Grok 4.7 Lands in Copilot, Cursor and the API

Five things shipped in AI this week that people are already putting to work. One new frontier model, two open-weight releases you can download tonight, an image model with a licensing catch, and a coding agent that went open source for an uncomfortable reason. Every item below has a live Reddit thread behind it.

Grok 4.7 arrives in Copilot, Cursor and the xAI API

ModelConfirmed in r/singularityView thread

xAI released Grok 4.7 on September 21, pitching it as a model for coding and long knowledge-work tasks that works longer on hard problems and checks its own output. The useful part is reach: it landed the same day in GitHub Copilot, in Cursor and on the Grok API, so most developers can try it without a new account.

SiliconANGLE reports pricing of $2 per million input tokens and $6 per million output, with a faster variant at twice the price. It also puts Grok 4.7 at 46.3% on CursorBench, behind Claude Fable 5.1 Max at 51.8%.

On r/singularity, the benchmarks thread is doing the careful reading. Commenters point out the new scores were run at a higher reasoning setting than Grok 4.6's, and they question how many tokens it burns to get there.

What to do: if you use Copilot or Cursor, switch models for one real task this week and watch the token bill, not just the answer.

Qwen-Image-2.1 edits and generates in one model, with transparency

ModelConfirmed in r/StableDiffusionView thread

Alibaba's Qwen team released Qwen-Image-2.1, a 7-billion-parameter image model that handles both generation and editing. Two features stand out for working designers: it outputs native transparent PNGs, and it accepts up to 10 reference images in one prompt.

The r/StableDiffusion crowd moved fast. One tester called it "pixel precise at 2K" and walked through multi-reference work, and a follow-up tips thread covers pose replacement and texture and style transfer. Users there report it already runs inside ComfyUI, and r/LocalLLaMA picked up the release too.

The catch is the license. The model ships under the Qwen Research License Agreement, not an open-source license, and AI Weekly frames it as a move to research-only terms.

What to do: use it freely for mockups, cutouts and experiments. Read the license before anything it makes goes into client or paid work.

Ternary Bonsai 2 squeezes a 27B model into 5.9 GB

ModelConfirmed in r/LocalLLaMAView thread

PrismML released Ternary Bonsai 2 27B on September 17. It compresses Qwen3.8-27B to 5.9 GB, about 1.76 effective bits per weight, under the Apache-2.0 license. That puts a capable 27B model on a single consumer GPU or a laptop.

PrismML claims it keeps 98.2% of the base model's benchmark scores and reports 143 tokens per second on an RTX 5090 and 46.8 on an M5 Max. Its own table is more honest than the headline: vision drops from 81.6 to 78.6, and knowledge and reasoning slip too.

r/LocalLLM is doing exactly what it should, with a thread testing the 98% claim and calling for independent evaluation.

What to do: if you run models locally, grab it from the Bonsai 2 collection and test it on your own prompts. It needs PrismML's runtime, not stock llama.cpp.

Xiaomi opens MiMo-V2.6 under the MIT license

ModelConfirmed in r/LocalLLaMAView thread

Xiaomi published open weights for MiMo-V2.6 Pro and MiMo-V2.6 Flash on September 21. Both read text, images, video and audio, handle a one-million-token context and carry the permissive MIT license, which allows commercial use.

Pro is a mixture-of-experts model with about 1.02 trillion total parameters and 42 billion active. Flash is the practical one, with 309 billion total and 15 billion active.

The r/LocalLLaMA thread on Flash appeared within hours, with one commenter describing it as an official lab distill with state-of-the-art scores. Treat that as enthusiasm, not proof. Xiaomi's comparisons against frontier models are its own and have not been reproduced.

What to do: Pro is out of reach for most, needing roughly 16 GPUs across two nodes per RuntimeWire. Hosting reports conflict, so check OpenRouter before you plan around Flash.

Z.ai open-sources its ZCode agent after a privacy scare

RepoConfirmed in r/LocalLLaMAView thread

Z.ai put its whole ZCode coding-agent stack on GitHub under Apache-2.0: the desktop app, web interface, terminal CLI, backend and runtime. It gathered thousands of stars within a day.

The context matters. Days earlier, an r/LocalLLaMA thread alleged the closed client uploaded whole workspaces to the cloud, .git history included. RuntimeWire covers the release as a security response. Opening the client lets anyone audit what it sends, a long-standing request in the community.

Open code has limits, though. The repository has only two commits, its install script still points at a placeholder URL and there is no security policy file. Publishing the client also cannot show whether data already uploaded was deleted.

What to do: if you used ZCode, rotate any secrets that lived in those repositories. If you want a self-hostable agent, read the code before you run it.

Quick answers

Which new AI model can I try today without signing up for anything new?

Grok 4.7 is already inside GitHub Copilot and Cursor, so existing users can switch to it now (GitHub changelog).

Can I use Qwen-Image-2.1 for commercial work?

Not freely. It ships under the Qwen Research License Agreement rather than an open-source license, so check its terms first (Hugging Face).

What is the smallest capable model released this week?

Ternary Bonsai 2 27B fits in 5.9 GB and PrismML reports 143 tokens per second on an RTX 5090, though it needs PrismML's own runtime (PrismML).