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Replit has launched Free Mode, a new option that lets users create far more with their existing monthly subscription and no extra usage costs.

Powered by OpenAI’s GPT-5.6 Luna, Free Mode allows Core subscribers to build up to 30 times more than before. Everyday tasks like chatting, ideating, and running simple projects no longer consume credits. The company says this removes the constant worry about token limits so people can focus on actual creation.

The update also brings a refreshed interface designed to move users straight from idea to finished work. Replit positions the platform as an all-in-one daily tool that handles quick questions and full builds in the same place while carrying context across projects.

Core plans start at $20 a month. Users can stay in Free Mode until they hit their limits, which reset every five hours, or switch to Power Mode or Max Mode for more demanding work. Pro subscribers get higher limits.

Replit says the change responds to feedback that AI creation was becoming too expensive for regular use. The company frames Free Mode as a step toward making high-quality software building accessible to anyone with an idea.

Cartesia has launched Sonic-3.6, the newest version of its text-to-speech system. The company calls it the most lifelike model it has built so far.

The update arrives just three months after Sonic-3.5. Cartesia says it made major model changes after gathering feedback from teams already using the earlier version. The result is clearer natural speech across 44 languages, with better pauses, filler words, and smooth shifts between languages such as Hindi and English.

Sonic-3.6 currently ranks first on the Artificial Analysis leaderboards for both provider and controlled voice streaming. The company highlights strong performance in voice quality and the underlying model.

The new model is open for beta testing now. Users can access it through the Cartesia website.

Dots Studio just dropped the preview of dots3-note, a new open model built for real-world agent tasks that stretch over long periods.

It uses a 280B MoE setup with only 16B parameters active at once, plus a 512K context window. The model handles text, vision, and audio together.

A fresh training method called TEMPO helps it learn long-horizon behavior through self-critique and value estimation that scales at test time. The system can reason through problems, explore new settings, keep updating its memory, and mix perception with coding plus tool use to finish complex jobs.

Weights are available on Hugging Face. The team also released two new benchmarks for real-life agents called VibeSearchBench and VibeLifeBench. Early results show it holds up well against much bigger models on reasoning, agent, and multimodal tests.

Z.ai has released GLM-5.3, its latest model focused on strong coding performance and cybersecurity work. The company describes it as built to code and ready for cyber defense.

The model draws from post-training on a 743B base model. Z.ai says this delivers top-tier coding and agentic abilities. It also marks a clear step forward in cybersecurity performance among open models.

GLM-5.3 is available right away through the GLM Coding Plan and ZCode platform. API access and open weights will follow later, after safety evaluations are complete. An initial group of partners is already offering services powered by the model under Z.ai’s safeguards and usage rules.

The update continues Z.ai’s push into practical coding agents and security-related tasks. Users can try it now via the company’s coding plan or ZCode.

OpenAI has launched Computer History for the ChatGPT desktop app on Mac. The update lets ChatGPT track activity across apps and websites so conversations feel more relevant and need less repeated context.

The tool expands on the Chronicle research preview. It cuts token use and adds tighter privacy settings. Users get a timeline view that shows recent work and helps surface patterns from everyday tasks.

Full control stays with the user. From the timeline or menu bar anyone can delete all or selected history, choose which apps and sites to include or skip, and pause or restart the feature at any time.

Activation sits under Settings then Integrations inside the ChatGPT desktop app. The feature is available now to Pro, Business, and Enterprise customers around the world. Access for the EEA, UK, and Switzerland arrives in the coming weeks.

Google has released Gemini 3.7 Flash, its latest workhorse model focused on coding, agent workflows, and everyday tasks. The update comes just three weeks after Gemini 3.6 Flash and brings clear gains in several key areas.

On coding benchmarks the model jumps from 34.4% to 43.6% on FrontierCode 1.1 Main and from 49% to 65.3% on DeepSWE v1.1. Web development scores also improve, with a higher Elo on WebDev Arena. Document processing and real-world business workflow tests show solid lifts as well.

Pricing is lower for a limited time. Through the end of 2026 it costs $0.75 per million input tokens and $3.75 per million output tokens, half the previous Flash rate. The model is live in the Gemini API, AI Studio, Gemini Enterprise, and powers the Spark agent for AI Pro and Ultra subscribers in the Gemini app.

Logan Kilpatrick shared a chart comparing intelligence, speed, and cost against other leading models. Gemini 3.7 Flash stands out for its high output speed while staying competitive on performance and price.

OpenAI just shared a preview of Ultrafast mode for its GPT-5.6 Sol model. The setup delivers responses up to 14 times faster than before and can hit as high as 750 tokens per second.

This first rollout happens through the OpenAI API and starts with a limited group of customers. Access will grow as capacity increases. The speed boost comes from Cerebras hardware.

The company points to clear use cases where every second matters. Real-time voice systems, customer support tools, commerce platforms, coding workflows, design work, financial research, and security response all stand to gain from the faster frontier intelligence.

OpenAI is currently working with that early set of businesses to learn where the extra speed creates the biggest impact. Those insights will shape future product decisions. Companies that need this level of performance can already request notifications as more capacity opens up.

DeepSeek has officially released DeepSeek-V4-Pro today. The update focuses on major agent improvements that deliver clearer gains in real production use.

The model now supports flexible reasoning effort levels for both V4-Pro and V4-Flash. Users can pick low effort for simple tasks, high for everyday agent work, or max for tougher problems. It also adds native support for the OpenAI Responses API and works smoothly with Codex through a simple one-click setup.

V4 Pro is live right now on the DeepSeek app and web platform under Expert Mode. It is available through the API as well, with model names staying the same.

Alongside the launch, DeepSeek is changing its API pricing. Peak and off-peak rates take effect at 16:00 UTC on August 16, 2026. Off-peak rates sit 50 percent lower than peak rates, giving users more room to schedule workloads when costs matter most.

Benchmark results shared by the company show solid jumps on agent and coding tasks compared with earlier previews. The model keeps its 1 million token context window and remains positioned as a strong option for complex, multi-step work.

Mureka has released version 9.5 of its AI music platform. The new build delivers vocals that sound more natural, arrangements that track user prompts more closely, and genre results that feel intentional from start to finish.

The company says the update makes generated tracks more human and more musical overall. Users can start creating with Mureka V9.5 now at mureka.ai/mureka-9-5.

Liquid AI just dropped LFM2.5-VL-3B, a compact vision-language model built for real-world use. It reads screens on phones, websites, and desktops, pulls text and data from documents and charts, locates objects with precise coordinates, and can call tools from either text or image prompts.

The model sits on the LFM2.5-2.6B base and pairs it with a SigLIP2 400M vision encoder. It was trained on about 34 trillion tokens and uses a 128K vocabulary. On key tests it holds its own against models more than twice its size. ScreenSpot-v2 hits 80.7, RealWorldQA reaches 73.1, TextVQA scores 84.3, and RefCOCO averages 87.9. Tool use also jumped sharply to 59.5 on ToolSandbox.

Speed and size stand out. It runs at 228 tokens per second on an Apple M5 Max and 116 tokens per second on an AMD Ryzen AI Max+ 395 while staying around 3 GB of memory. Even a Galaxy S26 Ultra phone can manage 20 tokens per second, so private on-device use becomes practical. Day-one support covers llama.cpp, MLX, vLLM, SGLang, and ONNX.

On a single H100 it delivers a 34 ms time to first token on multi-image inputs and roughly 11,000 output tokens per second under high load. That works out to nearly a billion tokens a day from one GPU.

LFM2.5-VL-3B fits screen agents, document work, grounding tasks, and multi-image jobs that need quick answers.

xAI has rolled out Grok 4.6, its latest model that improves on Grok 4.5 while keeping the same pricing.

The new version focuses on long-running agents and tougher multi-step work. It handles research, codebases, and turning ideas into working apps or visual projects more reliably than before. Benchmarks show it matching top models on the Artificial Analysis Intelligence Index and leading on several practical agent and knowledge-work tests.

Pricing stays at $2 per million input tokens and $6 per million output tokens, which is half the cost of many other frontier models. A faster variant costs twice as much.

Grok 4.6 is live now in Cursor, Grok Build, Grok Bot, and the API. For the first week, users get double the included usage in Cursor and Grok Build.

Alibaba’s Wan team just released Wan-Animate-2, a big step up for their open source character animation model. The update focuses on cleaner motion transfer, better multi character scenes, and more creative control.

It maps motion and micro expressions accurately across humans, cartoons, robots, and animals without relying on explicit pose skeletons. The reference video itself becomes the motion guide. Users can also animate several characters in one scene while keeping each identity distinct.

Camera angles can now be shifted with simple text prompts like “top view,” independent of the driving video. A lighter version supports real time streaming so long sequences generate chunk by chunk without visible quality drop.

Unsloth AI has launched Unsloth Desktop, an open-source desktop application that lets users run and train AI models directly on their own machines. The app works across Mac, Windows, and Linux systems.

Key features include support for MLX, diffusion models for images and video, audio processing, and GGUF formats. Users can connect tools like Claude Code and Codex to local large language models. The software claims 50 percent more accurate self-healing tool calls along with sandboxed code execution.

It handles both CPU and multi-GPU setups covering NVIDIA, AMD, Intel, and Mac hardware. Training runs up to twice as fast while using 70 percent less VRAM. Additional capabilities cover private web search, deep research, RAG, MCP, and model exports in formats like NVFP4 and GGUF.

The app also provides an OpenAI-compatible API, access to cloud models, and options for secure remote deployment of LLMs.

NVIDIA has released Nemotron 3.5 Lightning, a new open mixture-of-experts model with 30 billion total parameters and just 3 billion active ones. The model targets always-on agents that handle large numbers of specialized tasks and claims up to four times the output speed of similar-sized models.

On the PinchBench test it scored 86 percent accuracy while finishing 10,000 tasks 35 percent faster than Qwen3.6 35B at comparable accuracy. Teams can post-train it with NVIDIA NeMo using their own domain data, tools, workflows and policies. Early results show accuracy gains in cybersecurity, coding, legal and energy workloads.

The model is sized to run from an NVIDIA DGX Spark all the way up to full data-center setups, making it practical for long-running agent workflows that spend most of their time calling tools and validating results.

Alongside the model, NVIDIA is also releasing NeMo Switchyard, an open-source library for routing requests between different models. Developers can send complex reasoning and planning steps to larger frontier models and hand high-volume specialized execution to Lightning.

Google has added Gemini-3.7-flash to the model options in its official Python GenAI SDK. The change showed up in a recent GitHub pull request for the googleapis/python-genai repository.

This move points to Gemini 3.7 Flash getting closer to release. No official launch date has been shared yet, but the update signals active preparation on Google’s side.

The news comes as competition in the AI space heats up with recent model drops from OpenAI and other labs. Gemini Flash will need strong performance gains to stand out in this crowded field.

OpenAI announced an expansion of its Daybreak cybersecurity initiative on Monday, introducing GPT-5.6-Cyber, a specialized model built for advanced and authorized cybersecurity tasks.

The company said the move aims to equip trusted defenders with frontier AI tools as threats grow more sophisticated. The goal is to give security teams an edge before attackers can scale offensive AI capabilities.

Daybreak now includes two tracks. Daybreak Blue offers access to frontier models such as GPT-5.6 Sol and focuses on everyday defensive work. This covers vulnerability discovery, secure code review, malware analysis, incident response, and patch validation. OpenAI calls it the recommended starting point for most defenders.

Daybreak Red provides purpose-trained models including GPT-5.6-Cyber. It targets experienced teams handling complex authorized work like vulnerability research, exploit validation, and security testing.

OpenAI reported using GPT-5.6-Cyber in real-world research that uncovered previously unknown vulnerabilities in popular open-source software, including Chrome’s V8 engine.

Access remains restricted to approved defenders. Higher-risk work comes with extra controls and monitoring to maintain strong safeguards.

Meta has released Muse Glimmer, a new 30 billion parameter open weight model built for local agent workflows that stay active without cloud dependence.

The model targets everyday hardware such as Macs and PCs equipped with capable GPUs. It delivers solid results on agent focused tasks and benchmarks against other models in the same size range. Weights come under the Apache 2.0 license so developers can use and adapt them freely.

To keep it practical on consumer machines Meta applied quantization that brings the model under 20 GB and paired it with a lightweight DFlash drafter system. This combination keeps response times low enough for smooth conversation and real time interaction entirely on device.

In a demonstration the model handled a full multi step job from one plain language request. It located a local Home Assistant setup through network tools, pulled device data, wrote a complete HTML CSS and JavaScript dashboard from scratch, then launched a local server to confirm everything worked.

Download links and technical details appear on Hugging Face along with Meta’s research blog and developer resources.

MiniMax Hub has been renamed MiniMax Design. The change went live on August 10 2026.

Free credits and annual membership discounts now run until August 15. Users who buy an annual membership before that date lock in 20 percent off H3 generations for a full year. Free access also continues through the same deadline so people can keep testing the platform.

Alibaba’s Wan team has rolled out Wan 3.0 in public beta. The new model generates videos up to 30 seconds long in a single pass and aims for more realistic, consistent frames.

Key upgrades include stronger character expression, better handling of digital elements, and an expanded input system called Omni Reference. Users can now feed it text, images, audio, video, documents, spreadsheets, slides, webpages, PDFs, and other file types. The model reads the material and builds video from it.

Access is live on Alibaba Cloud Model Studio and Qwen Cloud. The official wan.video site will open soon for members. API pricing starts at $0.05 per second for 480p, $0.10 for 720p, and $0.20 for 1080p.

Full API access is still rolling out. Creators can apply for the beta and start testing right away.