DeepSeek-V4-Flash-0731 vs o4-mini
DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to 27.5. DeepSeek-V4-Flash-0731 is 21.4x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.7 to 27.5, ranking #35 overall.
On price, DeepSeek-V4-Flash-0731 is roughly 21.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 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-Flash-0731
- overall performance matters — it scores 44.7 and ranks #35 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 21.4x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
- you need open weights you can self-host or fine-tune
Choose o4-mini
- you want predictable pricing at $1.10/M input and $4.40/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for DeepSeek-V4-Flash-0731 · 14 for o4-mini
DeepSeek-V4-Flash-0731 and o4-minidon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.06/1M tokens) is 18.3x cheaper than o4-mini ($1.10/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 24.4x cheaper than o4-mini ($4.40/1M tokens).
In conclusion, o4-mini is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to o4-mini's 200,000 tokens. DeepSeek-V4-Flash-0731 can generate longer responses up to 1,048,576 tokens, while o4-mini is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
o4-mini supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
o4-mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
o4-mini
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while o4-mini 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-Flash-0731 was released on 2026-07-31, while o4-mini was released on 2025-04-16.
DeepSeek-V4-Flash-0731 is 16 months newer than o4-mini.
Jul 31, 2026
1 months ago
1.3yr newerApr 16, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while DeepSeek-V4-Flash-0731's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without DeepSeek-V4-Flash-0731's cutoff date.
—
May 2024
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Novita, Fireworks. o4-mini is available from OpenAI.
DeepSeek-V4-Flash-0731
o4-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and o4-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs o4-mini.