Model Comparison

Llama 3.2 90B Instruct vs QwQ-32B

QwQ-32B significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Llama 3.2 90B Instruct outperforms in 0 benchmarks, while QwQ-32B is better at 1 benchmark (GPQA).

QwQ-32B significantly outperforms across most benchmarks.

Tue Apr 21 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
Tue Apr 21 2026 • llm-stats.com
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Alibaba Cloud / Qwen Team
QwQ-32B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

57.5B diff

Llama 3.2 90B Instruct has 57.5B more parameters than QwQ-32B, making it 176.9% larger.

Meta
Llama 3.2 90B Instruct
90.0Bparameters
Alibaba Cloud / Qwen Team
QwQ-32B
32.5Bparameters
90.0B
Llama 3.2 90B Instruct
32.5B
QwQ-32B

Context Window

Maximum input and output token capacity

Only Llama 3.2 90B Instruct specifies input context (128,000 tokens). Only Llama 3.2 90B Instruct specifies output context (128,000 tokens).

Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
QwQ-32B
Input- tokens
Output- tokens
Tue Apr 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 90B Instruct supports multimodal inputs, whereas QwQ-32B does not.

Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama 3.2 90B Instruct

Text
Images
Audio
Video

QwQ-32B

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.2 90B Instruct is licensed under Llama 3.2, while QwQ-32B uses Apache 2.0.

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

Llama 3.2 90B Instruct

Llama 3.2

Open weights

QwQ-32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Llama 3.2 90B Instruct was released on 2024-09-25, while QwQ-32B was released on 2025-03-05.

QwQ-32B is 5 months newer than Llama 3.2 90B Instruct.

Llama 3.2 90B Instruct

Sep 25, 2024

1.6 years ago

QwQ-32B

Mar 5, 2025

1.1 years ago

5mo newer

Knowledge Cutoff

When training data ends

QwQ-32B has a documented knowledge cutoff of 2024-11-28, while Llama 3.2 90B Instruct's cutoff date is not specified.

We can confirm QwQ-32B's training data extends to 2024-11-28, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.

Llama 3.2 90B Instruct

QwQ-32B

Nov 2024

Outputs Comparison

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Key Takeaways

Larger context window (128,000 tokens)
Supports multimodal inputs
Alibaba Cloud / Qwen Team

QwQ-32B

View details

Alibaba Cloud / Qwen Team

Higher GPQA score (65.2% vs 46.7%)

Detailed Comparison

AI Model Comparison Table
Feature
Meta
Llama 3.2 90B Instruct
Alibaba Cloud / Qwen Team
QwQ-32B

FAQ

Common questions about Llama 3.2 90B Instruct vs QwQ-32B

QwQ-32B significantly outperforms across most benchmarks. Llama 3.2 90B Instruct is made by Meta and QwQ-32B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%. QwQ-32B scores MATH-500: 90.6%, IFEval: 83.9%, AIME 2024: 79.5%, LiveBench: 73.1%, BFCL: 66.4%.
Llama 3.2 90B Instruct supports 128K tokens and QwQ-32B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (yes vs no), licensing (Llama 3.2 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Llama 3.2 90B Instruct is developed by Meta and QwQ-32B is developed by Alibaba Cloud / Qwen Team.