Ari Messer (@arimesser) header
Ari Messer (@arimesser) profile picture

@kilocode @littledatauk. @stanford and @edinburghuni. Tech optimist. Former journalist.

Manhattan, NY
Joined February 2011
Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)Photo by Ari Messer (@arimesser)
Full circle 🤣
FABLE 5.1 IS WILD! This video is NOT a screen recording of x.com. It's what happened when we pasted a screenshot of X into Kilo Code with Fable 5.1 and said: "Recreate X (twitter). Use the screenshot for design, and implement all actual functionality." One prompt, $13.00. All buttons work, and all the X functionality is there: reposts, quotes, polls, settings, suggestions, etc. 🤯
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WorldCupBench update: 94 matches predicted. Best model so far: Nemotron 3 Ultra at 63%, followed by MiniMax M3 (61%) and DeepSeek V4 Pro (61%). The machines are doing pretty well! There's still time to join and make your picks: worldcup.kilo.ai/
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Next-Edit is live in Kilo, powered by Mercury Edit 2 from @_inception_ai. Autocomplete predicts the next few tokens ahead of your cursor. Next-Edit predicts your next actual edit anywhere in the file. Hit Tab to accept. And it's free for everyone for 30 days!
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A week where one model got pulled by an export order, another beat the frontier, and a third may or may not exist depending on whether it comes out from under the couch. More in the thread. 🧵
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Gonna get even crazier with the next Zai release 🤠
Fable 5 and Mythos 5 were the best coding models you could get. Gone three days after launch when a US export directive forced Anthropic to pull them globally. Production doesn't pause for a regulatory fight. The frontier didn't go dark either. 🧵
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Model freedom is essential. Over on the @kilocode blog I dive into some of the key LLMs to check out right now, including some of the top open-weight contenders blog.kilo.ai/p/you-dont-have…
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That’s a pretty significant discount just from using a top OSS model
We gave the same code audit to Claude Opus 4.8 and MiniMax M3. Same codebase. Same prompt. 17 known bugs planted in advance. MiniMax M3 caught 13 of them for $0.07. The cheapest Claude run caught the same 13 for $1.30. Here's the breakdown. 🧵
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Insanely impressed by @grok Build 0.1 so far. And this is only 0.1... @xai 🚀
Stepfun is still leading the Kilo Gateway with 30%+ of usage. But three new arrivals are shaking it up. • Grok Build 0.1 made some noise. • Gemini 3.5 Flash quietly raised the bar. • Qwen 3.7 Max showed up earlier than expected. Same workflow, same prompts, three different answers.
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Ari Messer retweeted
“Things are not what they seem, nor are they otherwise.” — Lankavatara Sutra
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Replying to @MistralAI
@MistralAI 3.5 Medium is live in @kilocode It’s one of the few European open-source labs at scale – French, with a growing US presence. We've been running one of their models behind Kilo's autocomplete for a while now, so the team has been close to their work.
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This is their first general release in a bit. Medium-sized, built for everyday work.
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Real testing still underway. If you've already routed it for something, what are you using it for?
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Great app for stress-testing ideas!
This Post is from an account that no longer exists. Learn more
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OSS continues to win
TokenSpeed is a brand new inference engine purpose built for speed-of-light agentic workloads. Read their blog to learn more about its advanced KV cache management, safe and efficient scheduler, and pluggable layered kernel system designed for multi-silicon support. Plus, it also has the fastest MLA attention kernel on NVIDIA Blackwell. Congrats to @lightseekorg on the launch!
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A quick taxonomy of "open." Open source: the code is public. Model-neutral: you pick the model. Provider-neutral: you pick the host. Surface-neutral: you pick the IDE. Warp is one of those. Kilo is all four.
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Ari Messer retweeted
HF becoming the platform for agents (assisted by their humans) to use and build AI (rather than just leveraging APIs)!
Introducing ml-intern, the agent that just automated the post-training team @huggingface It's an open-source implementation of the real research loop that our ML researchers do every day. You give it a prompt, it researches papers, goes through citations, implements ideas in GPU sandboxes, iterates and builds deeply research-backed models for any use case. All built on the Hugging Face ecosystem. It can pull off crazy things: We made it train the best model for scientific reasoning. It went through citations from the official benchmark paper. Found OpenScience and NemoTron-CrossThink, added 7 difficulty-filtered dataset variants from ARC/SciQ/MMLU, and ran 12 SFT runs on Qwen3-1.7B. This pushed the score 10% → 32% on GPQA in under 10h. Claude Code's best: 22.99%. In healthcare settings it inspected available datasets, concluded they were too low quality, and wrote a script to generate 1100 synthetic data points from scratch for emergencies, hedging, multilingual etc. Then upsampled 50x for training. Beat Codex on HealthBench by 60%. For competitive mathematics, it wrote a full GRPO script, launched training with A100 GPUs on hf.co/spaces, watched rewards claim and then collapse, and ran ablations until it succeeded. All fully backed by papers, autonomously. How it works? ml-intern makes full use of the HF ecosystem: - finds papers on arxiv and hf.co/papers, reads them fully, walks citation graphs, pulls datasets referenced in methodology sections and on hf.co/datasets - browses the Hub, reads recent docs, inspects datasets and reformats them before training so it doesn't waste GPU hours on bad data - launches training jobs on HF Jobs if no local GPUs are available, monitors runs, reads its own eval outputs, diagnoses failures, retrains ml-intern deeply embodies how researchers work and think. It knows how data should look like and what good models feel like. Releasing it today as a CLI and a web app you can use from your phone/desktop. CLI: github.com/huggingface/ml-in… Web + mobile: huggingface.co/spaces/smolag… And the best part? We also provisioned 1k$ GPU resources and Anthropic credits for the quickest among you to use.
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Kimi K2.6 just landed in Kilo! It's open weights. It's fast. There's no free trial this time around, but honestly, the model speaks for itself, and builders who care already know what they're looking at. blog.kilo.ai/p/kimi-k26-has-…
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I'm retiring. ...from using 5 different apps to get around NYC, because now #MyBotDoesThat! KiloClaw from @kilocode now finds the most scenic routes for me, includes ferries and bike paths, and even shares historical tidbits along the way. 🦞
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🚨 FREE, virtual OpenClaw Workshop this Wednesday! No lectures, no corporate buzz. Just real, practical takeaways you can put to work the same day. Sessions from @openclaw maintainers, AI companies like @arcee_ai, @ExaAILabs, Neuralwatt, and more! Sign up: luma.com/wuu7ftpo
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Dola Seed 2.0 Pro is free in Kilo right now. It matches GPT-5.2 and Gemini 3 Pro on benchmarks. It's true multimodal (images, video, visual docs). 256K context. 128K output. Native browser and computer use built in. So new it hasn't even been benchmarked in PinchBench yet. Use it in VS Code, CLI, or KiloClaw while it's free. kilo.codes/dola-seed-2
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