Anthropic's New AI: Surprisingly Affordable to Train

Anthropic's latest AI model, Claude 3.7 Sonnet, was reportedly trained for just a few tens of millions of dollars, using less than 10^26 FLOPs of computing power. This info comes from Wharton professor Ethan Mollick, who shared on X that he got this straight from Anthropic's PR team. They told him, "I was contacted by Anthropic who told me that Sonnet 3.7 would not be considered a 10^26 FLOP model and cost a few tens of millions of dollars," though they hinted that future models would be way bigger.
TechCrunch tried to get the scoop from Anthropic but didn't hear back before their article went live.
If Claude 3.7 Sonnet really did cost just a few tens of millions to train, it's pretty wild to think how much cheaper it's getting to roll out top-notch AI models. Just to give you an idea, Claude 3.5, which came out in the fall of 2024, also cost a few tens of millions to train, according to Anthropic's CEO, Dario Amodei.
When you stack these numbers against what it cost to train the big dogs from 2023, it's even more impressive. OpenAI dropped over $100 million to get their GPT-4 model up and running, according to their CEO, Sam Altman. And Google? They spent close to $200 million on their Gemini Ultra model, if you believe a Stanford study.
But hold on, Amodei thinks the price tag for future AI models could hit the billions. And remember, training costs are just one piece of the puzzle. There's also safety testing, fundamental research, and all that jazz. Plus, as the AI world starts leaning into "reasoning" models that chew on problems for longer, the costs to keep these models running are probably gonna keep climbing.
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Comments (37)
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Wait, only tens of millions to train a top-tier model? That's a game-changer for accessibility. Makes you wonder how much the others are spending... and what the real cost of compute will be in a few years. 🤔
Anthropicのコスト効率すごい!数十億ドルかかると思ってたのに、たった数千万ドルでトレーニング済みなの?🤯 でも本当に倫理的にデータ使ってるのか気になる。他社も追従してAI開発費が下がったら、もっと面白いプロジェクトが増えるかもね。
Wow, Anthropic trained Claude 3.7 Sonnet for just tens of millions? That’s a steal in the AI world! Makes me wonder how they optimized to keep costs so low. Exciting for smaller startups, but big players must be sweating. 😅
Wow, training Claude 3.7 for just tens of millions? That’s a steal in AI land! Makes me wonder how they cut corners without losing quality. 🤔 Exciting for startups, though—cheaper AI could shake things up!

Anthropic launches Opus 4.8 featuring new dynamic workflow tool
Anthropic unveiled Opus 4.8 on Thursday, marking the latest iteration of its premier public model. Priced identically to its predecessor, this update is now accessible across all platforms.Releasing just 41 days after Opus 4.7, Anthropic has accelera
Anthropic debuts Claude Fable 5, a public version of Mythos
Anthropic is making its most powerful AI model available to the general public for the first time — but with safety measures in place.
On Tuesday, the company launched Claude Fable 5, the first public release of its Mythos model. According to Anthrop
SandboxAQ brings drug discovery AI to Claude, no computing PhD needed
Drug discovery remains one of the costliest challenges in modern industry. Identifying a single viable molecule can take a decade and billions of dollars, and most candidates still fail. A wave of AI startups has promised to change that — though most
Wait, only tens of millions to train a top-tier model? That's a game-changer for accessibility. Makes you wonder how much the others are spending... and what the real cost of compute will be in a few years. 🤔
Anthropicのコスト効率すごい!数十億ドルかかると思ってたのに、たった数千万ドルでトレーニング済みなの?🤯 でも本当に倫理的にデータ使ってるのか気になる。他社も追従してAI開発費が下がったら、もっと面白いプロジェクトが増えるかもね。
Wow, Anthropic trained Claude 3.7 Sonnet for just tens of millions? That’s a steal in the AI world! Makes me wonder how they optimized to keep costs so low. Exciting for smaller startups, but big players must be sweating. 😅
Wow, training Claude 3.7 for just tens of millions? That’s a steal in AI land! Makes me wonder how they cut corners without losing quality. 🤔 Exciting for startups, though—cheaper AI could shake things up!





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