DeepSeek-R1 vs Llama 3.2 90B Instruct Comparison
Comparing DeepSeek-R1 and Llama 3.2 90B Instruct across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Llama 3.2 90B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 1.6x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 5.5x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than Llama 3.2 90B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1 has 581.0B more parameters than Llama 3.2 90B Instruct, making it 645.6% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1 accepts 131,072 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Llama 3.2 90B Instruct is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Llama 3.2 90B Instruct supports multimodal inputs, whereas DeepSeek-R1 does not.
Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1
Llama 3.2 90B Instruct
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Llama 3.2 90B Instruct uses Llama 3.2.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.2
Open weights
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Llama 3.2 90B Instruct was released on 2024-09-25.
DeepSeek-R1 is 4 months newer than Llama 3.2 90B Instruct.
Jan 20, 2025
1.2 years ago
3mo newerSep 25, 2024
1.5 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic. The availability of providers can affect quality of the model and reliability.
DeepSeek-R1
Llama 3.2 90B Instruct
Outputs Comparison
Key Takeaways
DeepSeek-R1
View detailsDeepSeek
Detailed Comparison
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