i forced myself to use a few non-mainstream models today. sharing my experience with everyone in case you're wondering 1. muse spark 1.3 i was genuinely surprised by how good this model is. if you silently swapped opus 4.8 with this without telling me, it'll probably take me quite a while to figure it out, and it would likely be from the communication style rather than capability at its contributor pricing, the ROI is quite incredible. i find very little motivation to even try deepseek v4 flash when this exists i don't like the phrase they keep using though - "intelligence that's too cheap to meter". if i do all my work with this model, even at its extremely good pricing, it'll still cost me thousands of dollars a month - that's not "too cheap to meter" reduce the cost by another 100x then let's talk about "too cheap" 2. glm 5.3 flash i thought it'd be better than muse spark 1.3, but actually immediately after i switched to this as my firstmate, it made quite a few mistakes it could be a bit anecdotal but now it lost trust with me and i'm a bit nervous about letting it manage my work. i'm going to let it do some more straightforward implementation rather than acting as my primary model 3. gemini 3.8 flash maybe it's because i never spent much time with gemini before, but this model is SO GOOD at communicating. it's such a breath of fresh air. i can understand every word without using much brain power at all but this is significantly more expensive than the two above. i think i'd have to get a google ai subscription if i want to use this more, but not being able to use it in 3rd party harnesses gives me a pause it's also powerful enough as an opus replacement for most things i tried. my general sense after trying these models is - everyone has an opus now, and they are all cheaper than the real opus fable and astra is probably the only moat the labs have now - the game has fundamentally shifted from what it was 6 months ago

Meta's Muse Image debuts at #4# on the Artificial Analysis Image Editing Leaderboard and takes #5# in Text to Image, including a position on the Pareto frontier for quality vs price Muse Image is the first image model from Meta Superintelligence Labs, launched in Meta AI in July and now available to developers on the Meta Model API. Meta positions it as an agentic image model: it invokes search and coding tools, self-refines its own generations, and composes from multiple references. In the Artificial Analysis Image Arena, Muse Image debuts at #4# in Image Editing, behind Microsoft's MAI-Image-2.6-Preview and OpenAI's GPT Image 2 (high) and narrowly behind Google's Nano Banana 2. In Text to Image it takes #5#, behind only GPT Image 2 (high), MAI-Image-2.6-Preview, Reve 2.1, and Google's Nano Banana 2. Muse Image is available in the Meta AI app, on in Instagram Stories, in WhatsApp in limited countries, and to developers via the Meta Model API and partner platforms fal, Runway, and OpenRouter. Congratulations to @AIatMeta, @alexandr_wang, & @finkd on the release! See below for our analysis and example outputs of Muse Image in the Artificial Analysis Image Arena 🧵