🚀 RELEASES & LAUNCHES
Nace.AI releases Drex Max v1: open-weight 27B multimodal decision model with 262K context
Nace.AI open-sourced Drex Max v1, a 27B multimodal decision model that returns calibrated probabilities over typed options in a single forward pass instead of generating text.- Built for computer-use and browser agents, routing, classification, and policy checks in finance, banking, and legal.
- Dense 27B model with a 255-way readout head, no decode loop, 262,144-token context, released under the Open RAIL-M license; accepts text, JSON, and images.
- Scores 67.5 on the public Decision Index 0.4, 73.9 on the public vision index, and 64 on the Artificial Analysis Decision Index (4th of 18).
- Runs via Python on NVIDIA GPUs and on Apple Silicon/CPU via llama.cpp, Ollama, Kapitsa, and MLX forks; affine Q4 checkpoint runs on 24 GB Macs, Q8_0 needs 48 GB.
- Available through the Nace API and OpenRouter at $0.06 per million input tokens with ~172-183 ms median latency per decision.
Heretic 2.0 launches as general-purpose LLM model modification tool
Developer p-e-w released Heretic 2.0, expanding the censorship-removal tool into a general-purpose language model modification tool.- Aimed at local LLM users and model tinkerers on r/LocalLLaMA and Hugging Face.
- Heretic 2.0 arrives after ~5 months of development; the project now has 37k GitHub stars, 8,500+ models on Hugging Face, and 88 million total downloads.
- Beyond censorship removal, it can suppress slop, reduce sycophancy, and alter emotional alignment, positioning itself as a general-purpose model modification tool.
- The release marks a shift from a purpose-built censorship-removal utility to a broader model-modification platform.
- It gives builders a free, open-source way to customize open-weight model behavior without retraining.
Silencio-2: open 18M-parameter TTS with emotion and sound tags, ~20x realtime on CPU
BlueRoseLabs released Silencio-2, an open-weights 18M-parameter English TTS model that follows inline emotion and sound tags and runs about 20x realtime on CPU.- Aimed at local/on-device TTS users and developers; free and open with no paid tier or API, weights on Hugging Face and a browser Colab demo.
- Fine-tune of Kyutai's Pocket TTS 18M that follows tags written inside the text, e.g. [sigh], , , plus sounds like laugh, sigh, and gasp.
- 18.2M speech parameters (27.9M with the voice-cloning encoder), 112 MB on disk, 24 kHz streaming output, zero-shot voice cloning from a short clip, English only.
- Reports about 20x realtime on an Apple M4 with 4 CPU threads and no GPU, from a single long-text run rather than a benchmark.
- Shows tiny open models can add expressive control (emotion/sound tags) while staying CPU-deployable for builders of local voice apps.
🔬 RESEARCH
- DeepSeek open-sources dsh-superagent, an autonomous multi-agent coding prototype
DeepSeek open-sourced dsh-superagent, a research prototype of an always-on coding agent that coordinates parallel worker sessions with minimal human attention.- Aimed at developers and teams running coding agents on GitHub, with optional Feishu integration for task intake
- The prototype uses a persistent Router to assign work to parallel Worker sessions, with event-driven triggers, thread subscriptions, and a Watchdog for recovery during long-running tasks
- It listens to GitHub (and optionally Feishu), opens work items, and replies with pull requests or messages when rules permit; a web panel shows what needs human attention
- Released under MIT license on GitHub, where it gained ~6,700 stars in three days; DeepSeek stresses it is research code, not an official product, with some described designs not yet implemented
- The Router/Worker architecture contrasts with single-session subagent designs in Claude Code and Codex, giving teams a concrete implementation to study and adapt