NVIDIA · Released Oct 15, 2026 your queue
This is the one you said you'd download yourself, Matt. 74B total, 9B active per token, quantization-aware-trained at 2-bit so the whole thing packs into 24GB — and it runs at launch through llama.cpp, vLLM, Ollama, Unsloth, LM Studio, and "directly in Hermes and OpenClaw." NVIDIA's own claim: faster than popular dense models, smarter than most MoE models at a similar memory footprint. Weights, data, and recipes open like other Nemotron releases. The sibling to note: a 4GB Bolt E4B for game NPCs lands Oct 23. Your homework writes itself — this is the natural challenger in the Qwen spec-pair's neighborhood, though the 24GB footprint means it needs your whole 32GB pool, no parking it on one card.
DeepSeek · Open-sourced Oct 20, 2026 day's #1 repo
Not weights. The plumbing. FlashMLA, DeepGEMM, DeepEP kernels, MoE expert parallelism with load balancing, DSpark confidence-scheduled speculative decoding, batch-invariant deterministic inference — Apache 2.0, ~9.4k stars on day one. But be honest about the catch: it serves one model (V4.1-Flash) on two chips (NVIDIA SM100, Huawei Ascend 950), and the load-balancer machinery that makes the economics work stayed home. Nothing here runs on your A770s. What does transfer: DSpark-style speculative decoding and FlashMLA attention kernels are the exact ideas the llama.cpp folks reverse-engineer next. Worth a star, not a weekend.
Google · Open-sourced Oct 20, 2026
Frozen weights, warmer scores — your exact doctrine, Matt. Google's play: improve the harness around the model instead of retraining the model, and Gemini 3.5 Flash gained 8.4 and 7.5 points on two task benchmarks just from that. This is the kind of free lunch the hermes-desktop workstream should be stealing ideas from — tool surface and orchestration are where the agentic gains live once the brain is good enough. Skim the harness diff before the next "let's swap the model" impulse.
Moonshot AI · Released Oct 14, 2026
The phone-steers-local-agent dream, productized. AppImage/deb/RPM builds, a file-tree panel, and Remote Control: watch task progress, approve things, and send follow-ups from a phone, tablet, or another machine via link/QR code while files, shell, and tools keep running on the desktop. That's the interaction shape the hermuse phone console is chasing — difference being Kimi did the pairing link in one release. Study the UX, steal shamelessly, don't get sad about it.
Industry trend · October 2026
Typed answers, probabilities, no prose — the kev-decision playbook, now an industry pattern. Cloudflare's Clef models are post-trained from Qwen bases, read text/JSON/images/video, and cost $0.24/$0.09 per million input tokens with 65k context. Amazon's Strands Decider is 2B and free to run locally. The point of the pattern: put a cheap check right before the action instead of paying for a frontier round-trip. That's literally what :8080 is for. Meanwhile in megamodel land: Meta's Muse Spark Open (816B/42B active, 1M context, limited-commercial license) and Reflection's Beam (501B MoE, Apache 2.0, coding/agentic, NVFP4 squashes 1TB → 280GB) are datacenter toys. Admire from afar.