DeepSeek-R1 vs Nova Pro
Comparing DeepSeek-R1 and Nova Pro across benchmarks, pricing, and capabilities.
DeepSeek · Amazon · Updated for 2026
Which is better?
DeepSeek-R1 and Nova Pro trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-R1 is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Nova Pro also accepts a larger context window (300,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-R1
- cost matters — it's about 1.5x cheaper per token
- you want the most recent training data — it shipped Jan 2025
- you need open weights you can self-host or fine-tune
Choose Nova Pro
- you process long inputs — it offers a 300,000 token context window
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-R1 · 27 for Nova Pro
DeepSeek-R1 and Nova Prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 1.5x cheaper than Nova Pro ($0.80/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 1.5x cheaper than Nova Pro ($3.20/1M tokens).
In conclusion, Nova Pro is more expensive than DeepSeek-R1.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Nova Pro accepts 300,000 input tokens compared to DeepSeek-R1's 131,072 tokens. Nova Pro can generate longer responses up to 300,000 tokens, while DeepSeek-R1 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Nova Pro supports multimodal inputs, whereas DeepSeek-R1 does not.
Nova Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1
Nova Pro
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Nova Pro uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Nova Pro was released on 2024-11-20.
DeepSeek-R1 is 2 months newer than Nova Pro.
Jan 20, 2025
1.6 years ago
2mo newerNov 20, 2024
1.8 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. Nova Pro is available from Bedrock.
DeepSeek-R1
Nova Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and Nova Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs Nova Pro.