Model Comparison
DeepSeek-V3.2-Exp vs o1-miniWhich is better in 2026?
DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is 17.2x cheaper per token.
Verdict: DeepSeek-V3.2-Exp vs o1-mini — which is better?
DeepSeek-V3.2-Exp (by DeepSeek) and o1-mini (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-Exp outperforms in 1 benchmarks (GPQA), while o1-mini is better at 0 benchmarks. DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.
On price, DeepSeek-V3.2-Exp is roughly 17.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3.2-Exp also accepts a larger context window (163,840 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3.2-Exp if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- cost matters — it's about 17.2x cheaper per token
- you process long inputs — it offers a 163,840 token context window
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Choose o1-mini if…
- you want predictable pricing at $3.00/M input and $12.00/M output
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2-Exp outperforms in 1 benchmarks (GPQA), while o1-mini is better at 0 benchmarks.
DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 11.1x cheaper than o1-mini ($3.00/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 29.3x cheaper than o1-mini ($12.00/1M tokens).
In conclusion, o1-mini is more expensive than DeepSeek-V3.2-Exp.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V3.2-Exp accepts 163,840 input tokens compared to o1-mini's 128,000 tokens. Both models can generate responses up to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while o1-mini 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-Exp was released on 2025-09-29, while o1-mini was released on 2024-09-12.
DeepSeek-V3.2-Exp is 13 months newer than o1-mini.
Sep 29, 2025
10 months ago
1.0yr newerSep 12, 2024
1.9 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-Exp is available from Novita. o1-mini is available from OpenAI, Azure.
DeepSeek-V3.2-Exp
o1-mini
Outputs Comparison
Key Takeaways
DeepSeek-V3.2-Exp
View detailsDeepSeek
o1-mini
View detailsOpenAI
No standout differentiators in the data we have for this pair.
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and o1-mini side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V3.2-Exp vs o1-mini.