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Llama 4 Scout vs Qwen2.5-Coder 32B Instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Llama 4 Scout offers 19.7M more tokens in context window than Qwen2.5-Coder 32B Instruct. Both models have similar pricing. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 4 Scout was created as an exploratory variant in the Llama 4 family, designed to investigate new architectures and optimization strategies. Built as part of Meta's commitment to advancing open-source AI, it serves as a testbed for innovations that may inform future model releases.
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Alibaba Cloud / Qwen Team
Qwen 2.5 Coder 32B was developed as a specialized coding model, designed to excel at programming tasks with 32 billion parameters specifically optimized for code. Built to understand and generate code across multiple programming languages, it serves developers requiring advanced code completion, debugging, and explanation capabilities.
6 months newer
Qwen2.5-Coder 32B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
Llama 4 Scout
Meta
2025-04-05
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Pricing Comparison
Cost per million tokens (USD)
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Llama 4 Scout
Input:$0.08
Output:$0.30
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Qwen2.5-Coder 32B Instruct
Input:$0.09
Output:$0.09($0.20 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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Llama 4 Scout
Average Score:61.0%(+0.1%)
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Qwen2.5-Coder 32B Instruct
Average Score:60.9%
Provider Availability & Performance
Available providers and their performance metrics
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Llama 4 Scout
6 providers
DeepInfra
Throughput: 76.1 tok/s
Latency: 0.31ms
Fireworks
Throughput: 116.1 tok/s
Latency: 0.53ms
Groq
Throughput: 776.1 tok/s
Latency: 1.08ms
Lambda
Throughput: 139.7 tok/s
Latency: 0.43ms
Novita
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Llama 4 Scout
Avg Score:61.0%(+0.1%)
Providers:6
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Qwen2.5-Coder 32B Instruct
Avg Score:60.9%
Providers:4