Reviewed and written up.
New
Added Oct 13, 2026
Muse Wonder is Meta Superintelligence Labs' October 12, 2026 model, a larger class than the Muse Spark line, released alongside a more capable Muse Wonder Full. Wonder is sold through the Meta Model API as muse-wonder-1.0 at $4 per million input tokens and $20 output ($0.20 cached input), with a one million token context window, and works with existing OpenAI SDK code by changing the base URL. It takes screenshots, charts, documents, images and video as input. Wonder Full is not on the API: it comes only with Muse Code's Power Usage and Maximum Usage plans. Both models will power Meta's Muse agent.
Why: It is Meta back at the frontier. At launch, VentureBeat reported, Artificial Analysis put Wonder a point behind GPT-6 Astra and Gemini 4 Argon on its Intelligence Index, and Wonder Full level with Claude Sonnet 5.5, behind only Claude Opus 5.5. Meta's own coding results are stronger still, and the API price matches Opus 5.5 per token.
New
Added Oct 14, 2026
Nano Banana 2.1 is Google's October 6, 2026 update to Nano Banana 2 (Gemini 3.1 Flash Image), built on Gemini 3.6 Flash. It generates and edits images from text and reference images, at 1K, 2K and 4K, with multi-turn character consistency and optional grounding in Google Search. On the Gemini API it is gemini-nano-banana-2.1 at $30 per million image output tokens, which Google prices at about $0.034 per 1K image, $0.050 per 2K and $0.113 per 4K. It also runs in the Gemini app, Google AI Studio, AI Mode in Search, Flow and Stitch.
Why: It is a better model for less money. On the independent Artificial Analysis text-to-image arena it scores well above Nano Banana 2 and level with Grok Imagine Image 2.0 and MAI-Image-2.6, and Google's price per 1K image is about half Nano Banana 2's. Google lists it as the replacement for Nano Banana 2.
New
Added Oct 14, 2026
Qwen-Image-2.1-Turbo is an accelerated checkpoint of Alibaba Qwen's Qwen-Image-2.1, released on October 9, 2026. It uses the same 7B architecture but generates in 8 denoising steps, and handles both text-to-image and image editing from a reference, up to 2752 x 1536 at 16:9 and 2048 x 2048 square. The weights are on Hugging Face and ModelScope and load in Diffusers.
Why: It is one of the few strong image models you can download and run yourself, and the 8-step schedule makes it fast enough to iterate with locally. The licence is the catch: it is research and evaluation only, so it suits experiments and in-house prototypes rather than a product.