71–80 of 265 posts
Here's the Muse Spark 1.2 pelican: https://tools.simonwillison.net/markdown-svg-renderer#url=ht... I think it's a bit of an improvement on the Spark 1.1 pelican: https://simonwillison.net/2026/Jul/9/muse-spark-1-1/
Will someone at Meta for the love of God make it so none of this stuff goes through Facebook.com? You want customers but most corporate firewalls block social media. Also, a lot of devs do not want their work stuff tied up to their facebook account. For the love of all things show the IG / FB logins as optional and do email as primary. I am not a fan of Meta but I do cheer for any competitors against OpenAI and Anthr…
China says hi.
Meta is offering a 10x discount on input ($0.10 vs. $1.25/Mtok) and 20x discount on output ($0.20 vs. $4.25/Mtok) if you opt in to let them train on your data. https://developer.meta.com/ai/models/muse-spark/
Meta is offering a 10x discount on input ($0.10 vs. $1.25/Mtok) and 20x discount on output ($0.20 vs. $4.25/Mtok) if you opt in to let them train on your data. https://developer.meta.com/ai/models/muse-spark/
Meta is offering a 10x discount on input ($0.10 vs. $1.25/Mtok) and 20x discount on output ($0.20 vs. $4.25/Mtok) if you opt in to let them train on your data. https://developer.meta.com/ai/models/muse-spark/
Probably to compete with DeepSeek, which AFAIK also retains data (or at least OpenRouter says they do)
Earlier quoted context omitted.
Probably to compete with DeepSeek, which AFAIK also retains data (or at least OpenRouter says they do)
DeepSeek is really crazy cheap, though, and they don't have a giant pool of other invasive personal data to correlate it with.
Meta is offering a 10x discount on input ($0.10 vs. $1.25/Mtok) and 20x discount on output ($0.20 vs. $4.25/Mtok) if you opt in to let them train on your data. https://developer.meta.com/ai/models/muse-spark/
Why does every AI lab feel the need to build their own coding agent…? Don’t we have more than enough already?
It is easy to benchmark across one harness, one system prompt and extract the most performance when you control the harness.
They chose to compare against Open AI’s mid tier model Terra instead of Sol and still lost some benchmark against it. They left Opus in and got beat in all but one benchmark. Nothing wrong with trying to improve, but why the marketing games? Instead of trying to say in the post you’re “closer” to frontier, first set a clear goal to beat the Chinese labs on price or performance and demonstrate it convincingly. Then wh…
It's definitely confusing from a presentation perspective, but they are somewhat coherent comparisons if you account for the inference heuristics involved.
(They could in theory be gaming the decode speeds with much larger than normal batch sizes given the TTFT is pretty high at around 8s)