Developer Advocate @NebiusAI. Building with open models | coding agents | LLM inference

San Jose, CA, USA
Joined February 2025
Friday fun 🎉 The Nemotron family (Super, Lightning, Ultra) went to the carnival… and raced horses 🎪🏇 One of them is a total sprinter. Guess who? 👀 Link below 👇
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Models running on @nebiustf 😀
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taking muse-wonder, gpt-astra and claude-opus for a (horse) ride :-) it was a close race - latency was a big decider see below 👇 (just a fun test, not a benchmark)
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Our talk at @aiDotEngineer World's Fair SF is now live! 🎥 @dylan and I explored "Optimizing Open Models for Production" - the techniques that make LLM inference faster, more efficient, and cheaper at @nebiustf. We covered a few key optimizations: - KV caching - Reuse previously computed key-value states instead of recomputing them. One of the biggest performance wins, with 5-10x speedups in some scenarios. - Cache-aware routing - Route requests to workers that already have the relevant KV cache, improving cache hit rates and reducing redundant computation. - Speculative decoding - A smaller model drafts tokens while a larger model verifies them, accelerating generation without sacrificing output quality. - Disaggregated prefill and decoding - Prefill is compute-heavy, while decoding is memory-bandwidth-heavy. Running them on separate GPU pools lets us optimize each independently. - Quantization - Smaller models, less memory, faster inference. But aggressive quantization can hurt quality, so finding the right balance is key. Lots of practical techniques for getting more performance out of open models! 🎥 Watch the talk: youtube.com/watch?v=TRe1u7dH… 📊 Slides: sujee.dev/events/2026-06-29_…
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Friday fun! I built a horse race for LLMs. 🏇 LLM Derby puts models head-to-head on the same questions. Every correct answer moves a horse forward. First to 20 wins. This race: 🏇 Qwen3.8-27B 🏇 gpt-6-astra 🏇 claude-sonnet-5-5 Who won? Watch the video 👇 Try the game (in your browser): sujee.github.io/llm-derby/ Just a fun game, not a benchmark 😄
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Great collection!
I built a growing gallery of motion graphics made with Claude Opus 5.5, each shown next to the prompt or skill that made it. 226 so far, all pulled from posts here and credited to their creators. prompt-motion.com
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Sujee Maniyam retweeted
🎂 I’m turning my dog into a video game for his second birthday!! Tomorrow on Build With @nebiusai : @sujee_dev tests AI models then we’ve got 30 minutes to build a game. You vote on the levels! 9 a.m. Pacific · X + YouTube. Let’s go!! 🔥
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35 years ago today, Linux 0.02 was released 🐧 I've been using Linux for ~31 of those years. 1995: recompiling kernels to get new hardware working. 2026: Linux Mint + NVIDIA GPU, running LLMs locally. A lot has changed. Linux is still there. I made this little visual history of Linux 👇 What’s your favorite Linux memory?
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how i made this video.. prompts + stack xitter.cf/sujee_dev/status/21075…
A few of you asked how I made this Linux history video: youtube.com/watch?v=lkOxEeqw… It started with one prompt in Claude Code (Opus 5.5): "Create visualization tracing Linux history. A 2 min video, with cool music." That's the whole prompt. No 3-page storyboard. No extra skills, MCP servers or API keys. ~7 minutes later I had a 2-minute video with an original soundtrack. The music is generated in Python, not by a music service. That first pass got me ~80% there. The rest was notes in the same session, like: "0:30: keep this sequence longer" Takeaway: you don't need a complicated setup or a long prompt to make good motion graphics. Start with one sentence and direct from there. The prompt, the code, and how to remix it yourself: github.com/sujee/visual-stor…
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Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
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My Le Chonk 🐈😂
Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
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A few of you asked how I made this Linux history video: youtube.com/watch?v=lkOxEeqw… It started with one prompt in Claude Code (Opus 5.5): "Create visualization tracing Linux history. A 2 min video, with cool music." That's the whole prompt. No 3-page storyboard. No extra skills, MCP servers or API keys. ~7 minutes later I had a 2-minute video with an original soundtrack. The music is generated in Python, not by a music service. That first pass got me ~80% there. The rest was notes in the same session, like: "0:30: keep this sequence longer" Takeaway: you don't need a complicated setup or a long prompt to make good motion graphics. Start with one sentence and direct from there. The prompt, the code, and how to remix it yourself: github.com/sujee/visual-stor…
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one of my 'favorite' memories is buying a logitech sound card and then spending next few days recompiling kernel to get it to work 😅
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Found this one in the archives :-) Me holding a Red Hat Linux 5.1 CD, circa 1998. Check out those CRTs! I wrote a little more about my 31-year journey with Linux: sujee.dev/post/linux-35th-bi… Also 4K video : youtu.be/lkOxEeqwMBo
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Most AI models write. Jev @typesafeai decides. A 2-minute explainer for devs 👇 Made with Claude Code + Opus 5.5. Open source and fully reproducible. Remix it: github.com/sujee/visual-expl…
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