DeepSeek-V4: 1.6 Trillion Parameters and a Lot of Open Questions
There isn't much officially confirmed about DeepSeek-V4 yet beyond its arxiv preprint. But what's in that paper is worth paying attention to.
Published on arXiv on 19 June 2026 (arXiv:2606.19348v1), the DeepSeek-V4 preview announcement describes two Mixture-of-Experts models at a scale that most labs aren't publicly talking about yet. The timing matters. This is fresh.
What DeepSeek-V4 Actually Is
DeepSeek-V4 is a preview release of two MoE (Mixture-of-Experts) language models from DeepSeek. The larger model, DeepSeek-V4-Pro, has 1.6 trillion total parameters with 49 billion activated at inference. The smaller, DeepSeek-V4-Flash, runs 284 billion total parameters with 13 billion activated. Both support a context window of one million tokens.
That context length is the number to focus on. One million tokens means these models can, in theory, ingest entire codebases, lengthy documentation sites, or large collections of web content in a single pass. Which changes how you think about what "getting cited" by a model like this even means.
The paper also mentions a hybrid attention architecture that combines Compressed Sparse Attention — though the full technical details are still emerging from the preprint.
Is DeepSeek-V4 Crawling the Web?
Honestly, we couldn't confirm this. The arXiv preprint describes the model architecture and capabilities, not its deployment infrastructure or data collection methods. There is no mention of a web crawler, user agent string, or live indexing pipeline in the available source material.
So: is DeepSeek-V4 crawling your website right now? We don't know. No official documentation exists yet on that question.
Does It Support LLMs.txt?
No information is available yet. The preprint makes no reference to LLMs.txt or any structured content protocol for AI model access. We couldn't confirm any stance from DeepSeek on this.
If you're already maintaining an llms.txt file for other AI systems, keep it. It costs nothing and the habit is good practice across the board. Check Uptrue's tools if you want a quick way to audit what AI-facing signals your site is currently sending.
Is There a Submission or Indexing Process?
No official submission or website indexing process has been announced for DeepSeek-V4. As of 19 June 2026, no such process exists in public documentation. If that changes, it'll likely appear in DeepSeek's official channels or an updated paper revision.
What Content Does It Favour?
The preprint doesn't specify training data sources or content preferences. We couldn't confirm what types of sites, formats, or content signals DeepSeek-V4 might weight when generating responses.
That said — the one million token context window is a meaningful clue. Models with long context capability tend to reward depth. Not keyword stuffing. Not thin overview pages. Dense, accurate, well-structured content that holds up when a model reads 50,000 words of it at once.
That's what you should be building anyway.
What Should Website Owners Do Right Now?
Not much panic is warranted yet. But a few things are worth doing.
Track whether you're being cited. If DeepSeek-V4 does go into production as a consumer-facing product, you'll want to know whether your content is showing up in its responses. Uptrue's AI Visibility feature is built exactly for this — tracking when and how AI models reference your site, so you're not flying blind.
Keep your content structured and substantive. Given the scale of these models and their long context capability, thin content is a real liability. Headers, clear argument structure, specific data points — these matter more than ever.
Don't fabricate signals you don't have. No submission URL exists. No confirmed user agent to whitelist. Anyone telling you otherwise right now is guessing. Use Uptrue's tracker to monitor actual traffic patterns and spot crawler activity if and when it shows up.
Watch the paper. arXiv preprints get updated. Version 1 dropped today. Version 2 may include deployment details, data sourcing notes, or API access information. Bookmark the abstract page and check back.
FAQ
What is DeepSeek-V4? DeepSeek-V4 is a preview series of two Mixture-of-Experts language models — DeepSeek-V4-Pro (1.6T parameters) and DeepSeek-V4-Flash (284B parameters) — both supporting one million token context windows, announced via arXiv preprint on 19 June 2026.
Is DeepSeek-V4 crawling websites? As of 19 June 2026, there is no confirmed information about DeepSeek-V4 operating a web crawler or using a specific user agent string.
How do I get my site cited by DeepSeek-V4? No official citation or indexing process has been announced. The best approach is to publish accurate, well-structured, substantive content and monitor your AI citation visibility using a tool like Uptrue.
Does DeepSeek-V4 support LLMs.txt? No information is available yet on whether DeepSeek-V4 reads or respects the LLMs.txt protocol.
Who made DeepSeek-V4? The preprint lists DeepSeek as the originating lab, though no specific individual authors are named in the available source material.