Model Comparison
DeepSeek-V3.2 (Thinking) vs o1-previewWhich is better in 2026?
DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is 83.3x cheaper per token.
Verdict: DeepSeek-V3.2 (Thinking) vs o1-preview — which is better?
DeepSeek-V3.2 (Thinking) (by DeepSeek) and o1-preview (by OpenAI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V3.2 (Thinking) outperforms in 2 benchmarks (GPQA, SWE-Bench Verified), while o1-preview is better at 0 benchmarks. DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.
On price, DeepSeek-V3.2 (Thinking) is roughly 83.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3.2 (Thinking) also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3.2 (Thinking) if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 83.3x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Dec 2025
- you need open weights you can self-host or fine-tune
Choose o1-preview if…
- you want predictable pricing at $15.00/M input and $60.00/M output
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2 (Thinking) outperforms in 2 benchmarks (GPQA, SWE-Bench Verified), while o1-preview is better at 0 benchmarks.
DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 53.6x cheaper than o1-preview ($15.00/1M tokens).
For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 142.9x cheaper than o1-preview ($60.00/1M tokens).
In conclusion, o1-preview 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
DeepSeek-V3.2 (Thinking) accepts 131,072 input tokens compared to o1-preview's 128,000 tokens. DeepSeek-V3.2 (Thinking) can generate longer responses up to 65,536 tokens, while o1-preview is limited to 32,768 tokens.
License
Usage and distribution terms
DeepSeek-V3.2 (Thinking) is licensed under MIT, while o1-preview 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 o1-preview was released on 2024-09-12.
DeepSeek-V3.2 (Thinking) is 15 months newer than o1-preview.
Dec 1, 2025
6 months ago
1.2yr newerSep 12, 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. o1-preview is available from OpenAI, Azure.
DeepSeek-V3.2 (Thinking)
o1-preview
Outputs Comparison
Key Takeaways
o1-preview
View detailsOpenAI
No standout differentiators in the data we have for this pair.
Detailed Comparison
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FAQ
Common questions about DeepSeek-V3.2 (Thinking) vs o1-preview.