@lmstudio

Bionic is the agent for your computer https://xitter.cf/t.co/YS5uiRQ7TI

New York, USA
Joined May 2023
We're excited to bring you Flint by @Recursive_SI in LM Studio on day 0! • 40B MoE, 2.5B active • 262K token context window • Apache 2.0 • Trained for local agentic coding model Requires about 24GB to run locally on your machine, performs impressively on benchmarks.
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
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We’ve added new US-based capacity for DeepSeek-V4.1-Flash-1017 in Bionic. Should run into much fewer rate limits now. Working to add more!
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DeepSeek-V4.1-Flash-1017 is now live in LM Studio Bionic! 1M context • image input • highly cost effective US-hosted with full ZDR. Try it out for coding tasks!
🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4
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Beam (501B MoE) by Reflection is now live in Bionic! US-hosted and ZDR. Let’s go! 🚀👾
Beam is now available across platforms, with open weights under the Apache 2.0 license - in collaboration with an ecosystem of 40+ partners. We're releasing: - Weights, tokenizer, and reference implementation - BF16, FP8 and NVFP4 weights and a DFlash2 drafter - The open source harness we built and trained Beam on: Mirror CLI Weights and model card on Hugging Face: huggingface.co/reflection
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Nemotron 3.5 Super VL from @NVIDIAAI is live in LM Studio! • 120B total / 12B active MoE • Supports vision input, reasoning • Trained for visual understanding, tool use Requires ~70GB RAM to run locally 🚀 👾 lmstudio.ai/models/nemotron-…
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State → local decision model → action Check out @liquidai's d1 decision model playing Lmmy Run, all on its own 🦖👾 Served 100% on-device, making decisions in a fraction of a second
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LM Studio 0.4.26 is out now! • ⚡️ `/v1/systemone` and `/v1/decisions` APIs • 👾 Coexistence with Bionic • 🎨 UI updates and bug fixes Yes, you can now point your Bionic agent to models loaded in your LM Studio. lmstudio.ai/docs/developer/j…
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Bionic can now show live updating previews of your docs, sheets, and slides!
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Also new in Bionic 1.1.8: - /v1/systemone and /v1/decisions API support - Run Bionic at the same as LM Studio lmstudio.ai/changelog/bionic…
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We’re so back.
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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Bionic now has a built-in interactive canvas. Create Excalidraw diagrams both you and Bionic can see and edit. Collaborate on mock ups, system design, process maps and ask Bionic to implement them.
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Qwen3.8-27B, up to 144 tok/sec on M5 Max. Let that sink in. ⚡️✨🚀 Excited to partner with @inco_ai to bring you their Splash inference engine in LM Studio on day 0! Get it running now: lmstudio.ai/blog/splash-engi…
Qwen3.8-27B at 144 tok/s on an M5 Max MacBook Pro ⚡ Meet Inco Splash: our open-source inference engine, built around the model and around Apple silicon. Up to 3× the decode speed of Ollama, 2× oMLX, and almost 4× when an agent fans out into sub-agents.
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Head to Settings > Runtime > Experimental backends to get the Splash engine. Download supported models by searching "incoai". Recommended specs: - M3 or newer Mac on macOS 26.4 - 36GB+ RAM
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Introducing Introspection and Session References Bionic agent can now search through its own session history, making it much more capable of handling long-term context and multiple compactions. You can also reference other sessions directly in the composer using an @ mention!
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LM Studio retweeted
ローカルAIエージェント「LM Studio Bionic」が日本語UIに対応 pc.watch.impress.co.jp/docs/…
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