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DeepSeek-AI/DeepSeek-v3.2

DeepSeek aims to make its own AI chip

GitHub DeepSeek-AI/DeepSpec

DSpark: Speculative decoding accelerates LLM inference [pdf]

DeepSeek Made AI Cheap. Now It Needs Billions to Keep It Cheap

DeepSeek Slashes AI Costs to Cents

DeepSeek makes the V4 Pro price discount permanent

&gt; (3) The deepseek-v4-pro model API pricing will be officially adjusted to 1&#x2F;4 of the original price after the 75% discount promotion ends on 2026&#x2F;05&#x2F;31 15:59 UTC.<p><a href="https:&#x2F;&#x2F;x.com&#x2F;deepseek_ai&#x2F;status&#x2F;2057854261699195173" rel="nofollow">https:&#x2F;&#x2F;x.com&#x2F;deepseek_ai&#x2F;status&#x2F;2057854261699195173</a><p>Related ongoing thread:<p><i>DeepSeek reasonix, DeepSeek native coding agent with high caching and low cost</i> - <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=48256953">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=48256953</a> - May 2026 (135 comments)

Show HN: Stagewise – Agentic IDE for Your Z.ai/DeepSeek/Moonshot Subscription

DeepSeek: Thinking with Visual Primitives [pdf]

US State Department upgrades AI theft accusations to target China AI companies

The Download: DeepSeek's latest AI breakthrough, and the race to build world mo

DeepSeek drops input cache price to 1/10th

Ask HN: Why is cache for DeepSeek-v4 cheapest on Vercel AI Gateway?

Do they charge below their cost? Or do they run their own cache?<p>Vercel cache read: $0.01&#x2F;M for flash, $0.14&#x2F;M for pro.<p>Deepseek and OpenRouter cache read: $0.028&#x2F;M for flash, $0.145 for pro.<p>That&#x27;s a 64% discount on Vercel for flash, and a 3% discount for pro.<p>Links: Vercel - https:&#x2F;&#x2F;vercel.com&#x2F;ai-gateway&#x2F;models OpenRouter - https:&#x2F;&#x2F;openrouter.ai&#x2F;deepseek&#x2F;deepseek-v4-flash

DeepSeek V4 Flash

DeepSeek-V4

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek v4

<a href="https:&#x2F;&#x2F;api-docs.deepseek.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;api-docs.deepseek.com&#x2F;</a><p><a href="https:&#x2F;&#x2F;huggingface.co&#x2F;deepseek-ai&#x2F;DeepSeek-V4-Pro&#x2F;blob&#x2F;main&#x2F;DeepSeek_V4.pdf" rel="nofollow">https:&#x2F;&#x2F;huggingface.co&#x2F;deepseek-ai&#x2F;DeepSeek-V4-Pro&#x2F;blob&#x2F;main...</a>

DeepSeek-V4 Technical Report [pdf]

What happened to Deepseek?

Meta had a comeback - arguably not opensource, but still - but Deepseek just seems to have vanished from the scene. What happened? Will we ever see Deepseek V4?

From Twitter/X: DeepSeek is rolling out a limited V4 gray release.

Source: https://x.com/i/status/2041458478569689589

Gemma 4 just casually destroyed every model on our leaderboard except Opus 4.6 and GPT-5.2. 31B params, $0.20/run

Tested Gemma 4 (31B) on our benchmark. Genuinely did not expect this. 100% survival, 5 out of 5 runs profitable, +1,144% median ROI. At $0.20 per run. It outperforms GPT-5.2 ($4.43/run), Gemini 3 Pro ($2.95/run), Sonnet 4.6 ($7.90/run), and absolutely destroys every Chinese open-source model we've tested — Qwen 3.5 397B, Qwen 3.5 9B, DeepSeek V3.2, GLM-5. None of them even survive consistently. The only model that beats Gemma 4 is Opus 4.6 at $36 per run. That's 180× more expensive. 31 billion parameters. Twenty cents. We double-checked the config, the prompt, the model ID — everything is identical to every other model on the leaderboard. Same seed, same tools, same simulation. It's just this good. Strongly recommend trying it for your agentic workflows. We've tested 22 models so far and this is by far the best cost-to-performance ratio we've ever seen. Full breakdown with charts and day-by-day analysis: foodtruckbench.com/blog/gemma-4-31b FoodTruck Bench is an AI business simulation benchmark — the agent runs a food truck for 30 days, making decisions about location, menu, pricing, staff, and inventory. Leaderboard at foodtruckbench.com EDIT — Gemma 4 26B A4B results are in. Lots of you asked about the 26B A4B variant. Ran 5 simulations, here's the honest picture: 60% survival (3/5 completed, 2 bankrupt). Median ROI: +119%, Net Worth: $4,386. Cost: $0.31/run. Placed #7 on the leaderboard — above every Chinese model and Sonnet 4.5, below everything else. Both bankruptcies were loan defaults — same pattern we see across models. The 3 surviving runs were solid, especially the best one at +296% ROI. But here's the catch. The 26B A4B is the only model out of 23 tested that required custom output sanitization to function. It produces valid tool-call intent, but the JSON formatting is consistently broken — malformed quotes, trailing garbage tokens, invalid escapes. I had to build a 3-stage sanitizer specifically for this model. No other model needed anything like this. The business decisions themselves are unmodified — the sanitizer only fixes JSON formatting, not strategy. But if you're planning to use this model in agentic workflows, be prepared to handle its output format. It does not produce clean function calls out of the box. TL;DR: 31B dense → 100% survival, $0.20/run, #3 overall. 26B A4B → 60% survival, $0.31/run, #7 overall, but requires custom output parsing. The 31B is the clear winner. Updated leaderboard: foodtruckbench.com

One year ago DeepSeek R1 was 25 times bigger than Gemma 4

I'm mind blown by the fact that about a year ago DeepSeek R1 came out with a MoE architecture at 671B parameters and today Gemma 4 MoE is only 26B and is genuinely impressive. It's 25 times smaller, but is it 25 times worse? I'm exited about the future of local LLMs.

China's DeepSeek AI chatbot suffers longest outage

DeepSeek Employee Teases "Massive" New Model Surpassing DeepSeek V3.2

Translated by Nano Banana https://preview.redd.it/8bfh5zk1q6rg1.png?width=1158&format=png&auto=webp&s=9d8e6c2f285ba04527f0e9578f9ca7b75124c11f https://preview.redd.it/jpa7aikcr6rg1.png?width=688&format=png&auto=webp&s=2a35594f8ff5eb5f2cd18ad2f4de6662f2898b1d Note: The employee just deleted his reply; it seems he said something he shouldn't have. Original post: http://xhslink.com/o/3ct3YOygvNN