DeepSeek-V3 vs o1-mini
DeepSeek-V3 shows notably better performance in the majority of benchmarks. DeepSeek-V3 is 11.0x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V3 outperforms in 2 benchmarks (MATH-500, MMLU), while o1-mini is better at 1 benchmark (GPQA). DeepSeek-V3 shows notably better performance in the majority of benchmarks.
On price, DeepSeek-V3 is roughly 11.0x 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
- you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
- cost matters — it's about 11.0x 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-mini
- you want predictable pricing at $3.00/M input and $12.00/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3 outperforms in 2 benchmarks (MATH-500, MMLU), while o1-mini is better at 1 benchmark (GPQA).
DeepSeek-V3 shows notably better performance in the majority of 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 11.1x cheaper than o1-mini ($3.00/1M tokens).
For output processing, DeepSeek-V3 ($1.10/1M tokens) is 10.9x cheaper than o1-mini ($12.00/1M tokens).
In conclusion, o1-mini 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-mini's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while o1-mini is limited to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while o1-mini 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-mini was released on 2024-09-12.
DeepSeek-V3 is 3 months newer than o1-mini.
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-mini is available from OpenAI, Azure.
DeepSeek-V3
o1-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 and o1-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs o1-mini.