214 summarised stories about Open Source Models, each linking back to the original source. Browse all topics →
TechCrunch 1 month ago 50 ● 4 sources
PrismML released Bonsai 2 27B, a compressed reasoning large language model designed to run on PCs and smartphones. The model compresses Qwen3.8 27B down to 5.9 GB, matching 98% of Qwen’s aggregate benchmark scores. As a result, LLMs can be deployed with much lower memory use while aiming to preserve performance, with the company planning next releases targeting several-hundred-billion parameters.
Product Hunt 1 month ago 41
Mantle launched an open-source service runtime and WebMCP-native builder that generates typed schemas, views, procedures, and HTTP/MCP triggers from business rules. The builder and an OSS-first Cloudflare deployment path are live as of today. The release adds an in-browser design/verification flow and a handoff step for a coding agent to materialize, verify, and deploy to a user’s Cloudflare account.
TechCrunch 1 month ago 12
Base Labs launched a safety infrastructure partnership with Hugging Face and Goodfire to build evaluation and monitoring for open-weight AI models. Hugging Face currently lists over 6,000 abliterated models, a practice tied to weakening model safeguards. The effort aims to publish methods and an open call so safety controls are built into how models are trained and deployed.
Hacker News 1 month ago 35
Skillsync, a YC W26 startup, released portable AI chat sessions that can be converted and moved across different coding agents while preserving messages, reasoning, and tool calls.
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20 October 2026
Today’s biggest thread is the build-out of “agent infrastructure” that makes AI assistants feel less like chat windows and more like tools with their own computers, workflows, and controls. Daytona, a startup branding its stack as an “agentic cloud,” raised a $60 million Series B to a $1 billion valuation, aiming to speed up sandbox provisioning for agent “computers” with a 60-millisecond setup time—an attack on the bottleneck of traditional VM spin-up. IBM, Red Hat, and contributors also pushed in the same direction with llm-d framework v1.0, adding operational controls for distributed in-house inference, including a router that captured 97% cache reuse in an agentic coding test and improvements for multi-tenant QoS, zero-downtime upgrades, and request routing.
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