DeepSeek-V3.2 (Non-thinking) vs DeepSeek-V3
Comparing DeepSeek-V3.2 (Non-thinking) and DeepSeek-V3 across benchmarks, pricing, and capabilities.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V3.2 (Non-thinking) and DeepSeek-V3 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V3.2 (Non-thinking) is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V3.2 (Non-thinking)
- cost matters — it's about 1.3x cheaper per token
- you want the most recent training data — it shipped Dec 2025
Choose DeepSeek-V3
- you want predictable pricing at $0.27/M input and $0.89/M output
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-V3.2 (Non-thinking) · 20 for DeepSeek-V3
DeepSeek-V3.2 (Non-thinking) and DeepSeek-V3don'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-V3.2 (Non-thinking) ($0.28/1M tokens) is 1.0x more expensive than DeepSeek-V3 ($0.27/1M tokens).
For output processing, DeepSeek-V3.2 (Non-thinking) ($0.42/1M tokens) is 2.1x cheaper than DeepSeek-V3 ($0.89/1M tokens).
In conclusion, DeepSeek-V3 is more expensive than DeepSeek-V3.2 (Non-thinking).*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3.2 (Non-thinking) has 14.0B more parameters than DeepSeek-V3, making it 2.1% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while DeepSeek-V3.2 (Non-thinking) is limited to 8,192 tokens.
License
Usage and distribution terms
DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while DeepSeek-V3 uses MIT + Model License (Commercial use allowed).
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
MIT + Model License (Commercial use allowed)
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while DeepSeek-V3 was released on 2024-12-25.
DeepSeek-V3.2 (Non-thinking) is 11 months newer than DeepSeek-V3.
Dec 1, 2025
9 months ago
11mo newerDec 25, 2024
1.7 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 (Non-thinking) is available from DeepSeek. DeepSeek-V3 is available from DeepSeek, DeepInfra.
DeepSeek-V3.2 (Non-thinking)
DeepSeek-V3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2 (Non-thinking) and DeepSeek-V3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2 (Non-thinking) vs DeepSeek-V3.