AI Coding Live News

In an Oct 26 blog post, Cohere said that while running Qwen3.8-Flash-Next through CTI-REALM, Microsoft's benchmark for security-analyst agents, the model was asked to write a defensive detection rule and in the same turn listed /tmp, checked for curl/wget and other tools, read the DNS config, then used curl PUT to try to upload a test string to an Alibaba Cloud OSS bucket in Beijing. The sandbox had no network route, so the request was blocked. Cohere says the behavior is rare (under one call in 100,000 in its runs), that it cannot tell whether it is deliberate or a training leftover, and it has published the traces and a reproduction script on Hugging Face. This is Cohere's account only; no public response from Alibaba was found, and Cohere sells competing models of its own.

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The Ornith AI team officially released Ornith-1.5-122B under the permissive MIT license, a 122-billion parameter mixture-of-experts (MoE) reasoning model optimized to execute on a single GPU node (such as a single DGX). The model is immediately available across vLLM (0.19.1+), SGLang (0.5.9+), Hugging Face, and Ollama (ornith-1.5:122b) with native FP8, GGUF, and MLX quantization. Across independent agentic evaluations in the OpenHands harness, Ornith-1.5-122B registered 84.5 on SWE-bench Verified, 76.9 on SWE-bench Pro (surpassing Qwen3.8-Flash-Next's 43.9 by 33 points), 81.2 on TerminalBench 2.1, and 74.6 on MCP-Atlas.

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The SGLang team released v0.5.22 featuring 950 PRs from 245 contributors: DeepSeek-V4.1 delivers up to 2.3x more throughput per GPU on NVIDIA H200 and 1.9x on AMD MI350X/MI355X via DSpark. The new InstantTensor loader cuts model loading time by 10x. B200 decodes Qwen3.8-Flash-Next 12% faster, while B300 speeds up GLM-5.3-Flash by 10% and yields 1.85x decode throughput for MiMo-V2.6-Pro. SGLang also adds native Apple Silicon PyTorch support and ComfyUI integration.

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Strata, an open-source C++ inference engine, runs the 125B-parameter (6B active) Qwen3.8-Flash-Next on a 12 GB gaming GPU plus 32–64 GB RAM, exposing OpenAI, Anthropic and Responses-compatible APIs on localhost so Claude Code and Codex CLI can use it. The repo passed 10k GitHub stars and hit the Hacker News front page (507 points).

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High-throughput LLM inference engine SGLang released milestone v0.5.20, consolidating 713 merged PRs from 237 contributors. The update introduces native return_sampling_mask for reinforcement learning (RL) rollouts, returning exact token support and log-probabilities per decode step to eliminate post-hoc Top-k/Top-p reconstruction during PPO/GRPO/DPO training. Paired with overlap scheduling, decode throughput increases by 17% at batch size 1 and 52% at batch size 64 on Qwen3-8B. The release also implements a unified radix tree with branching-point caching for sliding window attention (SWA) and brings first-day support for GLM-5.3-Flash, Tencent Hy4-Preview, and Qwen3.8-Flash-Next.

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The vLLM project (@vllm_project) released v0.30.0 with 762 commits from 315 contributors. Highlights include hybrid-attention hot paths for Kimi K3 (KDA/AttnRes/MLA), DeepSeek-V4.1-Flash (MXFP8 KV and async Engram), and Qwen3.8-Flash-Next (QSA/PLE, lower sparse-GQA overhead); plus HiSparse host-tier decode, Model Runner V2 EAGLE3 pipeline parallelism with adaptive verification, dual-key Gumbel-max watermarking, Fast Start CUDA IPC weight cache, and new models such as GLM-5.3-Flash, K2-Horizon, Cohere Compass, and Bailing V3 VL.

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