Introducing the Fusion API, the smartest compound model in the market. Fusion achieves Fable-level intelligence at half the price. How it works 👇

RP GLM-5.2、1Mコンテキストに対応してる

Intelligence should be open, accessible, and ready to build with, empowering every developer, everywhere. GLM-5.2 is now available to all GLM Coding Plan users, including Lite, Pro, Max, and Team plans. docs.z.ai/devpack/latest-mod… As our new flagship model, GLM-5.2 delivers powerful coding capabilities, usable 1M-context support, and continued strengths in long-horizon tasks. API and Chatbot services will launch next week. The model will also be officially open-sourced next week under the MIT License. The future of AI is open, and it belongs to the people.

Thanks for all the feedback. GLM-5.2 will begin rolling out to all Coding Plan users in 3 hours.

Today we're releasing ZONOS2, our next-generation real-time TTS model with high-fidelity voice cloning. ZONOS2 is the most expressive open-source TTS model, released under Apache 2.0 and available on Zyphra Cloud on @AMD. 🧵

🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced! 🔷 Improved coding & agent performance over K2.6: 21.8% on Kimi Code Bench v2, 11.0% on Program Bench, and 31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6. 🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates. ⚡️ 6x High-Speed Mode coming soon! 🔌 Available today via Kimi API and Kimi Code. 🔗 Kimi Code: kimi.com/code 🔗 API: platform.moonshot.ai

We've updated the Artificial Analysis Coding Agent Index, replacing SWE-Bench Pro with Datacurve's DeepSWE benchmark - the swap lifts Codex with GPT-5.5 (xhigh) above Claude Code with Opus 4.8 (max), while the newly released Claude Fable 5 (max) in Claude Code debuts at the top DeepSWE, built by @datacurve, writes its tasks from scratch rather than adapting them from public GitHub issues or pull requests, so no model has seen the solutions during training. That matters because SWE-Bench Pro, the benchmark it replaces in our Coding Agent Index, had grown gameable, with some models recovering the fix from the repository's commit history instead of solving the task. The swap reorders the index: Codex with GPT-5.5 (xhigh) rises from 65 to 76, overtaking Claude Code with Opus 4.8 (max) at 73. Claude Code with Fable 5 (max), which enters directly on the refreshed index, leads at 77. SWE-Bench Pro had been flattering some combinations and penalizing others. More below.

Soniox v5 Async is live. Our new async speech-to-text model turns real-world audio into more accurate, structured speech data. What’s improved: • Higher accuracy across 60 languages • Completely reengineered speaker separation for identifying who said what • Improved language identification for multilingual and accented speech • Better recognition and formatting of numbers, dates, emails, IDs, codes, names, and addresses • More robust context usage for names, domain vocabulary, product terms, and custom phrases stt-async-v5 is fully compatible with the existing async API. Just update the model name. Read more: soniox.com/blog/soniox-v5-as…

Google releases DiffusionGemma.✨ The new 26B-A4B diffusion text model runs locally on 18GB RAM. It supports high-speed text generation, thinking, image, video and 256K context. Run and train via Unsloth Studio. GGUF: huggingface.co/unsloth/diffu… Guide: unsloth.ai/docs/models/diffu…

Meet DiffusionGemma! An experimental open model that explores a fast approach to text generation, released under an Apache 2.0 license. Moving beyond sequential, token-by-token processes to generate entire blocks of text simultaneously. Here’s what’s new with DiffusionGemma: 👇

New paper: Multi-Faceted Interactivity Alignment in Full-Duplex Speech Models We use RL to post-train speech models (Moshi and PersonaPlex) to talk more like a human: to know when to respond, when to wait, and when to nod along with “yeah”s and “okay”s when listening.

Fable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision. The longer and more complex the task, the larger Fable 5’s lead over our other models.

NVIDIA just dropped Nemotron-3.5-ASR: one 0.6B model, 40 languages, streaming. parakeet.cpp already runs it. On a plain CPU, 2.5x faster than @NVIDIAAI 's Nemo runtime, output byte-for-byte identical (WER 0). No GPU needed. Offline or real-time. Pick a language with --lang, or auto. GPU numbers are coming to compare with Nemo framework.

The new @GoogleColab bridges the gap between local environments and the cloud, providing a zero-friction execution platform for developers and AI agents alike. The CLI Supports: ⚡️ Agent-driven Colab workflows ⚡️ Instant GPU/TPU provisioning ⚡️ Remote script execution ⚡️ Interactive runtime access (console/REPL) Learn more in the blog: goo.gle/4dNPhF6

本日、日本語向けの新モデルを2つ公開しました🇯🇵
音声モデル：LFM2.5-Audio-1.5B-JP
言語モデル：LFM2.5-1.2B-JP-202606 LFM2.5-Audio-1.5B-JP は、Liquid AI 初の日本語音声モデルです。 日本語で話しかけると、日本語の音声で応答します。ASR・TTS を別々に組み合わせるのではなく、単一のモデルで完結するエンドツーエンドの音声モデルです。 > 日本語に対応した、このスケールでは初の汎用エンドツーエンド音声モデル > 15億（1.5B）パラメータで、J-Moshi（約77億）を上回る性能 > Qwen2.5-Omni-3B（約55億）にも匹敵する性能 > 追加学習を想定したベースモデル LFM2.5-1.2B-JP-202606 は、最新版の日本語言語モデルです。 前バージョン（LFM2.5-1.2B-JP）はすでに、JMMLU、M-IFEval、GSM8K において Qwen3-1.7B や Llama 3.2 1B を上回っていました。 今回のアップデートでは、日本語データミックスの改善と新しい中間・事後学習により、さらに広範な日本語ベンチマークで 最高性能を達成しています。 どちらのモデルも本日より利用できます。 モデル: 音声: huggingface.co/LiquidAI/LFM2… 言語: huggingface.co/LiquidAI/LFM2… ドキュメント: docs.liquid.ai

Today we’re releasing two new models for Japanese: LFM2.5-Audio-1.5B-JP (audio) and LFM2.5-1.2B-JP-202606 (text). 🧵

Introducing LFM2.5-VL-1.6B-Extract and LFM2.5-VL-450M-Extract: Vision-language models that return structured JSON, not free-form text. Pass in an image and a list of fields. Get back a clean JSON object. > Two sizes: 1.6B parameters and 450M > open-weight > run on any device SoC 🧵

Higgs Audio v3 TTS is here. Built for voice AI that speaks, not just reads: • 100 languages with single-digit WER/CER • inline control over emotion, style, prosody, and sound effects • API, Workspace, and open weights • Blog 👉 boson.ai/blog/higgs-audio-v3… Watch the demo 👇

We’ve been researching new ways for ChatGPT memory to carry context across conversations and keep it useful over time. Today, that work is rolling out as a more capable memory system in ChatGPT. openai.com/index/chatgpt-mem…

Second big release from us today: Nemotron-3.5-ASR-Streaming! 🌎40 languages ⚡️80ms - 1s controllable latency 🔥240 - 2400 concurrent streams on 1xH100 🧱FastConformer Cache-Aware RNN-T architecture huggingface.co/nvidia/nemotr…