DeepSeek-V3.2 (Thinking) vs Nova Pro
DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is 4.4x cheaper per token.
DeepSeek · Amazon · Updated for 2026
Which is better?
DeepSeek-V3.2 (Thinking) outperforms in 1 benchmarks (GPQA), while Nova Pro is better at 0 benchmarks. DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.
On price, DeepSeek-V3.2 (Thinking) is roughly 4.4x 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 benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V3.2 (Thinking)
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- cost matters — it's about 4.4x cheaper per token
- you want the most recent training data — it shipped Dec 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.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2 (Thinking) outperforms in 1 benchmarks (GPQA), while Nova Pro is better at 0 benchmarks.
DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 2.9x cheaper than Nova Pro ($0.80/1M tokens).
For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 7.6x cheaper than Nova Pro ($3.20/1M tokens).
In conclusion, Nova Pro is more expensive than DeepSeek-V3.2 (Thinking).*
* 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-V3.2 (Thinking)'s 131,072 tokens. Nova Pro can generate longer responses up to 300,000 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Nova Pro supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.
Nova Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2 (Thinking)
Nova Pro
License
Usage and distribution terms
DeepSeek-V3.2 (Thinking) 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-V3.2 (Thinking) was released on 2025-12-01, while Nova Pro was released on 2024-11-20.
DeepSeek-V3.2 (Thinking) is 13 months newer than Nova Pro.
Dec 1, 2025
8 months ago
1.0yr 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-V3.2 (Thinking) is available from DeepSeek. Nova Pro is available from Bedrock.
DeepSeek-V3.2 (Thinking)
Nova Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2 (Thinking) and Nova Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2 (Thinking) vs Nova Pro.