retired geek happily tinkering. waaay out of my depth - and loving it😜 mainly here for local AI / low-key lurking & learning 🔬📚 no followers ≠ fake

Cirencester, England
Joined January 2026
Mark Sunner retweeted
Replying to @PessimistsArc
Right. Dario was already claiming that GPT2 was too dangerous to open source back in 2019. I made fun of them then. Everyone should make fun of them now.
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Mark Sunner retweeted
Dario wants to pace the frontier. Sam agrees. Elon agrees. Somehow everyone found the brake pedal right as open models started catching up. I run AI on hardware I actually own. If you care who gets to own intelligence, you need to read this.
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Mark Sunner retweeted
Chetaslua
@chetasluaAug 22
🚨BREAKING: the stealth model Ox Alpha is Z.ai (Zhipu) everyone else is guessing it from tokenizer vibes and emoji rates. i made the server say its own name out loud. sent it one malformed request and it threw a java stack trace naming its own internal class: com.wd.paas.api.domain.v4.ch….ChatCompletionRequest paas/v4/chat = Zhipu's documented route /api/paas/v4/chat/completions thats not a fingerprint guess. thats the server confessing. proven at the serving layer, confidence 0.98.
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New production build on my tp=4 GLM-5.2 cluster, and this one is about a lesson I keep relearning: the benchmark config and the config you actually want to live with are two different animals. My 44.6 tok/s record build is still in the repo, still reproduces, still the fastest published decode on this hardware. But I don't serve it anymore. Here's why. I watched what my agent actually does all day: long agentic coding sessions that grow until they hit the context ceiling, deep prompts, real work. The record config was tuned for a number, not for that job. It kept running my agent out of room. The new production build trades the sprint for the marathon: context window up 58% to 316K, deep-context decode up 18% at 77% draft acceptance, deep cold prefill at 667 tok/s which is the best I've seen published for a 4x Spark, and real workload throughput identical to the record config. The only thing it gives up is a peak number my agent never produces in practice. Everyone benchmarks the sprint. Nobody benchmarks the marathon their agent actually runs. Measure your own workload before you copy anyone's config, including mine. Both builds ship in the repo one launcher command apart, with the full trade table and raw data, because a config is a set of trades and I publish mine. github.com/joesinvestments/G…
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Mark Sunner retweeted
Me this morning
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Mark Sunner retweeted
Today we’ve raised $52M Seed and we are announcing the public launch of S2.1 Pro. >It can clone a voice from 5 seconds of audio >2x faster than Cartesia & 1/6th the cost of Eleven Labs >most expressive model with word level control over emotion, intonation, pacing etc We support frontier AI companies including HeyGen, LiveKit, Retell, Sanas, and OpenArt all run our model in production. If you're a business and we can't cut your voice AI costs by 50%, we'll give you 1 year of Fish Audio for free. Book a demo: s.fish.audio/tmapke To celebrate our first birthday, we'll give you 1 month of S2.1 Pro for free. Like, retweet, and comment “Fish” to get it.
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Mark Sunner retweeted
You can now run GLM-5.2 on 3x @NVIDIAAI DGX Sparks at home 🤯 • 248k context • 15-20 tok/s (content-dependent) • MTP for max context / DSpark optional • NVFP4+AQLM hybrid Still a work in progress — will keep improving over time. → github.com/MiaAI-Lab/GLM-5.2…
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Mark Sunner retweeted
The first 2.8T open model! Yes, we are pushing forward the frontier open intelligence!🫡
Introducing Kimi K3: Open Frontier Intelligence 🔹 2.8 Trillion Parameters, 1 Million Context, Native Multimodal 🔹 Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts 🔹 Attention Residuals deliver ~25% higher training efficiency at <2% additional cost 🔹 Built for long-horizon agentic coding and self-evolving workflows Kimi K3 is now live on on Kimi.com, Kimi Work, Kimi Code, and the Kimi API. Open Weights by July 27, 2026. 🔗 API: platform.kimi.ai 🔗 Tech blog: kimi.com/blog/kimi-k3
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Mark Sunner retweeted
Chinese models are 112x cheaper than Anthropic per million tokens. Chamath laid it out on CNBC: a "barrel of intelligence" costs $56 from Anthropic, $26 from OpenAI, $1.50 from Meta, $1 from xAI and Google, and $0.50 from Chinese models. That is not a pricing quirk. That is the steepest commodity curve any technology has run in recorded history. Oil took 40 years to compress like this. Semiconductors took 20. AI inference is doing it in months. The companies sitting at $26 and $56 are not stupid. They're buying time… betting that trust, safety, and enterprise contracts hold the premium long enough for costs to catch up. What they cannot bet on is the timeline. Because the $0.50 model is not a demo. I've been inside the labs building it.
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Mark Sunner retweeted
Pay Attention ! If you dig into the HF page, there's also Inkling-Small hiding out: 276B params, 12B active, and it actually outperforms the big model on some benchmarks. Not a formal launch, just quietly sitting there. Easter egg find 🥚 Open weights, Apache 2.0, fine-tune on Tinker.
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/int… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
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Announcing our $130M Series A to build the Open Superintelligence Stack Led by Radical Ventures, with NVIDIA, Intel Capital, Dell Capital, and existing investors Train, deploy, and continuously improve your own models using our stack. Own your intelligence.
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Replying to @Web3Twon
Things are moving in a path that increasingly benefit Anthropic and I think its not all a bunch of coincidences.
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Major fallout if so. Basically this is the Dario wins timeline. Get your subscription face on pleeb 😶‍🌫️
CHINA CONSIDERS RESTRICTING OVERSEAS ACCESS TO CUTTING-EDGE AI MODELS China’s Ministry of Commerce has led meetings over the past month with major AI companies, including Alibaba, ByteDance, and Z.ai, to discuss measures that would restrict overseas access to cutting-edge AI models, including models that have not yet been released. The discussions reportedly include not only closed-source models but also open-weight models. However, the scope of application is still under debate, and the rules may ultimately apply only to future frontier models. Officials have also discussed designating the leakage or theft of proprietary AI technologies as a national security crime, with stronger penalties, as well as restricting the types of foreign capital that can invest in Chinese AI startups. The backdrop is the U.S. move to strengthen export controls on AI models, along with national security concerns over cutting-edge models that could possess advanced cyberattack capabilities. Chinese authorities are reportedly concerned that advanced U.S. cybersecurity AI models could be used to exploit vulnerabilities in Chinese software. Since the beginning of this year, China has continued to tighten measures to prevent AI technology from being transferred overseas. Authorities have investigated whether Chinese AI startups that relocated abroad violated export control laws, while also strengthening oversight of overseas transactions involving Chinese investors, technology, data, and national security concerns. Future regulations could take the form of a tiered framework based on technological capability. Basic open-source AI models may be managed through a filing system, high-performance models may be subject to security reviews, and the most sensitive frontier models may be banned from public release or restricted to use within China.
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Mark Sunner retweeted
WHO DID THIS It’s the best shot Anthropic has at getting Fable back.
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Working continuously over a week on getting DDTree to work natively on DGX Spark in a custom vLLM container. Unfortunately not over the finish line yet. Community collaboration is welcome, I've published all the work so far and the container image. github.com/AEON-7/Qwen3.6-27…
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Mark Sunner retweeted
me and @claudeai
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Mark Sunner retweeted
Have you tried @lmstudio ? You can load Nemotron 3 Nano by @nvidia
Just a simple video about @lmstudio Showing users how to use LM Studio with chat and LLM API building a quick demo app! Let me know in the comments what you think! 👇
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Mark Sunner retweeted
if you dont have a few of these open at all times… you’re not gonna make it
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