, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron 70B Instruct has a documented knowledge cutoff of 2023-12-01, while GLM-4.5V's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron 70B Instruct's training data extends to 2023-12-01, but cannot make a direct comparison without GLM-4.5V's cutoff date.

GLM-4.5V

—

Llama 3.1 Nemotron 70B Instruct

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-4.5V and Llama 3.1 Nemotron 70B Instruct side-by-side, then vote on the output you prefer.

GLM-4.5V
✓ Preferred
Llama 3.1 Nemotron 70B Instruct
Open in Playground

FAQ

Common questions about GLM-4.5V vs Llama 3.1 Nemotron 70B Instruct.

Which is better, GLM-4.5V or Llama 3.1 Nemotron 70B Instruct?

GLM-4.5V (Zhipu AI) and Llama 3.1 Nemotron 70B Instruct (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-4.5V compare to Llama 3.1 Nemotron 70B Instruct in benchmarks?

Llama 3.1 Nemotron 70B Instruct scores GSM8k: 91.4%, HellaSwag: 85.6%, Winogrande: 84.5%, GSM8K Chat: 81.9%, MMLU Chat: 80.6%.

What are the context window sizes for GLM-4.5V and Llama 3.1 Nemotron 70B Instruct?

GLM-4.5V supports 131K tokens and Llama 3.1 Nemotron 70B Instruct 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-4.5V and Llama 3.1 Nemotron 70B Instruct?

Key differences include multimodal support (yes vs no), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.5V and Llama 3.1 Nemotron 70B Instruct?

GLM-4.5V is developed by Zhipu AI and Llama 3.1 Nemotron 70B Instruct is developed by NVIDIA.

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