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DeepSeek-R1 vs IBM Granite 4.0 Tiny Preview
Comprehensive side-by-side LLM comparison
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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IBM
Granite 4.0 Tiny Preview was introduced as an experimental ultra-compact model, designed to demonstrate IBM's progress in efficient model development. Built to explore the boundaries of what small models can achieve for enterprise applications, it represents an early look at next-generation Granite capabilities.
3 months newer
DeepSeek-R1
DeepSeek
2025-01-20
IBM Granite 4.0 Tiny Preview
IBM
2025-05-02
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Performance Metrics
Context window and performance specifications
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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IBM Granite 4.0 Tiny Preview
Avg Score:0.0%
Providers:0