DeepSeek-V3 vs o1-preview
o1-preview significantly outperforms across most benchmarks. DeepSeek-V3 is 55.0x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V3 outperforms in 1 benchmarks (SWE-Bench Verified), while o1-preview is better at 4 benchmarks (AIME 2024, GPQA, MMLU, SimpleQA). o1-preview significantly outperforms across most benchmarks.
On price, DeepSeek-V3 is roughly 55.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V3
- cost matters — it's about 55.0x 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 2024
- you need open weights you can self-host or fine-tune
Choose o1-preview
- you want the strongest raw capability — it leads on 4 of 5 shared benchmarks
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3 outperforms in 1 benchmarks (SWE-Bench Verified), while o1-preview is better at 4 benchmarks (AIME 2024, GPQA, MMLU, SimpleQA).
o1-preview significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 ($0.27/1M tokens) is 55.6x cheaper than o1-preview ($15.00/1M tokens).
For output processing, DeepSeek-V3 ($1.10/1M tokens) is 54.5x cheaper than o1-preview ($60.00/1M tokens).
In conclusion, o1-preview is more expensive than DeepSeek-V3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V3 accepts 131,072 input tokens compared to o1-preview's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while o1-preview is limited to 32,768 tokens.
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while o1-preview 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 was released on 2024-12-25, while o1-preview was released on 2024-09-12.
DeepSeek-V3 is 3 months newer than o1-preview.
Dec 25, 2024
1.7 years ago
3mo newerSep 12, 2024
2.0 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 is available from DeepSeek. o1-preview is available from OpenAI, Azure.
DeepSeek-V3
o1-preview
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 and o1-preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs o1-preview.