Model Comparison

DeepSeek-R1 vs Nova Pro

Comparing DeepSeek-R1 and Nova Pro across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Nova Pro 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

DeepSeek-R1 costs less

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

Lowest available price from all providers
Fri Apr 03 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
Amazon
Nova Pro
Input tokens$0.80
Output tokens$3.20
Best providerAWS Bedrock
Notice missing or incorrect data?Start an Issue→

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.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Amazon
Nova Pro
Input300,000 tokens
Output300,000 tokens
Fri Apr 03 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Text
Images
Audio
Video

Nova Pro

Text
Images
Audio
Video

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.

DeepSeek-R1

MIT

Open weights

Nova Pro

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.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

2mo newer
Nova Pro

Nov 20, 2024

1.4 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Nova Pro is available from Bedrock.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

Nova Pro

bedrock logo
AWS Bedrock
Input Price:Input: $0.80/1MOutput Price:Output: $3.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Has open weights
Amazon
Larger context window (300,000 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
Amazon
Nova Pro

FAQ

Common questions about DeepSeek-R1 vs Nova Pro

DeepSeek-R1 (DeepSeek) and Nova Pro (Amazon) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Nova Pro scores ARC-C: 94.8%, GSM8k: 94.8%, DocVQA: 93.5%, IFEval: 92.1%, ChartQA: 89.2%.
DeepSeek-R1 is 1.5x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Nova Pro costs $0.80/M input and $3.20/M output via bedrock.
DeepSeek-R1 supports 131K tokens and Nova Pro supports 300K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 300K), input pricing ($0.55 vs $0.80/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1 is developed by DeepSeek and Nova Pro is developed by Amazon.