DeepSeek-V3 vs Nova Pro
DeepSeek-V3 and Nova Pro are closely matched at 15.7 and 12.4 on the LLM Stats Score. DeepSeek-V3 is 2.9x cheaper per token.
DeepSeek · Amazon · Updated for 2026
Which is better?
DeepSeek-V3 and Nova Pro are closely matched on the overall LLM Stats Score at 15.7 and 12.4.
In the 4 individual benchmarks reported for both models, DeepSeek-V3 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 is roughly 2.9x 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-V3
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
- cost matters — it's about 2.9x cheaper per token
- you want the most recent training data — it shipped Dec 2024
- 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V3 · 27 for Nova Pro
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.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
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
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.
Input capabilities
Documented input modalities across available providers
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
Nova Pro
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.
MIT + Model License (Commercial use allowed)
Open weights
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.
Dec 25, 2024
1.7 years ago
1mo 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-V3 is available from DeepSeek. Nova Pro is available from Bedrock.
DeepSeek-V3
Nova Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 and Nova Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs Nova Pro.