Introducing everything about DeepSeek V4 Flash 0731—the AI that boosted its performance by 10 points just by refining its internal training and configuration, without needing to 'rebuild' its foundation.
Imagine this: your AI assistant, which until yesterday could barely fix a typo in your writing, suddenly starts churning out complex programming code and managing your busy schedule all by itself this morning. The outward appearance of the AI (the model architecture) is exactly the same as it was yesterday. It’s as if an athlete, who until yesterday was only doing basic physical conditioning, suddenly completes tactical training and displays national-team-level performance overnight. This is the story of “DeepSeek V4 Flash 0731,” released on July 31, 2026. [Source: DeepSeek V4 Flash: Official Release, Explained]
Why It Matters
Until now, we’ve assumed that for AI performance to improve, we inevitably needed bigger and more expensive models. However, this 0731 update shattered that conventional wisdom. It demonstrated that even with a model of the same scale, performance can make a massive jump depending on “how you educate it.”
For businesses, this is an opportunity to drastically lower the cost of technology adoption; for users like us, it means our daily task assistants are becoming smarter and more affordable. [Source: DeepSeek V4 Flash 0731 update drops: GPT-5.6 performance at 60% less cost]
The Explainer
To understand DeepSeek V4 Flash 0731, you first need to understand the difference between an AI’s “brain size” and its “teaching method.”
This model is a “Mixture-of-Experts” model (a structure that selectively uses expert neural networks for required situations) with 284 billion parameters (connection links that process complex information inside the AI brain). [Source: DeepSeek V4 Flash: Official Release, Explained] In the 0731 update, the development team did not increase this “brain scale,” but instead went through a process called “additional post-training.”
Simply put, if the original basic training was “the process of reading textbooks at school,” this update was “the process of mastering coding and tool-usage skills by solving countless practical workbooks.” Through this process alone, the model’s intelligence increased by 10 points compared to before. [Source: DeepSeek V4 Flash 0731 scores 50 on the Artificial Analysis Intelligence Index, 10 points above previous DeepSeek V4 Flash]
Where We Stand
According to the indicators from “Artificial Analysis,” a credible AI analysis institution, DeepSeek V4 Flash 0731 recorded an intelligence score of 50 points. This is only a 1-point difference from the industry’s top-tier GPT-5.6 Luna (51 points). [Source: DeepSeek V4 Flash 0731 scores 50 on the Artificial Analysis Intelligence Index, 10 points above previous DeepSeek V4 Flash, Source: DeepSeek-v4-Flash-0731 Scores 50 On Artificial Analysis Intelligence Index, Creates Big Spike On Pareto Frontier]
The most surprising thing is the price. Even though OpenAI drastically lowered the price of GPT-5.6 Luna, DeepSeek V4 Flash 0731 provides a similar level of intelligence at a price 60% cheaper. [Source: DeepSeek V4 Flash 0731 scores 50 on the Artificial Analysis Intelligence Index, 10 points above previous DeepSeek V4 Flash]
Moreover, this model even outperformed “V4 Pro,” which was classified as DeepSeek’s flagship model, in agent performance benchmarks (tests measuring an AI’s ability to set its own goals and use tools to solve problems), hitting a peak in cost-effectiveness. [Source: DeepSeek Retrained V4-Flash Beats Its Flagship Pro on Nine Agent Benchmarks]
What’s Next
The AI market of the future will move away from the competition of simply bloating in size and toward a competition of how efficiently a model can be trained, just like this DeepSeek example.
In particular, the improvement in coding and agent task capabilities shown in the 0731 version is, metaphorically speaking, like an assistant who has mastered foreign languages and coding. We can now give complex commands to our AI assistants, like “Organize the data, draft a report, and even register the schedule on my calendar,” more easily and cheaply. Now, what’s important in the AI market is not the “size of the model” but its “practical utility.”
AI’s Take
MindTickleBytes’ AI Reporter’s perspective: This instance, where performance was boosted by improving “training methods” while keeping the model’s core architecture intact, is a significant milestone showing that AI development is moving beyond simply pursuing size and entering an era of efficiency. DeepSeek’s move to break through the wall of cost-effectiveness is accelerating a world where more people can freely use AI.
References
- DeepSeek V4 Flash 0731 (max) - Intelligence, Performance & Price Analysis
- DeepSeek V4 Flash 0731 scores 50 on the Artificial Analysis Intelligence Index, 10 points above previous DeepSeek V4 Flash
- DeepSeek-v4-Flash-0731 Scores 50 On Artificial Analysis Intelligence Index, Creates Big Spike On Pareto Frontier
- Artificial Analysis on X: DeepSeek V4 Flash 0731 scores 50 on the Artificial Analysis Intelligence Index
- DeepSeek-V4-Flash-0731: Codex Support, $0.14/$0.28 Pricing
- DeepSeek V4 Flash 0731 - Pricing & Benchmarks 2026
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[DeepSeek V4 Flash 0731 Intelligence, Performance and Price Analysis Hacker News](https://news.ycombinator.com/item?id=49120299) - DeepSeek V4 Flash - Intelligence, Performance & Price Analysis
- DeepSeek-V4-Flash-0731: Codex Support, $0.14/$0.28 Pricing
- DeepSeek V4 Flash: Official Release, Explained
- DeepSeek V4 Flash 0731 update drops: GPT-5.6 performance at 60% less cost
- DeepSeek Retrained V4-Flash Beats Its Flagship Pro on Nine Agent Benchmarks
- The entire model architecture structure was completely replaced
- Intelligence was improved through additional post-training
- The number of parameters was doubled
- 40 points
- 50 points
- 60 points
- It is about 60% cheaper than GPT-5.6 Luna
- The cost is identical
- It is 80% more expensive than GPT-5.6 Luna