DeepSeek-V3.2-Exp vs o4-mini
DeepSeek-V3.2-Exp and o4-mini are closely matched at 28.2 and 27.5 on the LLM Stats Score. DeepSeek-V3.2-Exp is 6.3x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V3.2-Exp and o4-mini are closely matched on the overall LLM Stats Score at 28.2 and 27.5.
In the 6 individual benchmarks reported for both models, o4-mini wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3.2-Exp is roughly 6.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o4-mini also accepts a larger context window (200,000 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-V3.2-Exp
- cost matters — it's about 6.3x cheaper per token
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Choose o4-mini
- you value its reported benchmark strengths — it wins 4 of 6 exact shared results
- you process long inputs — it offers a 200,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
14 reported for DeepSeek-V3.2-Exp · 14 for o4-mini
DeepSeek-V3.2-Exp outperforms in 2 benchmarks (Aider-Polyglot, Humanity's Last Exam), while o4-mini is better at 4 benchmarks (AIME 2025, BrowseComp, GPQA, SWE-Bench Verified).
o4-mini 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-V3.2-Exp ($0.27/1M tokens) is 4.1x cheaper than o4-mini ($1.10/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 10.7x cheaper than o4-mini ($4.40/1M tokens).
In conclusion, o4-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
o4-mini accepts 200,000 input tokens compared to DeepSeek-V3.2-Exp's 163,840 tokens. o4-mini can generate longer responses up to 100,000 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
o4-mini supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
o4-mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
o4-mini
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while o4-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 o4-mini was released on 2025-04-16.
DeepSeek-V3.2-Exp is 6 months newer than o4-mini.
Sep 29, 2025
11 months ago
5mo newerApr 16, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while DeepSeek-V3.2-Exp's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without DeepSeek-V3.2-Exp's cutoff date.
—
May 2024
Provider Availability
DeepSeek-V3.2-Exp is available from Novita. o4-mini is available from OpenAI.
DeepSeek-V3.2-Exp
o4-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and o4-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Exp vs o4-mini.