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DeepSeek-R1 vs Gemma 3n E2B Instructed
Comprehensive side-by-side LLM comparison
Gemma 3n E2B Instructed supports multimodal inputs. DeepSeek-R1 is available on 5 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1 was developed as a reasoning-focused language model, designed to combine chain-of-thought reasoning with reinforcement learning techniques. Built to excel at complex problem-solving through trial-and-error learning and deliberate analytical processes, it demonstrates the power of efficient training methods in open-source model development.
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Gemma 3N E2B IT was developed as the instruction-tuned version of Gemma 3N E2B, designed to follow user instructions while maintaining edge-optimized efficiency. Built for applications requiring both compact size and reliable instruction-following, it extends conversational AI to resource-constrained environments.
5 months newer
DeepSeek-R1
DeepSeek
2025-01-20
Gemma 3n E2B Instructed
2025-06-26
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Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E2B Instructed
2024-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-R1
5 providers
DeepInfra
Throughput: 0.9 tok/s
Latency: 0.3ms
DeepSeek
Throughput: 9 tok/s
Latency: 0.3ms
Fireworks
Throughput: 2.1 tok/s
Latency: 0.3ms
Together
Throughput: 4 tok/s
Latency: 0.6ms
ZeroEval
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DeepSeek-R1
Avg Score:0.0%
Providers:5
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Gemma 3n E2B Instructed
Avg Score:0.0%
Providers:0