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Llama 3.1 Nemotron Ultra 253B v1 vs Qwen3 VL 4B Thinking

Llama 3.1 Nemotron Ultra 253B v1 leads the LLM Stats Score 19.1 to 12.9.

NVIDIA · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Llama 3.1 Nemotron Ultra 253B v1 leads the overall LLM Stats Score 19.1 to 12.9, ranking #206 overall.

In the 3 individual benchmarks reported for both models, Llama 3.1 Nemotron Ultra 253B v1 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 Llama 3.1 Nemotron Ultra 253B v1

  • overall performance matters — it scores 19.1 and ranks #206 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results

Choose Qwen3 VL 4B Thinking

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

At a glance

The differences that matter most.

Core performance indexes
19.1
#206
12.9
#249
18.8
#205
14.0
#231
Cost, coverage & limits
Benchmark wins
2 of 3
1 of 3
Input price
— / M
$0.10 / M
Output price
— / M
$1.00 / M
Context window
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Llama 3.1 Nemotron Ultra 253B v1
Qwen3 VL 4B Thinking
15.6#214
15.6#216
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for Llama 3.1 Nemotron Ultra 253B v1 · 48 for Qwen3 VL 4B Thinking

3 shared

Llama 3.1 Nemotron Ultra 253B v1 outperforms in 2 benchmarks (GPQA, IFEval), while Qwen3 VL 4B Thinking is better at 1 benchmark (AIME 2025).

Llama 3.1 Nemotron Ultra 253B v1 shows notably better performance in the majority of benchmarks.

Mon Sep 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

249.0B diff

Llama 3.1 Nemotron Ultra 253B v1 has 249.0B more parameters than Qwen3 VL 4B Thinking, making it 6225.0% larger.

NVIDIA
Llama 3.1 Nemotron Ultra 253B v1
253.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
253.0B
Llama 3.1 Nemotron Ultra 253B v1
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).

NVIDIA
Llama 3.1 Nemotron Ultra 253B v1
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3 VL 4B Thinking supports multimodal inputs, whereas Llama 3.1 Nemotron Ultra 253B v1 does not.

Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama 3.1 Nemotron Ultra 253B v1

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.1 Nemotron Ultra 253B v1 is licensed under Llama 3.1 Community License, while Qwen3 VL 4B Thinking uses Apache 2.0.

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

Llama 3.1 Nemotron Ultra 253B v1

Llama 3.1 Community License

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Llama 3.1 Nemotron Ultra 253B v1 was released on 2025-04-07, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 6 months newer than Llama 3.1 Nemotron Ultra 253B v1.

Llama 3.1 Nemotron Ultra 253B v1

Apr 7, 2025

1.5 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

12 months ago

5mo newer

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron Ultra 253B v1 has a documented knowledge cutoff of 2023-12-01, while Qwen3 VL 4B Thinking'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 Qwen3 VL 4B Thinking's cutoff date.

Llama 3.1 Nemotron Ultra 253B v1

Dec 2023

Qwen3 VL 4B Thinking

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Llama 3.1 Nemotron Ultra 253B v1 and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.

Llama 3.1 Nemotron Ultra 253B v1
✓ Preferred
Qwen3 VL 4B Thinking
Open in Playground

FAQ

Common questions about Llama 3.1 Nemotron Ultra 253B v1 vs Qwen3 VL 4B Thinking.

Which is better, Llama 3.1 Nemotron Ultra 253B v1 or Qwen3 VL 4B Thinking?

Llama 3.1 Nemotron Ultra 253B v1 leads the LLM Stats Score 19.1 to 12.9. Llama 3.1 Nemotron Ultra 253B v1 is made by NVIDIA and Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Llama 3.1 Nemotron Ultra 253B v1 compare to Qwen3 VL 4B Thinking in benchmarks?

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%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

What are the context window sizes for Llama 3.1 Nemotron Ultra 253B v1 and Qwen3 VL 4B Thinking?

Llama 3.1 Nemotron Ultra 253B v1 supports an unknown number of tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 3.1 Nemotron Ultra 253B v1 and Qwen3 VL 4B Thinking?

Key differences include LLM Stats Score (19.1 vs 12.9), multimodal support (no vs yes), licensing (Llama 3.1 Community License vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.1 Nemotron Ultra 253B v1 and Qwen3 VL 4B Thinking?

Llama 3.1 Nemotron Ultra 253B v1 is developed by NVIDIA and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.