GPT-6.1 Terra: delivering fast and capable computer use at a lower price. GPT-6.1 Terra understands what’s on screen, takes action across apps, writes naturally, and is a more capable model for your whole workday with the efficiency to take on more of it.

Opus 5.5 is one of anthropics biggest success. on OpenRouter token volume went up 3.6x since launch. And I havent heard anyone saying Opus 5.5 is a bad model. Its the oppostite. Everyone loves it. If they stick to this approach, Fable 5.5 will be the biggest success ever. No wonder they keep it until IPO.

Not just PHP. Node.js has also announced security releases for October 21, with HIGH-severity vulnerabilities affecting its 26.x, 24.x and 22.x release lines. If you run either stack in production, keep an eye on official advisories and apply patches promptly. Security maintenance doesn't stop at your application code. Your runtime matters too. Node.js advisory: nodejs.org/en/blog/vulnerabi…

Sage-A1.5 is here, bringing 256K context, parallel research, and evidence checks to long-horizon scientific workflows. 🤖 modelscope.ai/collections/In… 🏆 SOTA across scientific benchmarks: Scores 90.0 on PinchBench, 81.0 on FrontierScience-Olympiad, and 48.3 on FrontierScience-Research, ahead of Kimi-K3, GLM-5.3, and GPT-5.6-sol in the reported comparison. 🧩 Agentic Orchestration: When enabled, delegates independent investigations to parallel subagents with isolated contexts, then integrates their evidence and findings to guide subsequent work. ✅ Verification: Optional Verification Mode reviews progress, checks evidence and assumptions, and redirects stalled searches within the model's own reasoning, without a separate critic model at inference. 🔬 Open Scientific Discovery: Supports exploratory research through tool-assisted analysis and produces inspectable research artifacts, extending its use beyond predefined question answering. 🛠️ Native tool use for research: Supports APIs, code interpreters, search engines, and external tools for tool-augmented scientific reasoning and professional workflows. ⚡ Available in BF16, FP8, and GGUF F16/Q8/Q4 formats, with Transformers, vLLM, and SGLang support. 📜 Apache 2.0.

@thdxr This dynamic agent driven "model picking" is somethin I really miss in openCode right now. For me it feels right now it would be nice to just have an array of models per agent and then a default one (if the user uses the agent manually). Would love to use it in some kind of delegate workflow, this is currently not possible right? (e.g. Opus delegating to an explore/build agent running sonnet)

🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4

Today we release 𝙻𝙵𝙼𝟸.𝟻-𝟸𝟺𝙱-𝙰𝟸𝙱, the largest 𝙻𝙵𝙼𝟸.𝟻 family member. It is an efficient local model for laptops and PCs to work through multi-step tasks inside popular agent harnesses. > 24B total parameters, 2B active per token > Context expanded to 131K tokens > A 128K-token vocabulary > 33T pretraining tokens > It is a reasoning model > Very easy to fine-tune and customize > Performs competitively with Qwen3.6-35B-A3B, a model with ~50% more total and active parameters, on agentic and tool-use tasks. > Open base and post-trained weights on @huggingface 🤗 1/