DeepSeek-V3 0324 vs o3
o3 leads the LLM Stats Score 31.1 to 13.4. DeepSeek-V3 0324 is 8.6x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
o3 leads the overall LLM Stats Score 31.1 to 13.4, ranking #113 overall.
In the 2 individual benchmarks reported for both models, o3 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 0324 is roughly 8.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o3 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 0324
- cost matters — it's about 8.6x cheaper per token
- you need open weights you can self-host or fine-tune
Choose o3
- overall performance matters — it scores 31.1 and ranks #113 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 200,000 token context window
- you want the most recent training data — it shipped Apr 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for DeepSeek-V3 0324 · 22 for o3
DeepSeek-V3 0324 outperforms in 0 benchmarks, while o3 is better at 2 benchmarks (AIME 2024, GPQA).
o3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 0324 ($0.24/1M tokens) is 8.3x cheaper than o3 ($2.00/1M tokens).
For output processing, DeepSeek-V3 0324 ($0.90/1M tokens) is 8.9x cheaper than o3 ($8.00/1M tokens).
In conclusion, o3 is more expensive than DeepSeek-V3 0324.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o3 accepts 200,000 input tokens compared to DeepSeek-V3 0324's 163,840 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while o3 is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
o3 supports multimodal inputs, whereas DeepSeek-V3 0324 does not.
o3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3 0324
o3
License
Usage and distribution terms
DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while o3 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3 0324 was released on 2025-03-25, while o3 was released on 2025-04-16.
o3 is 1 month newer than DeepSeek-V3 0324.
Mar 25, 2025
1.5 years ago
Apr 16, 2025
1.4 years ago
3w newerKnowledge Cutoff
When training data ends
o3 has a documented knowledge cutoff of 2024-05-31, while DeepSeek-V3 0324's cutoff date is not specified.
We can confirm o3's training data extends to 2024-05-31, but cannot make a direct comparison without DeepSeek-V3 0324's cutoff date.
—
May 2024
Provider Availability
DeepSeek-V3 0324 is available from DeepInfra, Novita. o3 is available from OpenAI.
DeepSeek-V3 0324
o3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 and o3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 0324 vs o3.