Fetching from the wire…
OSS2026-09-23 · source-backed
dlab open-source week covers compression, context compaction, agent harnesses, autonomous research and test-time scaling, all aimed at local hardware. The bitsandbytes2 private beta is built around runtime dynamic compression of Mixture-of-Experts, and Dettmers says it runs a quantized Qwen model at 450 tokens/s at 1.5 bits per weight. That figure is unreplicated beta data.
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Somebody diffed the configs. Zero architectural changes. Same 64 layers, same 5,120 hidden dimension, same hybrid Gated DeltaNet → FFN / Gated Attention → FFN block structure as Qwen3.6-27B. The r/LocalLLaMA post showing this hit 945 upvotes and 157 comments, and Hugging Face...
Cherry Studio ships unified access to OpenAI, Anthropic, Gemini, DeepSeek, Qwen, Ollama, and dozens more providers in a single Electron app. Autonomous agent mode, built-in knowledge base, MCP support. It's basically a free, local-first alternative to switching between web int...
The Hugging Face page is marked "Upcoming release" with no model card, license, architecture details, context length or benchmarks, after Alibaba promised both Qwen3.8-Max and the 27B weights for the week of August 10. A ModelScope countdown pointed at August 15. Unsloth signa...
The letter to Senators Tim Scott and Elizabeth Warren, dated June 10 and surfacing publicly this week, frames it as model distillation run against Claude at scale (Anthropic). A related claim pegs it at 28.8 million fraudulent exchanges, though that figure is single-sourced an...
Alibaba released Qwen3.6-27B on April 22. Dense architecture. Open weights. 77.2% on SWE-bench Verified, within 3.7 points of Claude Opus 4.6. On SkillsBench, it scores 48.2% versus its own 397B MoE predecessor's 30.0%. That's a 77% improvement with 14.8x fewer parameters. Let...
Moonshot AI dropped Kimi K2.6 today and the numbers are hard to ignore. One trillion parameters total, 32 billion active per token across 384 experts, 256K context window, and native multimodal input. It scores 58.6 on SWE-Bench Pro versus GPT-5.4's 57.7 and Claude Opus 4.6's...
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