DeepSeek-V4.1-Flash vs o1-preview
DeepSeek-V4.1-Flash leads the LLM Stats Score 50.7 to 16.6. DeepSeek-V4.1-Flash is 79.5x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 50.7 to 16.6, ranking #17 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash is roughly 79.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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-V4.1-Flash
- overall performance matters — it scores 50.7 and ranks #17 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 79.5x cheaper per token
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
- you need open weights you can self-host or fine-tune
Choose o1-preview
- you want predictable pricing at $15.00/M input and $60.00/M output
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-V4.1-Flash · 8 for o1-preview
DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while o1-preview is better at 0 benchmarks.
DeepSeek-V4.1-Flash 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-V4.1-Flash ($0.22/1M tokens) is 68.2x cheaper than o1-preview ($15.00/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 90.9x cheaper than o1-preview ($60.00/1M tokens).
In conclusion, o1-preview is more expensive than DeepSeek-V4.1-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to o1-preview's 128,000 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while o1-preview is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas o1-preview does not.
DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4.1-Flash
o1-preview
License
Usage and distribution terms
DeepSeek-V4.1-Flash is licensed under MIT, while o1-preview 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-V4.1-Flash was released on 2026-09-10, while o1-preview was released on 2024-09-12.
DeepSeek-V4.1-Flash is 24 months newer than o1-preview.
Sep 10, 2026
1 months ago
2.0yr newerSep 12, 2024
2.1 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-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. o1-preview is available from OpenAI, Azure.
DeepSeek-V4.1-Flash
o1-preview
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and o1-preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs o1-preview.