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Llama 3.1 70B Instruct vs QwQ-32B
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. 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
QwQ 32B was developed as a reasoning-focused model, designed to emphasize analytical thinking and problem-solving capabilities. Built with 32 billion parameters optimized for step-by-step reasoning, it demonstrates Qwen's exploration into models that prioritize deliberate analytical processing.
7 months newer
Llama 3.1 70B Instruct
Meta
2024-07-23
QwQ-32B
Alibaba Cloud / Qwen Team
2025-03-05
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Llama 3.1 70B Instruct
Average Score:71.3%
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QwQ-32B
Average Score:71.8%(+0.5%)
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Knowledge Cutoff
Training data recency comparison
QwQ-32B
2024-11-28
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 3.1 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:71.3%
Providers:9
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QwQ-32B
Avg Score:71.8%(+0.5%)
Providers:0