Kolibri 78B Open, Claude Code 2.1.291, llama.cpp GLM-5.3
mardi 6 octobre 2026 - AI News · (24 dernières heures)
Aleph Alpha drops open-weight Kolibri 78B MoE with 1M context under Apache 2.0, aimed squarely at regulated industries.
Must read
- Aleph Alpha releases open-weight Kolibri with 1M context — 78B MoE, Apache 2.0, 1M context, tool calling — a sovereign-friendly option for identity/RegTech workloads you can self-host.
- Claude Code v2.1.290/291 — New plugin hook surface (serverToolUses, agentId, ceiling) tightens subagent permission control — directly useful for your overnight-agent-factory governance.
- llama.cpp v0.6.0 with GLM-5.3-Flash + MTP — Extended batch API, GLM-5.3 320B hybrid and Qwen4Exp speculative decoding land in the engine your Apple Silicon rigs depend on.
- Prime Inference: serving for frontier open models — Serverless + reserved GPU capacity for open frontier models — a credible LiteLLM upstream for routing coding agents off the big three.
- vLLM v0.31.0 — 717 commits, DeepSeek-V4.1 FlashMLA defaults and sparse MQA — matters if you’re benchmarking self-hosted inference against Anthropic/OpenAI.
Tools & Frameworks
Claude Code v2.1.290 plugin hook additions
Adds serverToolUses to turn.step, agentId on tool.check, and a ‘ceiling’ field describing the org approval required for a tool.
Why this matters: Lets your in-house MCP servers enforce per-agent policy without rewriting prompts.
OpenHands v1.25.0
Adds bulk LLM profile import from providers and direct-prompt Model Router settings for routing between models per task.
Why this matters: Mirrors the local-plus-cloud routing pattern you run through LiteLLM.
LangGraph 1.2.13
Bug-fix release hardening checkpoint forking, update_state branching, and DeltaChannel replay semantics.
Why this matters: If any Python agents use LangGraph persistence, upgrade — several silent branch-replay bugs squashed.
Cowork drops the local Anthropic VM
Felix Rieseberg explains why Cowork moved tool execution back to the cloud: battery, disk and perf cost of a local Anthropic-provided VM were too high.
Why this matters: Data point for anyone evaluating local sandboxing for Claude-powered desktop agents.
Open Models & Local
Whistle: 16.8 MB open speech-to-text
Open ASR model at 16.8 MB covering seven European languages, runs on the same CPU engine as Needle — mobile, wearable, microcontroller class.
Why this matters: Useful building block if voice ever enters your identity/fraud flows.
Smaller models are the future of AI sovereignty
Argues for a portfolio of smaller specialised open-weight models over frontier dependency, citing governance and cost advantages.
Why this matters: Reinforces the three-tier (rules/ML/LLM) stance you already apply at the agent layer.
Industry & Trends
Inference is the most important market in software
Tunguz projects inference ~$350B by 2027, overtaking databases; usage dwarfs platform fees and compresses SaaS gross margins.
Why this matters: Shapes how you price agentic features and what fraction of COGS goes to tokens.
How many AI agents could run on 2027 chips
Epoch estimates tens to hundreds of millions of concurrent frontier agents by 2027, equivalent to 140-720M FTEs of weekly working hours.
Why this matters: Scenario sizing for the overnight-agent-factory thesis — supply isn’t the bottleneck.
AI21 runs a 10,000-GPU fleet on Kueue
Kueue-based fair scheduling on GCP cut high-priority workload wait by 83% versus ad hoc capacity negotiation.
Why this matters: Prior art if your platform team starts queueing agent training/eval jobs.
Anthropic’s $100M Claude Frontier Academy
Anthropic commits $100M to train 10,000 AI engineers by 2027 with Accenture and Morgan Stanley as launch partners.
Why this matters: Signal on where Claude-fluent hiring supply will come from in London over the next 18 months.
Sources unavailable today: Every — Chain of Thought (Dan Shipper), Last Week in AI, r/ChatGPTCoding top, r/ClaudeAI top, r/LocalLLaMA top, r/MachineLearning top
Auto-curated daily by Claude Opus 4.7 from Don’t Worry About the Vase (Zvi), Exponential View (Azeem Azhar), GitHub: All-Hands-AI/OpenHands, GitHub: anthropics/claude-code, GitHub: ggml-org/llama.cpp, GitHub: langchain-ai/langgraph, GitHub: vllm-project/vllm, Lenny’s Newsletter, SaaStr (Jason Lemkin), Simon Willison, TLDR AI, The Algorithmic Bridge (Alberto Romero), Tomasz Tunguz, Understanding AI (Timothy B. Lee). Source list and editorial profile maintained by Daniel.