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Replicate@replicateOfficialAI score32AIReplicate has made Wan 3.0 Prime, the accelerated variant of Alibaba's Wan 3.0, available for text-to-video, image-to-video, and reference-driven workflows. The model generates clips up to 30 seconds long in a single shot with integrated audio-visual generation.
AIReplit has made Intelligent Model Routing available to all users, automatically matching each task with a model based on quality, speed, and cost. In the company's testing, the feature delivered the same output quality at 65% lower cost than the previous version of Max Mode. Enterprise administrators can restrict routing to a company-approved set of models.
LM Studio@lmstudioOfficialAI score57AILM Studio announced that Z.ai's GLM-5.3-Flash, previously previewed as Ox Alpha, is available in LM Studio Bionic. The source says the model outperforms GLM-5.2 at 9-10x lower cost, supports image input, and is served from US-based servers with ZDR enabled by default.
Michael Truell@mntruellXAI score60AIGrok Bot is now available to all standard Grok and Cursor subscribers, with SuperGrok and Cursor Pro subscribers included. Cursor's Michael Truell says users are delegating tasks ranging from running small e-commerce businesses to testing production software. Weekly usage limits are also being reset for all users.
Google AI Developers@googleaidevsOfficialAI score30AIThe post links to a Google blog page about Gemini 3.5 Transcribe, presented as a model developers can start building with. The post itself gives no benchmark scores, pricing, or capability details beyond the link.
Google AI Developers@googleaidevsOfficialAI score47AIGoogle has released Gemini 3.5 Transcribe, a speech-to-text model that filters out spoken hesitations and accurately grounds technical terms, file names, and code variables against the active context. The model uses visual biasing to incorporate screen-aware context into developer workflows, as demonstrated in Antigravity.
Sundar Pichai@sundarpichaiXAI score42AIGoogle has released Gemini 3.5 Transcribe, a speech-to-text model that auto-detects over 85 languages and handles multiple speakers. It also supports custom vocabulary adaptation for specialized jargon. The API is available now in Google AI Studio and Gemini Enterprise.
SpaceXAI@SpaceXAIOfficialAI score42AILiveKit announces that developers can build voice agents using Grok Voice models, with full ZDR support. LiveKit's example patient intake agent cascades Grok STT, Grok 4.3, and Grok TTS through LiveKit Inference in a single AgentSession, with no separate API key or billing.
LMSYS Org@lmsysorgOfficialPickAI score65AIZ.ai released GLM-5.3-Flash, a 320B-A18B model, with day-0 support in SGLang, after appearing earlier as ox-alpha. The post calls it the first native multimodal model in the GLM-5 series and says it outperforms GLM-5.2 at one-tenth the cost, with stable 1M-token long-context performance.
Why it matters: The post reports GLM-5.3-Flash's native multimodal design, its efficiency claims, and day-0 SGLang support, which bear on running it in practice.
Unsloth AI@UnslothAIOfficialPickAI score78AIUnsloth announces that Qwen3.8-Flash-Next can be run locally through its GGUF quantizations. The source says the 1-bit version needs 75GB of RAM or unified memory, and that the 125B MoE model is reported to outperform Claude-Opus-4.6 (Max).
Why it matters: The source gives concrete local hardware requirements, quantization sizes, and a guide, showing how a 125B MoE model can run on a 75GB RAM setup.
LMSYS Org@lmsysorgOfficialAI score60AISGLang announced Day-0 support for Qwen3.8-Flash-Next, a 125B MoE model with 6B active parameters and 51B N-gram embeddings, in collaboration with Alibaba Qwen, NVIDIA, and AMD. The post reports 540 tok/s decode speed at BS=1 on NVIDIA B200 (TP4) with an NVFP4 checkpoint, and says N-gram host offloading saves 23.5 GiB VRAM per GPU and raises KV capacity by 78.5%.
Generalist@GeneralistAIOfficialAI score35AIGeneralist AI introduces GEN-1.5, its latest foundation model for the physical world, with additional task demonstrations shared in a YouTube playlist. The post links to a blog post with further details about the model.
Generalist@GeneralistAIOfficialAI score22AIGeneralist AI demonstrated that GEN-1.5 behaves differently when given different physical prompts in the same environment. The post shares a simple example responding to a request from @JagdeepBhatia8 about whether the model follows physical prompts or just the most likely action for the scene.
Z.ai@Zai_orgOfficialAI score34AIZ.ai says GLM-5.3-Flash achieves greater intelligence with less compute, attributing this to architectural enhancements and an optimized pre-training corpus. The post gives no benchmark scores, parameter counts, or pricing.
Z.ai@Zai_orgOfficialAI score36AIOn the Z.ai Code Bench, which measures real-world coding performance, GLM-5.3-Flash clearly beats GLM-5.2 at every effort level. It performs on par with Claude Opus 4.8 on the same benchmark.
Z.ai@Zai_orgOfficialAI score29AIZ.ai has published standard API pricing for GLM-5.3-Flash, charging $0.15 per 1M input tokens and $0.50 per 1M output tokens. Cached input tokens are priced at $0.03 per 1M tokens.
AIAi2 has released Llama-B-8B on Hugging Face, a byte-level autoregressive language model retrofitted from Llama 3 8B through a short additional training procedure. The model operates over bytes instead of tokens and is licensed under the Llama 3 Community License for research and educational use. It requires transformers 4.57.3 and the xlstm package, and the source notes that model outputs can be inaccurate and should be verified.
AIAi2 has released allenai/Llama-B-8B-Stage1, a Llama 3 8B model retrofitted to operate over bytes instead of tokens through a short additional training procedure. This Stage 1 checkpoint contains only Stage 1 training, with inner model parameters unchanged, and is licensed under the Llama 3 Community License for research and educational use. It requires transformers 4.57.3 or later and the xlstm package, and is loaded with trust_remote_code.
AIAi2 has released Bwen-8B, a byte-level autoregressive language model retrofitted from Qwen3 8B Base through a short additional training procedure called byteification, which lets it operate over bytes instead of tokens. The model is licensed under Apache 2.0 for research and educational use, and requires transformers 4.57.3 or later and the xlstm package.
AIAi2 has released Bwen-8B-Stage1 on Hugging Face, a byte-level autoregressive model retrofitted from Qwen3-8B-Base through a short additional training procedure. This Stage 1 checkpoint contains only Stage 1 training, with inner model parameters unchanged, and is licensed under Apache 2.0 for research and educational use.
AIAi2 has released Bolmo-1B-Stage1, a 1B-parameter byte-level language model retrofitted from OLMo 2 1B to process bytes rather than tokens. This checkpoint includes Stage 1 training only, with inner model parameters unchanged, and is available on Hugging Face under an Apache 2.0 license for research and educational use.
AIAi2 has released Bolmo-7B-Stage1, a 7B byte-level language model retrofitted from Olmo 3 7B through a short additional training procedure. This checkpoint includes only Stage 1 training, with inner model parameters unchanged, and is licensed under Apache 2.0 for research and educational use.
AIDeepSeek V4 Pro 0813 scored 95.2% on SWE-Bench Verified, ahead of Kimi K3 at 92.6% and Fable 5 at 85.4%, in Fireworks AI's eval runs. It costs $0.309 per solved task on SWE-bench versus $0.808 for Fable 5, and it is available through Fireworks serverless and dedicated endpoints, with SFT, DPO, and RFT training support. Its 1M-token context window and native tool calling target long-horizon agentic workloads, though its Java accuracy on Aider Polyglot (48.9%) trails Fable 5 (74.5%).
AIHarvey and Fireworks post-trained Tenet from the Kimi K3 base using asynchronous reinforcement learning on the Fireworks Training API for long-horizon legal work. On the Legal Agent Benchmark, Tenet reached 19.7% all-pass versus 10.8% for base Kimi K3, and its cost per task was $5.92 versus $5.62.
AIZ.ai has released GLM-5.3-Flash, a model with native visual capabilities that observe interfaces, rendering results, and interaction feedback across code, browsers, and GUIs. It uses a hybrid linear and sparse attention architecture with 320B total parameters and 18B activated, which the company says significantly reduces compute and KV-cache requirements. The release notes also describe support for office document and financial research workflows.
Why it matters: The release notes give GLM-5.3-Flash's architecture, parameter counts, and cybersecurity findings, which make the model's scope concrete for comparison with earlier GLM releases.
cat@_catwuXAI score38AIAnthropic's Claude now shares one memory across chat and Claude Cowork, so information saved once carries over between surfaces. Cowork tasks start from what Claude already knows from your chats, such as project context, preferences, or past clients, and users decide what the memory holds.
Vercel@vercelOfficialAI score38AIVercel has introduced run, a hardened QuickJS sandbox for coding agents that exposes only approved host functions. It can pause for human approval before resuming, and it runs anywhere Node.js runs.
Andrew Ng@AndrewYNgXAI score46AIOpenWorker, an open source agent that completes tasks on a laptop, has released a new version with built-in cybersecurity agents. The agents scan code for vulnerabilities, scan dependencies for supply chain injections, and check cloud security configurations for attack surfaces. Users can run open weight models locally so sensitive code stays on their machine.
v0@v0OfficialAI score40AIv0 now lets users connect apps directly to Slack, GitHub, Notion, Salesforce, and other services through Vercel Connect. Vercel describes Connect as generally available, offering short-lived scoped access tokens, token and trigger observability, and RBAC with audit trails for 100+ services.
Vercel@vercelOfficialAI score53AIVercel Connect is now generally available, letting apps and agents securely access more than 100 services, including Slack, Linear, and GitHub. It uses short-lived, scoped access tokens, token and trigger observability, and RBAC with audit trails.
Google Labs@GoogleLabsOfficialAI score22AIGoogle Labs has introduced Play with Putty, an experimental collaborative vibe coding tool that lets users build tools and websites together in real time. It is available through a waitlist at labs.google/playwithputty and is limited to users in the US aged 18 and over.
AIMicrosoft Marketplace has made intelligent discovery generally available worldwide, letting customers describe business challenges in natural language and receive contextual recommendations and conversational comparisons. Early preview results show customers were 68% more likely to find solutions that met their needs and take the next step toward purchase.
Unsloth AI@UnslothAIOfficialAI score34AIUnsloth now lets users fine-tune Qwen3.8-27B for free with its notebook, with local training running on 24GB VRAM. The company says its method trains the model 1.5x faster while using 50% less VRAM.
Daniel Han@danielhanchenXAI score60AIQwen announced Qwen3.8-Flash-Next, an open-weight multimodal MoE model built on the new Qwen4 architecture. The model will be released tomorrow, and Unsloth is preparing day-zero support.
AIZ.ai released GLM-5.3-Flash on Hugging Face, the first natively multimodal model in the GLM-5 series, with 320B total parameters and 18B active parameters. The source says it outperforms GLM-5.2 across benchmarks at one-tenth the price and approaches Claude Opus 4.8 on coding and agentic benchmarks. It adopts a hybrid sparse and linear attention architecture to reduce long-context serving costs.
Why it matters: The release shows a hybrid sparse and linear attention design aimed at cutting long-context serving costs, which is useful for comparing efficiency trade-offs.
AIZ.ai released GLM-5.3 on Hugging Face, built on the same base model as GLM-5.2, with all gains coming from post-training. The source reports a 50% improvement over GLM-5.2 on Z.ai Code Bench and open-source SOTA on Terminal Bench 3.0 and Agents' Last Exam, with a benchmark table comparing it against Kimi K3, DeepSeek-V4 Pro-0813, Qwen3.8-Max, and others.
Why it matters: The source gives benchmark tables against GLM-5.2 and rival models, showing where the post-training gains concentrate in coding and cyber tasks.
Varun Mohan@_mohansoloXAI score32AIAntigravity now includes a built-in terminal and version control support, according to Varun Mohan's post. The post says the team is continuing to optimize the experience for developers.
AIGoogle Research has published the official PyTorch weights and configurations for TimesFM 3.0, a pretrained time-series foundation model for forecasting. The model uses a Stacked Mixing Transformer with 20 layers, a model dimension of 1280, and 16 heads, and it is released under the TimesFM Non-Commercial License v1.0.
SpaceXAI@SpaceXAIOfficialAI score46AIxAI has made Grok Voice Think Fast 2.0 available through its API and in the Agent Builder for building voice agents. Developers can build, tune, and deploy voice agents at console.x.ai, with more details in the linked announcement.
SpaceXAI@SpaceXAIOfficialAI score49AIStarlink is using Grok Voice to handle over 15,000 inbound customer support and sales calls per day. Grok diagnoses hardware issues, ships replacements, and fulfills over 3,000 orders a week across voice calls and chat.