231–240 of 392 posts
So this is why Anthropic rushed the weirdest "pre-responsible-disclosure-totally-not-for-marketing" announcement yesterday? To make sure Spark doesn't steal their thunder? (Spark beats Opus 4.6 on some benchmarks...). Or did I become a bitter cynical old man.
If spark beats opus 4.6, why is meta wasting money on opus internally?
Personal Superintelligence made me think this was an open-source model being released and I was excited. Then I continued reading and I'll just wait until the model comes out.
I'm cautiously waiting for the feedback from the first users. Meta has produced a lot of great models (LLama), maybe this is a comeback... but I'm cautious, as the jump in the quality is almost too high. Also, I think people aren't used that using such models requires meta.ai or meta ai app.
Meta hasn’t fully caught up, but they came close and I think can solidly claim to be a frontier lab again. I’d call it a 3.5 horse race right now, and hopefully their next model improves. More model competition is good!
Poor Grok 4.2 should probably be dropped from the table.
This really reinforces the idea that the AI race and the Railroad Mania of the 19th century are very similar. So many different companies are going to have similarly powerful ai that there will be no moat around it and it will be cheap. They will never earn their investment back.
I doubt its better than Opus and even if it was its not worth the privacy concerns.
"Muse Spark is available now, and Contemplating mode will be rolling out gradually in meta.ai." How does one get their hands on these models? They are not open-source, right? I go to meta.ai, but it's just a chat interface---no equivalent to codex or claud code? Can you use this through OpenCode? Is meta charging for model access, or is the gathering of chat data a sufficiently large tithe?
Ran some of my internal benchmarks against this and I'm very unimpressed. I don't think this moves them into the OAI v Anthropic v Gemini conversation at all. Major analytical errors in their response to multiple of my technical questions.
Playing with this some more and it's actively not good. Just basic mathematical errors riddling responses. Did some basic adversarial testing where its responses are analyzed by Gemini and Gemini is finding basic math errors across every relatively (relative to Opus, Gemini or GPT can handle) simple ask I make. Yikes.
Otherwise you're doomed to "sample size of one" level of relevance.