Model Comparison

DeepSeek-V3 vs Nova Pro

DeepSeek-V3 shows notably better performance in the majority of benchmarks. DeepSeek-V3 is 2.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3 outperforms in 3 benchmarks (DROP, GPQA, MMLU), while Nova Pro is better at 1 benchmark (IFEval).

DeepSeek-V3 shows notably better performance in the majority of benchmarks.

Wed Apr 08 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3 costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 3.0x cheaper than Nova Pro ($0.80/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 2.9x cheaper than Nova Pro ($3.20/1M tokens).

In conclusion, Nova Pro is more expensive than DeepSeek-V3.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Apr 08 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
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-V3's 131,072 tokens. Nova Pro can generate longer responses up to 300,000 tokens, while DeepSeek-V3 is limited to 131,072 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Amazon
Nova Pro
Input300,000 tokens
Output300,000 tokens
Wed Apr 08 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Nova Pro supports multimodal inputs, whereas DeepSeek-V3 does not.

Nova Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3

Text
Images
Audio
Video

Nova Pro

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Nova Pro uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Nova Pro

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Nova Pro was released on 2024-11-20.

DeepSeek-V3 is 1 month newer than Nova Pro.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

1mo 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-V3 is available from DeepSeek. Nova Pro is available from Bedrock.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

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

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Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher DROP score (91.6% vs 85.4%)
Higher GPQA score (59.1% vs 46.9%)
Higher MMLU score (88.5% vs 85.9%)
Amazon
Larger context window (300,000 tokens)
Supports multimodal inputs
Higher IFEval score (92.1% vs 86.1%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Amazon
Nova Pro

FAQ

Common questions about DeepSeek-V3 vs Nova Pro

DeepSeek-V3 shows notably better performance in the majority of benchmarks. DeepSeek-V3 is made by DeepSeek and Nova Pro is made by Amazon. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Nova Pro scores ARC-C: 94.8%, GSM8k: 94.8%, DocVQA: 93.5%, IFEval: 92.1%, ChartQA: 89.2%.
DeepSeek-V3 is 3.0x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Nova Pro costs $0.80/M input and $3.20/M output via bedrock.
DeepSeek-V3 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 ($0.27 vs $0.80/M), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Nova Pro is developed by Amazon.