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Llama 3.1 70B Instruct vs Qwen2.5 VL 32B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 VL 32B Instruct leads with 3.1% higher average benchmark score. Qwen2.5 VL 32B Instruct supports multimodal inputs. Llama 3.1 70B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 3.1 70B was created as a balanced open-source model, designed to provide strong performance with 70 billion parameters while remaining practical for many deployment scenarios. Built to serve as a versatile foundation for fine-tuning and application development, it combines capability with accessibility in the open-source ecosystem.
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Alibaba Cloud / Qwen Team
Qwen2.5-VL 32B was developed as a mid-sized vision-language model, designed to balance multimodal capability with practical deployment considerations. Built with 32 billion parameters for vision and language integration, it serves applications requiring strong visual understanding without flagship-scale resources.
7 months newer
Llama 3.1 70B Instruct
Meta
2024-07-23
Qwen2.5 VL 32B Instruct
Alibaba Cloud / Qwen Team
2025-02-28
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Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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Llama 3.1 70B Instruct
Average Score:68.0%
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Qwen2.5 VL 32B Instruct
Average Score:71.2%(+3.1%)
Provider Availability & Performance
Available providers and their performance metrics
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Llama 3.1 70B Instruct
9 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Cerebras
Throughput: 1204 tok/s
Latency: 0.2ms
DeepInfra
Throughput: 25 tok/s
Latency: 0.5ms
Fireworks
Throughput: 32 tok/s
Latency: 0.5ms
Groq
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Llama 3.1 70B Instruct
Avg Score:68.0%
Providers:9
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Qwen2.5 VL 32B Instruct
Avg Score:71.2%(+3.1%)
Providers:0