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DeepSeek R1 Distill Qwen 32B vs Kimi K2-Instruct-0905
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1-Distill-Qwen-32B was created as a larger distilled variant, designed to transfer more of DeepSeek-R1's reasoning capabilities into a Qwen-based foundation. Built to serve applications requiring enhanced analytical depth, it represents a powerful option in the distilled reasoning model family.
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Moonshot AI
Kimi K2 Instruct-0905 represents a specific release iteration of the K2 Instruct model, developed to incorporate refinements and improvements. Built to provide enhanced instruction-following based on deployment feedback, it continues the evolution of Moonshot's instruction-tuned offerings.
7 months newer
DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20
Kimi K2-Instruct-0905
Moonshot AI
2025-09-05
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Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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DeepSeek R1 Distill Qwen 32B
Average Score:74.2%(+0.3%)
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Kimi K2-Instruct-0905
Average Score:74.0%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek R1 Distill Qwen 32B
1 providers
DeepInfra
Throughput: 37 tok/s
Latency: 0.65ms
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Kimi K2-Instruct-0905
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DeepSeek R1 Distill Qwen 32B
Avg Score:74.2%(+0.3%)
Providers:1
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Kimi K2-Instruct-0905
Avg Score:74.0%
Providers:0