Image created with gemini-2.5-flash-image with claude-sonnet-4-5. Image prompt: Minimalist data center with single illuminated server rack in endless corridor of polished black marble and chrome, deep blue LED light reflecting infinitely in mirror-polished floors, dramatic perspective vanishing point, cold architectural emptiness, untouched pristine technology, bold white sans-serif text ‘DEEPSEEK’ overlaid, cinematic lighting with deep shadows, no people, ultra-wide angle, luxury tech isolation
🚨New Models in the Arena! 🐳DeepSeek V3.2: a new family of reasoning-first, agent-oriented models from @deepseek_ai are now live in the Arena. Standard, Thinking, and Speciale are all in the Text Arena, waiting for your toughest prompts! Get your votes in: we’ll see how they https://x.com/arena/status/1995564824718442620
🚀 @deepseek_ai just dropped two official models — V3.2 & V3.2-Speciale, and Chinese tech circles are buzzing. What do they really achieve? Zhihu contributor toyama nao breaks it down, closely aligning with DeepSeek’s own published scores👇 DeepSeek has already shaken China’s AI https://x.com/ZhihuFrontier/status/1995689116999311455
🚀 Day 0 Deepseek v3.2 launch on @FireworksAI_HQ ! Congrat @deepseek_ai team on releasing another SOTA model! Continuing our promise, you can access DSV3.2 now on our platform. We heavily focus on quality first. A ton of perf optimization will come shortly. Below are the”” / X https://x.com/lqiao/status/1995915147714723974
🚀 Launching DeepSeek-V3.2 & DeepSeek-V3.2-Speciale — Reasoning-first models built for agents! 🔹 DeepSeek-V3.2: Official successor to V3.2-Exp. Now live on App, Web & API. 🔹 DeepSeek-V3.2-Speciale: Pushing the boundaries of reasoning capabilities. API-only for now. 📄 Tech https://x.com/deepseek_ai/status/1995452641430651132
🚀 vLLM now offers an optimized inference recipe for DeepSeek-V3.2. ⚙️ Startup details Run vLLM with DeepSeek-specific components: –tokenizer-mode deepseek_v32 \ –tool-call-parser deepseek_v32 🧰 Usage tips Enable thinking mode in vLLM: – https://x.com/vllm_project/status/1996760535908642986
DeepSeek V3.2 is the #2 most intelligent open weights model and also ranks ahead of Grok 4 and Claude Sonnet 4.5 (Thinking) – it takes DeepSeek Sparse Attention out of ‘experimental’ status and couples it with a material boost to intelligence @deepseek_ai V3.2 scores 66 on the https://x.com/ArtificialAnlys/status/1996110256628539409
deepseek-ai/DeepSeek-V3.2 · Hugging Face https://huggingface.co/deepseek-ai/DeepSeek-V3.2
Game over https://x.com/Yuchenj_UW/status/1995523554679673180
If you need an adrenaline rush to wake up from your post-Thanksgiving stupor… we got you. @deepseek_ai V3.2 dropped this week and is now available on Baseten. It’s so smart your mother will ask why you can’t be more like DeepSeek. V3.2 is currently on par with GPT-5 all whilst https://x.com/basetenco/status/1996623218040254793
Incredible writeup! Some notable 💎s: Deepseek reduced attention complexity from quadratic to ~linear through warm-starting (w/ separate init + opt dynamics) and adapting the change over ~1T tokens. They also use separate attention modes for disaggregated prefill vs decode (is https://x.com/suchenzang/status/1995535496421015741
Introducing DeepSeek-V3.2-Exp | DeepSeek API Docs https://api-docs.deepseek.com/news/news250929
Link to DeepSeek’s technical paper: https://x.com/ArtificialAnlys/status/1996110267353325748
LisanBench results for DeepSeek-V3.2 DeepSeek-V3.2 and V3.2 Speciale are affordable frontier models* *the caveat is that they are pretty slow at ~30-40tks/s and produce by far the longest reasoning chains at 20k and 47k average output tokens (incl. reasoning) – which results in https://x.com/scaling01/status/1995895894219100462
New Model(s) Drop: DeepSeek V3.2 is now live on Yupp! From @deepseek_ai, these are open-source models with enhanced math, coding and logic capabilities – offered in Chat, Thinking and Speciale versions. Let’s see how they perform: https://x.com/yupp_ai/status/1995538168146526274
Speciale is the first DeepSeek model of all time that gets my dumb bilingual joke about God of War. V3.2 flails and invents cringe fake etymology, just like R1. 4o could do this already. The knowledge gap is wide and deep indeed. Still. Frontier at last. https://x.com/teortaxesTex/status/1995527632578834829
While reviewing the results again, I noticed a misjudged part in the score for the deepseek v3.2 Speciale model and corrected it. The revised result is a very impressive 8.81, which is top tier and achieved a perfect 10 across all quantitative metrics. However, as I mentioned https://x.com/Hangsiin/status/1995899545339990042
🚨BREAKING: Text Leaderboard Update 🐳 Deepseek-v3.2 enters the leaderboard at #38, and Deepseek-v3.2-thinking lands at #41. For comparison, previous versions ranked higher: 🔹 v3.2 ranks #38 (-5 pts v3.1 and -14 pts v3.2-exp) 🔹 v3.2-thinking ranks #41 (-7 pts vs v3.1-thinking https://x.com/arena/status/1996707563208167881
Compare how DeepSeek V3.2 performs relative to models you are using or considering at: https://x.com/ArtificialAnlys/status/1996110266065715249
DeepSeek’s new DeepSeekMath-V2 hits gold-medal performance on IMO and Putnam. It’s the first open model that can check its own proofs, fix mistakes, and improve itself. DeepSeekMath-V2 uses two “minds” in one model: ▪️ A verifier – Reads a proof and points out issues. – https://x.com/TheTuringPost/status/1994926897248288813
very smart choices by @stochasticchasm and the arcee team. in terms of arch, this is pretty much the perfect setup if you’re a bit constrained by compute/time and can’t do 100s of ablations hybrid nope, gated attention, norms to stabilize everything, muon, deepseek routing this”” / X https://x.com/eliebakouch/status/1995600008603697346
> be arcee > look around > realize open-weight frontier MoE is basically a Qwen/DeepSeek monopoly > decide “nah, we’re building our own” > actual end-to-end pretraining > on US soil > introducing Trinity > Nano (6B MoE) and Mini (26B MoE) > open weights, Apache 2.0 > free on https://x.com/TheAhmadOsman/status/1995613231629381935
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