AI Coding Live News

On 2026-11-05 World Labs released research preview Frameboy: a highly optimized Atlas variant streamed from cloud GPUs to the browser at up to ~15 fps (vendor claim) with live camera control. A public demo and a Viewfinder closed-beta overlay shipped together; CEO Fei-Fei Li amplified “Real time Atlas” on X.

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On Nov 2 Meituan's LongCat team listed LongCat-2.5 in its API platform change log as the full release of September 25's LongCat-2.5-Preview. The official technical blog says it has 1.6 trillion total parameters with about 48 billion activated per token, builds on LongCat-2.0 with stronger native visual understanding and agentic coding, and was trained and served with W4A4 inference on domestic AI accelerators. Vendor-reported scores include 88.4 on Terminal Bench v2.1, 38.5 on Terminal Bench v4.0, 91.9 on BrowseComp and 83.1 on MCP Atlas. The API speaks both OpenAI and Anthropic formats with a 1M-token context and up to 128K output tokens, at a limited-time price of $0.30 per 1M uncached input tokens, $0.006 cached input and $1.20 output.

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On 2026-10-23 Artificial Analysis launched Coding Agent Index v2.0, which scores model-plus-harness combinations across 290 tasks with three equally weighted benchmarks: FrontierCode v1.1 from Cognition (100 tasks on real open-source repos, graded on whether a maintainer would merge the change) replaces DeepSWE v1.1, SWE-Atlas-QnA becomes the stricter SWE-Atlas-QnA-AA, and Terminal-Bench 4.0 is unchanged. Claude Code with Claude Opus 5.5 (max) leads at 61.7, ahead of Sonnet 5.5 at 59.3 and Muse Wonder Full at 58.9. Scores fall across the board: the 21 configurations measured on both versions drop from a mean of 54.8 to 47.4.

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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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Meta AI published the technical report for Muse Glimmer 30B (arXiv:2610.24628), an open-source 30-billion parameter causal language model with an integrated perception encoder designed for on-device autonomous agents. Quantized to approximately 4 bits, Muse Glimmer operates inside 32GB of VRAM on a single consumer GPU (such as an RTX 5090) without cloud reliance. On rigorous agentic evaluations, Muse Glimmer sets new records for its size class: achieving 75.5 on MCPAtlas (surpassing Gemma4-31B at 54.2 and Qwen3.6-27B at 62.5) and 51.2 on SWE-Bench Pro, released fully under the Apache 2.0 license.

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Inception co-founder Stefano Ermon officially unveiled Mercury 3, the company's next-generation diffusion-based large language model. Delivering an astonishing 1,068 tokens per second inference speed on NVIDIA GPUs, Mercury 3 scales to 40x the size of Mercury 1 with a native 1M context window. Benchmarked on IFBench, GPQA Diamond, and SWE-Bench Atlas, it matches frontier closed baselines with standard API pricing of $0.20 / $0.70 per 1M input/output tokens (with 50% promotional pricing of $0.10 / $0.35).

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On October 19 Inception released Mercury 3, which it calls the most capable diffusion LLM (dLLM) to date. Per the vendor, it is more than 40x the size of Mercury 1, outputs 1,068 tokens/s, expands context from 260K (Mercury 2.5) to 1M tokens, and beats GPT-6 Luna and Claude Haiku 5.5 (both medium) on GPQA Diamond, IFBench, SWE-Bench Atlas and more. List price is $0.20/M input and $0.70/M output, 50% off at launch. It is live on the Inception API, OpenRouter, Baseten and Vercel AI Gateway with an OpenAI-compatible API. All scores are vendor-reported and not yet independently reproduced.

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On 2026-10-15 Meta released weights for Muse Spark Open, a natively multimodal MoE (~816B total / ~42B active per token, 1M context) aimed at long-horizon coding and agents. Weights are on Hugging Face and peers; hosted APIs include Together, Fireworks, Groq and OpenRouter. Reported figures include DeepSWE 60%, MCP-Atlas 89.2% and JobBench 61.8% (see Meta’s evaluation methodology).

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At Team '26 Europe, Atlassian introduced AMP, a framework giving agents an assigned identity, scoped authority, shared Teamwork Graph context and reviewable output, and made a rebuilt Atlassian MCP generally available with 220+ tools, OAuth 2.1/PKCE and tiered read/write/destructive scopes.

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On 2026-10-16 Hugging Face and Reflection confirmed Beam weights are downloadable: ~501B-total / ~23B-active sparse MoE, 1M context, Apache 2.0. BF16/FP8/NVFP4 checkpoints ship with day-0 transformers≥5.20.1, vLLM and SGLang. Model-card figures (vendor): SWE-bench Verified 81.6% (BF16), Terminal-Bench 2.1 80.1%, MCP Atlas 80.8%. This closes the Oct 5 promise to release weights later that month.

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On 2 Oct 2026 OpenRouter shipped Model Router Benchmarks: seven model routers (Auto, Jev, NVIDIA Switchyard, Unbiased Pareto, Sakana Fugu, and variants) compared on GPQA Diamond, Tau3 Banking, MMMU Pro Vision, SWE Atlas QA, Deep SWE, and Terminal Bench 2.1. The Router Index defaults to quality 60% / time 20% / cost 20%. openrouter/pareto-code and Fusion are not on this board.

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Claude (@claudeai) launched Claude Marketplace—one place for connectors/plugins, agents/products, and service partners. Customers get 2,000+ connectors (Atlassian, Google, Microsoft, Notion, Salesforce, …), can apply Anthropic committed spend to Claude-powered software from CrowdStrike, Cursor, Harvey, Legora, Lovable, Snowflake, and engage Accenture/BCG/Deloitte-style partners. Builders can list to reach Claude teams.

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