Model Comparison

Llama-3.3 Nemotron Super 49B v1 vs Qwen3 VL 235B A22B Thinking

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Llama-3.3 Nemotron Super 49B v1 outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 1 benchmark (AIME 2025).

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

Thu Apr 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 30 2026 • llm-stats.com
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input tokens$0.45
Output tokens$3.49
Best providerDeepinfra
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Model Size

Parameter count comparison

186.1B diff

Qwen3 VL 235B A22B Thinking has 186.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 372.9% larger.

NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
236.0Bparameters
49.9B
Llama-3.3 Nemotron Super 49B v1
236.0B
Qwen3 VL 235B A22B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 235B A22B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Thinking specifies output context (262,144 tokens).

NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas Llama-3.3 Nemotron Super 49B v1 does not.

Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama-3.3 Nemotron Super 49B v1

Text
Images
Audio
Video

Qwen3 VL 235B A22B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Llama-3.3 Nemotron Super 49B v1 is licensed under Llama 3.1 Community License, while Qwen3 VL 235B A22B Thinking uses Apache 2.0.

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

Llama-3.3 Nemotron Super 49B v1

Llama 3.1 Community License

Open weights

Qwen3 VL 235B A22B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.

Qwen3 VL 235B A22B Thinking is 6 months newer than Llama-3.3 Nemotron Super 49B v1.

Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.1 years ago

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

7 months ago

6mo newer

Knowledge Cutoff

When training data ends

Llama-3.3 Nemotron Super 49B v1 has a documented knowledge cutoff of 2023-12-31, while Qwen3 VL 235B A22B Thinking's cutoff date is not specified.

We can confirm Llama-3.3 Nemotron Super 49B v1's training data extends to 2023-12-31, but cannot make a direct comparison without Qwen3 VL 235B A22B Thinking's cutoff date.

Llama-3.3 Nemotron Super 49B v1

Dec 2023

Qwen3 VL 235B A22B Thinking

Outputs Comparison

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Key Takeaways

Larger context window (262,144 tokens)
Supports multimodal inputs
Higher AIME 2025 score (89.7% vs 58.4%)

Detailed Comparison

FAQ

Common questions about Llama-3.3 Nemotron Super 49B v1 vs Qwen3 VL 235B A22B Thinking

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Llama-3.3 Nemotron Super 49B v1 is made by NVIDIA and Qwen3 VL 235B A22B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Llama-3.3 Nemotron Super 49B v1 scores MATH-500: 96.6%, MT-Bench: 91.7%, MBPP: 91.3%, Arena Hard: 88.3%, BFCL v2: 73.7%. Qwen3 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%.
Llama-3.3 Nemotron Super 49B v1 supports an unknown number of tokens and Qwen3 VL 235B A22B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include 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.
Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA and Qwen3 VL 235B A22B Thinking is developed by Alibaba Cloud / Qwen Team.