DeepSeek-V3 vs o1-preview
DeepSeek-V3 and o1-preview are closely matched at 15.7 and 16.6 on the LLM Stats Score. DeepSeek-V3 is 61.8x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V3 and o1-preview are closely matched on the overall LLM Stats Score at 15.7 and 16.6.
In the 5 individual benchmarks reported for both models, o1-preview wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 is roughly 61.8x 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V3
- cost matters — it's about 61.8x 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 value its reported benchmark strengths — it wins 4 of 5 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V3 · 8 for o1-preview
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.
Human preference
Blind head-to-head votes and playground 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 ($0.89/1M tokens) is 67.4x 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
1.8 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, DeepInfra. 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.