Model Comparison

Llama 3.2 90B Instruct vs Qwen2.5-Omni-7B

Llama 3.2 90B Instruct has a slight edge in benchmark performance.

Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

Llama 3.2 90B Instruct outperforms in 5 benchmarks (AI2D, ChartQA, GPQA, MMMU, MMMU-Pro), while Qwen2.5-Omni-7B is better at 4 benchmarks (DocVQA, MATH, MathVista, TextVQA).

Llama 3.2 90B Instruct has a slight edge in benchmark performance.

Fri Apr 17 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
Fri Apr 17 2026 • llm-stats.com
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

83.0B diff

Llama 3.2 90B Instruct has 83.0B more parameters than Qwen2.5-Omni-7B, making it 1185.7% larger.

Meta
Llama 3.2 90B Instruct
90.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
90.0B
Llama 3.2 90B Instruct
7.0B
Qwen2.5-Omni-7B

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
Qwen2.5-Omni-7B
Input- tokens
Output- tokens
Fri Apr 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Llama 3.2 90B Instruct and Qwen2.5-Omni-7B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Llama 3.2 90B Instruct

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.2 90B Instruct is licensed under Llama 3.2, while Qwen2.5-Omni-7B 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

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Llama 3.2 90B Instruct was released on 2024-09-25, while Qwen2.5-Omni-7B was released on 2025-03-27.

Qwen2.5-Omni-7B is 6 months newer than Llama 3.2 90B Instruct.

Llama 3.2 90B Instruct

Sep 25, 2024

1.6 years ago

Qwen2.5-Omni-7B

Mar 27, 2025

1.1 years ago

6mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (128,000 tokens)
Higher AI2D score (92.3% vs 83.2%)
Higher ChartQA score (85.5% vs 85.3%)
Higher GPQA score (46.7% vs 30.8%)
Higher MMMU score (60.3% vs 59.2%)
Higher MMMU-Pro score (45.2% vs 36.6%)
Alibaba Cloud / Qwen Team

Qwen2.5-Omni-7B

View details

Alibaba Cloud / Qwen Team

Higher DocVQA score (95.2% vs 90.1%)
Higher MATH score (71.5% vs 68.0%)
Higher MathVista score (67.9% vs 57.3%)
Higher TextVQA score (84.4% vs 73.5%)

Detailed Comparison

AI Model Comparison Table
Feature
Meta
Llama 3.2 90B Instruct
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B

FAQ

Common questions about Llama 3.2 90B Instruct vs Qwen2.5-Omni-7B

Llama 3.2 90B Instruct has a slight edge in benchmark performance. Llama 3.2 90B Instruct is made by Meta and Qwen2.5-Omni-7B 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%. Qwen2.5-Omni-7B scores DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%, ChartQA: 85.3%.
Llama 3.2 90B Instruct supports 128K tokens and Qwen2.5-Omni-7B 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 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 Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.