1vuio0pswjnm7OpenAI's fall from grace as investors race to Anthropic
> The large gap between OpenAI’s $852-billion valuation and Anthropic’s $380 billion has investors rushing to grab equity in the latter before it rises, according to Augment co-founder Adam Crawley.
Interesting, so there are a lot of people still eager to invest in valuations of well greater than a-quarter-trillion, but OpenAI's latest raise has sucked up all the oxygen for enthusiasm of that valuation going even higher.
Which could be a "dumb money" move ("competitor number lower, already-big-number is scary") or a "smart money" move ("Anthropic is gaining position-wise, and currently is lower valued, let's bet on the one we think is better positioned") or some mix of both.
OpenAI just raised a shit-ton so clearly there is plenty of money out there who don't think there's a bubble or even a blown opportunity there. But the wider community doesn't think they have the competition in the bag, while still being willing to invest in big-AI-cos at absolutely enormous valuations.
If local hardware/models get good enough to take 80%-90% of what people use subscriptions for today... hoo boy. Big-AI is a bet I wouldn't be confident placing billions on. Unless your horizon is more "wait for IPO or next raise or positive news, then get out ASAP" than "hold for 5+ years."
Vibe coding requires the sota models to work at all, but someone who knows what they are doing and uses the AI more responsibly can absolutely use the cheaper Chinese models for coding, and they’re often faster too. If I was one of the big players my entire focus would be on lobbying for regulation and outright banning of local models.
Yeah, Qwen3 coder for Claude Code and 3.5 for OpenClaw replaced my full-stack use of Opus 4.6 already; it's fine for basic web apps, k8s/docker infra setup, optimizing AI models etc. with only slightly higher error rate than Opus. Upcoming 3.6 together with Gemma4 might make it even better (still to test). OpenAI's memory spot market play might have been directed at local inference as well.
Look for Deepseek 4 when it drops, I’m curious how good it will be.
The thing is, if you’re using AI responsibly today you’re already breaking down tasks to such a granular level that you don’t need the power of Opus. You can save that for deeper research tasks.
Based on the current DeepSeek website I suspect it's not going to be great as their current model (V3.4? V4-mini?) often forgets or changes facts explicitly mentioned in the conversation which R1 never did. It's better than R1 at math or coding, but nearly unusable for deep conversation. I suspect they pushed MLA or linear attention too much, or quantize a lot more than before.