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Llama 3.2 11B Instruct vs Qwen2.5 72B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 72B Instruct leads with 16.7% higher average benchmark score. Llama 3.2 11B Instruct offers 116.7K more tokens in context window than Qwen2.5 72B Instruct. Llama 3.2 11B Instruct is $0.65 cheaper per million tokens. Llama 3.2 11B Instruct supports multimodal inputs. Llama 3.2 11B Instruct is available on 6 providers. Overall, Qwen2.5 72B Instruct is the stronger choice for coding tasks.
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Meta
Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Meta's latest advancement in AI technology.
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Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 77.4% across 14 benchmarks. It excels particularly in GSM8k (95.8%), MT-Bench (93.5%), MBPP (88.2%). It supports a 139K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
6 days newer
Qwen2.5 72B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
Llama 3.2 11B Instruct
Meta
2024-09-25
Pricing Comparison
Cost per million tokens (USD)
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Llama 3.2 11B Instruct
Input:$0.05
Output:$0.05($0.65 cheaper)
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Qwen2.5 72B Instruct
Input:$0.35
Output:$0.40
Performance Metrics
Context window and performance specifications
Average performance across 23 common benchmarks
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Llama 3.2 11B Instruct
Average Score:30.4%
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Qwen2.5 72B Instruct
Average Score:47.1%(+16.7%)
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Knowledge Cutoff
Training data recency comparison
Llama 3.2 11B Instruct
2023-12-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Llama 3.2 11B Instruct
6 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
DeepInfra
Throughput: 108 tok/s
Latency: 0.5ms
Fireworks
Throughput: 125 tok/s
Latency: 0.2ms
Groq
Throughput: 100 tok/s
Latency: 0.5ms
Sambanova
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Llama 3.2 11B Instruct
Avg Score:30.4%
Providers:6
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Qwen2.5 72B Instruct
Avg Score:47.1%(+16.7%)
Providers:4