AI News

‹Mon, October 5›

0113

Reflection AI debuts Beam, a 501B open-weight model aimed at Chinese rivals

Reflection AI, the Nvidia-backed US startup founded by ex-DeepMind researchers, unveiled Beam — its first open-weight model — a text-only mixture-of-experts system with 501B total and 23B active parameters, pretrained on 23.8T tokens with a 1M-token context window. The company says Beam matches Z.ai's GLM-5.2 on reasoning, coding and agentic benchmarks while using 3–4x less inference compute, and approaches Qwen 3.8-Max; the claims have not been independently verified. Full weights are promised this month under an Apache 2.0 license.

IIT之家 AI·2d

023

Open source

Strata reportedly runs 125B Qwen model on 12GB GPUs

Developer Niko1221 has open-sourced the Strata engine, which reportedly runs a quantized Qwen3.8-Flash-Next model with 125 billion parameters on consumer GPUs with at least 12GB of VRAM. The engine keeps the MoE model in system RAM, loads frequently used experts into VRAM, and uses a lightweight model for speculative decoding; reported tests reached 94 tokens per second on an RTX 5070 with a 2-bit quantization.

IIT之家 AI·2d

033

Open source

Termexo v0.10.10 adds 19 local MCP tools and agent auto-connect

MIT-licensed Windows AI coding workspace Termexo released v0.10.10, exposing its terminal, tasks, and some settings as 19 local MCP tools. These connections are automatically added to newly launched Claude Code, Codex, OpenCode, Grok Build, and Antigravity terminals in Termexo.

开开源中国·2d

047

Open source

RemoveMacAI removes Apple Intelligence features from macOS 27

RemoveMacAI is an open-source command-line tool that removes selected or all Apple Intelligence features from macOS 27 using an approved configuration profile and Apple’s asset service. Its developer says the approach leaves System Integrity Protection enabled and avoids directly modifying /System; users can revert the changes and restore the models when features are re-enabled.

AArs Technica AI·2d

050

Open source

GitHub launches ReviewBench benchmark for AI code review

GitHub introduced ReviewBench, an open benchmark for evaluating AI code review agents. The benchmark covers 219 pull requests from 187 public repositories across 19 languages, uses a multi-source golden set, and supports precision, recall, severity, and category-based analysis. GitHub says its offline results have shown alignment with production experiments for GitHub Copilot code review.

GGitHub Blog · AI & ML·2d

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