The AI arena is free today

Open Superagent

GLM-4.6 vs Llama 3.1 Nemotron Ultra 253B v1

GLM-4.6 leads the LLM Stats Score 29.0 to 19.1.

Zhipu AI · NVIDIA · Updated for 2026

Which is better?

GLM-4.6 leads the overall LLM Stats Score 29.0 to 19.1, ranking #134 overall.

In the 2 individual benchmarks reported for both models, GLM-4.6 wins 2; this is a narrower head-to-head signal than the composite indexes.

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

Choose GLM-4.6

  • overall performance matters — it scores 29.0 and ranks #134 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Sep 2025

Choose Llama 3.1 Nemotron Ultra 253B v1

  • you are already invested in the NVIDIA ecosystem

At a glance

The differences that matter most.

GLM-4.6
Zhipu AI
Llama 3.1 Nemotron Ultra 253B v1
NVIDIA
Core performance indexes
LLM Stats Score
29.0
#134
19.1
#209
Reasoning
28.9
#126
18.8
#208
Coding
14.8
#134
12.4
#149
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.50 / M
— / M
Output price
$2.00 / M
— / M
Context window
202,752
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-4.6
Llama 3.1 Nemotron Ultra 253B v1
Math
24.7#116
15.6#214
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

7 reported for GLM-4.6 · 6 for Llama 3.1 Nemotron Ultra 253B v1

2 shared

GLM-4.6 outperforms in 2 benchmarks (AIME 2025, GPQA), while Llama 3.1 Nemotron Ultra 253B v1 is better at 0 benchmarks.

GLM-4.6 significantly outperforms across most benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

104.0B diff

GLM-4.6 has 104.0B more parameters than Llama 3.1 Nemotron Ultra 253B v1, making it 41.1% larger.

Zhipu AI
GLM-4.6
357.0Bparameters
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1
253.0Bparameters
357.0B
GLM-4.6
253.0B
Llama 3.1 Nemotron Ultra 253B v1

Context Window

Maximum input and output token capacity

Only GLM-4.6 specifies input context (202,752 tokens). Only GLM-4.6 specifies output context (202,752 tokens).

Zhipu AI
GLM-4.6
Input202,752 tokens
Output202,752 tokens
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1
Input- tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GLM-4.6 supports multimodal inputs, whereas Llama 3.1 Nemotron Ultra 253B v1 does not.

GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.6

Text
Images
Audio
Video

Llama 3.1 Nemotron Ultra 253B v1

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.6 is licensed under MIT, while Llama 3.1 Nemotron Ultra 253B v1 uses Llama 3.1 Community License.

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

GLM-4.6

MIT

Open weights

Llama 3.1 Nemotron Ultra 253B v1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

GLM-4.6 was released on 2025-09-30, while Llama 3.1 Nemotron Ultra 253B v1 was released on 2025-04-07.

GLM-4.6 is 6 months newer than Llama 3.1 Nemotron Ultra 253B v1.

GLM-4.6

Sep 30, 2025

11 months ago

5mo newer
Llama 3.1 Nemotron Ultra 253B v1

Apr 7, 2025

1.5 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron Ultra 253B v1 has a documented knowledge cutoff of 2023-12-01, while GLM-4.6's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron Ultra 253B v1's training data extends to 2023-12-01, but cannot make a direct comparison without GLM-4.6's cutoff date.

GLM-4.6

—

Llama 3.1 Nemotron Ultra 253B v1

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-4.6 and Llama 3.1 Nemotron Ultra 253B v1 side-by-side, then vote on the output you prefer.

GLM-4.6
✓ Preferred
Llama 3.1 Nemotron Ultra 253B v1
Open in Playground

FAQ

Common questions about GLM-4.6 vs Llama 3.1 Nemotron Ultra 253B v1.

Which is better, GLM-4.6 or Llama 3.1 Nemotron Ultra 253B v1?

GLM-4.6 leads the LLM Stats Score 29.0 to 19.1. GLM-4.6 is made by Zhipu AI and Llama 3.1 Nemotron Ultra 253B v1 is made by NVIDIA. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-4.6 compare to Llama 3.1 Nemotron Ultra 253B v1 in benchmarks?

GLM-4.6 scores AIME 2025: 93.9%, LiveCodeBench v6: 82.8%, GPQA: 81.0%, SWE-Bench Verified: 68.0%, BrowseComp: 45.1%. Llama 3.1 Nemotron Ultra 253B v1 scores MATH-500: 97.0%, IFEval: 89.5%, GPQA: 76.0%, BFCL v2: 74.1%, AIME 2025: 72.5%.

What are the context window sizes for GLM-4.6 and Llama 3.1 Nemotron Ultra 253B v1?

GLM-4.6 supports 203K tokens and Llama 3.1 Nemotron Ultra 253B v1 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-4.6 and Llama 3.1 Nemotron Ultra 253B v1?

Key differences include LLM Stats Score (29.0 vs 19.1), 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-4.6 and Llama 3.1 Nemotron Ultra 253B v1?

GLM-4.6 is developed by Zhipu AI and Llama 3.1 Nemotron Ultra 253B v1 is developed by NVIDIA.

Related comparisons