--- title: Intelligence, Performance & Price Analysis | daily.dev description: DeepSeek V4 Flash 0731 is a reasoning-capable, open-weights MoE model with 284B total parameters (13B active) released July 31, 2026. It scores 50 on the... canonical: https://daily.dev/posts/intelligence-performance-price-analysis-uowbhxnia twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Intelligence, Performance & Price Analysis | daily.dev og:description: DeepSeek V4 Flash 0731 is a reasoning-capable, open-weights MoE model with 284B total parameters (13B active) released July 31, 2026. It scores 50 on the... og:url: https://daily.dev/posts/intelligence-performance-price-analysis-uowbhxnia og:image: https://api.daily.dev/og/posts/UOWbHxNia.png og:image:alt: Intelligence, Performance & Price Analysis og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Intelligence, Performance & Price Analysis **[Hacker News](https://daily.dev/sources/hn)** · 5 min read · 10 upvotes · 0 comments ## Summary DeepSeek V4 Flash 0731 is a reasoning-capable, open-weights MoE model with 284B total parameters (13B active) released July 31, 2026. It scores 50 on the Artificial Analysis Intelligence Index, well above the median of 25 for comparable open-weight models. Pricing is highly competitive at $0.14/1M input tokens and $0.28/1M output tokens. The model supports a 1M token context window, is available via API, and is released under the MIT license allowing commercial use. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Community take How the wider developer community reacted, aggregated from 1 discussion and 548 comments across hackernews (as of 2026-08-01). **TL;DR:** The community is broadly enthusiastic about DeepSeek V4 Flash's cost-effectiveness and quality, with many sharing concrete examples of near-zero API costs; side threads debate potential bans on Chinese open-weight models and geopolitical implications. **Sentiment:** 55% positive · 30% mixed · 15% skeptical **The case for** - DeepSeek V4 Flash offers dramatically lower API costs compared to subscription-based frontier models, with some users spending under $2/week for heavy use. - The model quality has noticeably improved, especially at following instructions, making it competitive for most everyday coding tasks. - Open weights were released on Hugging Face, enabling self-hosting and further distillation. - A new updated V4 Pro is reportedly coming soon, potentially raising the ceiling further. **The pushback** - Data privacy is a serious concern when using DeepSeek's hosted API, with no meaningful opt-out from data collection for training. - The model lacks image/vision support, limiting autonomous debugging of certain issues. - Some worry China may eventually stop open-sourcing models once they dominate the market, mirroring historical 'dump and pump' strategies. - Potential US regulatory action could make using Chinese open-weight models legally risky for companies, especially those with government contracts. **By community** - hackernews (mixed): Mostly positive on cost and quality of DeepSeek V4 Flash, but with significant side debates around data privacy, geopolitics, potential bans, and EU/China competitiveness that dilute the overall enthusiasm. **Hottest debate:** Whether the US government will ban or restrict use of Chinese open-weight models, and whether such a ban would even be enforceable. **Open questions** - Will DeepSeek or the CCP eventually close off open-weight model releases as the technology matures? - How can enterprises realistically address data privacy and legal liability when using DeepSeek's hosted API? - When will DeepSeek V4 Pro (updated) be released and how will it compare to top frontier models like Opus 5? **Highlights** > The issue for me is the data privacy if you're using their hosted prices, because you cannot opt out of data collection (and I'm not sure how you'd legally follow up on it if they did offer it, but didn't actually follow through). That means all of my code is being retained for training. I've used it in some open source code though, and loved how fast it was. My mind is changing on how valuable my code actually is though... it's the complete picture, how it's put together, the design, the UI, the attention to detail that's the real value. > — [rapind on hackernews](https://news.ycombinator.com/item?id=49123709) > I'm not a heavy user of agentic coding, but still use them quite a bit for some automation here and there. I've been going around shopping all the ~$10 subscriptions and I finally settled on openrouter + ds4 pro. The more intensive days cost me $1 and I set a $2 weekly limit which I've never hit the past 3 weeks, to me it's way cheaper than most subscriptions and I don't have to worry about maximizing my weekly quota/resets. > — [nodja on hackernews](https://news.ycombinator.com/item?id=49124933) > Hell, the US doesn't even need to act. I claim the CCP will wise up within 2 years, possibly much much sooner, and ban their own companies from open sourcing to prevent the Americans from acquiring the capabilities. Despite all the nonsense claims of China distilling US models, the reality is that the Americans absolutely do distill these free Chinese models, and distillation when full logprobs are available (i.e. you have access to the weights of the model) is an order of magnitude better than when you don't. Yes, Chinese open weight models in the short term harm US closed source model providers bottom line. In the slightly longer term, "showing your hand" and publishing both the architecture innovations and the models weights will be too dangerous for the CCP to allow. This is triply true if they can release a model that beats the Americans on most benchmarks. I've already warned investors that this is probably the closest open weight models will ever get to closed access. > — [Der\_Einzige on hackernews · 3 comments](https://news.ycombinator.com/item?id=49122641) > The weights were just released a few minutes ago: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 > — [coder543 on hackernews · 3 comments](https://news.ycombinator.com/item?id=49122435) > I have one of my projects on DeepSeek and it blows my mind how I can use tens of millions of tokens for pennies. I don't find it suitable for everything, but there's some tasks it crushes for what feels like almost free. > — [singingtoday on hackernews](https://news.ycombinator.com/item?id=49125143) **Source threads** - [hackernews](https://news.ycombinator.com/item?id=49120299) · 466 points · 548 comments ## Similar posts on daily.dev - [Models & Pricing](https://daily.dev/posts/models-pricing-6vw4gyejf) · Hacker News · 2 upvotes · 0 comments - [DeepSeek V4—almost on the frontier, a fraction of the price](https://daily.dev/posts/deepseek-v4-almost-on-the-frontier-a-fraction-of-the-price-xfglgl9rp) · Simon Willison · 7 upvotes · 0 comments - [DeepSeek previews new AI model that ‘closes the gap’ with frontier models](https://daily.dev/posts/deepseek-previews-new-ai-model-that-closes-the-gap-with-frontier-models-7lqiiymer) · TechCrunch · 0 upvotes · 0 comments --- Tags: [#ai](https://daily.dev/tags/ai), [#llm](https://daily.dev/tags/llm), [#deepseek](https://daily.dev/tags/deepseek), [#mixture-of-experts](https://daily.dev/tags/mixture-of-experts) [View this post on daily.dev](https://daily.dev/posts/intelligence-performance-price-analysis-uowbhxnia) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Intelligence, Performance & Price Analysis","url":"https://daily.dev/posts/intelligence-performance-price-analysis-uowbhxnia","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/intelligence-performance-price-analysis-uowbhxnia"},"datePublished":"2026-07-31T16:52:56.411Z","dateModified":"2026-08-01T08:11:49.081Z","description":"DeepSeek V4 Flash 0731 is a reasoning-capable, open-weights MoE model with 284B total parameters (13B active) released July 31, 2026. 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