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DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

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161–170 of 214 posts

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#161
post #15

Since a few months, I almost exclusively use the Chinese "flash" models for my needs. They are a joy and they cost pennies per answer. Great job.

Yeah, the latest batch of <256GB Chinese models are really nice. They're far less cryptic than Claude, and competent enough to feel almost near Opus. I canceled all my subscriptions and switched to running the Chinese models locally (not as a cost saving measure).

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#162
post #103
post #67

>In keeping with our commitment to user responsibility, following the official launch of V4.1 Flash and prior to the release of V4.1 Pro, all requests to the Pro model will be routed to V4.1 Flash and billed at Flash's price Please don't do this kind of thing. If a user has validated a workflow on V4 Pro, they might not want to suddenly start testing it in production on V4.1 Flash. Instead, keep V4 Pro around but dep…

Usually I would very much agree with you, but those things are not deterministic so if that's an issue for you you're probably not making the right choices.

Crossing the street and Russian roulette both have non-deterministic risks of injury. And yet I would be bothered to find out that that on my way to work, I was playing Russian roulette by surprise.

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#164
post #153
post #103

Earlier quoted context omitted.

Usually I would very much agree with you, but those things are not deterministic so if that's an issue for you you're probably not making the right choices.

That's a narrow take. Non-deterministic doesn't mean random; workflows can be reasonably validated and consistent to some known degree. I work for an education department that serves a chatbot for students, and model changes go through painstaking content safety reviews. I initially assumed it's just a bunch of bureaucratic paranoia. But every other model upgrade has a measurably different adherence to the existing s…

I work in the same field for one of my company, in europe, and if you're not self hosting sorry but your worries are not something I can accept because models are very much not reliable on that front, let alone when you let the host decide HOW to serve a model (ressources allocated, different version of the same model, etc ...).

I'm not being a d**, just saying, the problem you have is something that I have faced EXACTLY, and at least here it's not working until you host in house or remote but on raw hardware. Otherwise it keeps having subtle changes, and you will notice no LLM API providers has guarantees about these.

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#165
post #103

Earlier quoted context omitted.

Usually I would very much agree with you, but those things are not deterministic so if that's an issue for you you're probably not making the right choices.

Crossing the street and Russian roulette both have non-deterministic risks of injury. And yet I would be bothered to find out that that on my way to work, I was playing Russian roulette by surprise.

Yes and if you decide to play not using a game rulebook but a website that call it "game A" you can't be shocked if "game A" switched from one to the other, even though the doc said opposite yesterday.

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#166
post #49

> all requests to the Pro model will be routed to V4.1 Flash and billed at Flash's price If I'd carefully tested and optimized prompts against Pro I wouldn't be keen on this particular news. I feel like API model providers should lean towards not swapping out models on their paying customers, no matter how much "better" the new model is meant to be.

I imagine they're doing this due to capacity issues or somesuch. They can always relaunch Pro later, meanwhile a little ricered benchmaxxing of their existing flash model provides a temporary cover story. They certainly aren't silly enough to think this won't impact existing Pro users

They could raise prices, if capacity is problem

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#167
post #132

Earlier quoted context omitted.

I am legitimately more excited for this release than any frontier models at this point. I don't need a model that can invent new mathematics. I need something that is fast, cheap, and consistent. Give me that and I can build and scale.

LLMs are not consistent

True, make them cheap and fast enough and you can scope and stack agents sufficiently that the error rate tends close enough to zero to be meaningfully useful.

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#168
post #67

>In keeping with our commitment to user responsibility, following the official launch of V4.1 Flash and prior to the release of V4.1 Pro, all requests to the Pro model will be routed to V4.1 Flash and billed at Flash's price Please don't do this kind of thing. If a user has validated a workflow on V4 Pro, they might not want to suddenly start testing it in production on V4.1 Flash. Instead, keep V4 Pro around but dep…

In this case, Deepseek organization is under a lot of pressure due to compute constraints. It would be better if they just throw a 404 instead of rerouting though so customers are not surprised by subtle changes in behavior.

Yes exactly. Automatic model downgrade seems horrible for a lot of production workloads, even if you are deterministically constraining the behavior of your agents.

Re: DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

#170
post #67

>In keeping with our commitment to user responsibility, following the official launch of V4.1 Flash and prior to the release of V4.1 Pro, all requests to the Pro model will be routed to V4.1 Flash and billed at Flash's price Please don't do this kind of thing. If a user has validated a workflow on V4 Pro, they might not want to suddenly start testing it in production on V4.1 Flash. Instead, keep V4 Pro around but dep…

I think keeping models around for a defined period of time is fine, but fracturing your model offerings like that (keeping around multiple versions of the same model) is very hard to do economically. The economics of the AI ecosystem are dominated by queueing theory constraints that make it extremely cheap to serve predictable traffic loads, and extremely expensive to serve unpredictable loads, and any time you split your offerings like that, you make both less predictable and therefore more expensive to serve both versions.

If I were paying anthropic prices, I'd expect it, but Deepseek is a super scrappy upstart in comparison and intentionally arbitraging on price. I would never expect them to do that.

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