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>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 Pr

by aftbit 7d ago

>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 deprecated for a defined period of time, then remove it. At least as open weights models, it's possible to use something like Together.ai or OpenRouter to run the V4 Pro model as long as other providers keep it up.

weego 7d ago
You absolutely cannot consider an LLM production build number something to be pinned against as a static dependency in a product chain, so it's a non-issue.
- weird-eye-issue 7d ago
  It's very easy to tell who is not running production applications using these models based on comments like this
  - Xunjin 7d ago
    Let me give you the benefit of the doubt, can you expand what you run in production?
    - vikramkr 7d ago
      In the openai api and many other rapid you can pretty trivially pin not only the model but also the specific snapshot you want to use by using the model id for that snapshot. It's not that big a deal and has been available for years
    - weird-eye-issue 7d ago
      I'm the founder of a SaaS in the marketing industry with tens of thousands of paying users and we have lots of AI powered workflows where small changes between model versions can make some big differences so whenever we update models we have to thoroughly test them which is why we pin them at specific versions which has been a best practice (and common sense) for the last 3+ years
- samuelknight 7d ago
  Yes you can and you should. Providers have SLAs for when models roll off support and this has been the case for APIs long before LLMs. For example https://platform.claude.com/docs/en/about-claude/model-deprecations#model-status https://platform.claude.com/docs/en/about-claude/model-depre... and https://developers.openai.com/api/docs/deprecations https://developers.openai.com/api/docs/deprecations
darksaints 7d ago
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.
monster_truck 7d ago
I'm not sure that anyone is running production workloads against an API that bills twice as much for a chunk of the day. One of the best things about Deepseek is that you can host it yourself and get a ridiculous multiple of usage for what the same dollar amount would yield from their API
- happycube 7d ago
  It'd be very expensive to get a setup that can run non-flash well. If they were still at original price I'd get a couple of DGX Sparks myself to run Flash models at a decent quant/context combo.
- Sha1rholder 7d ago
  > I'm not sure that anyone is running production workloads against an API that bills twice as much for a chunk of the day. I'm not sure that anyone will mind running production workloads against an API that bills half as much for a chunk of the day.
teamv02 7d ago
I don't really agree, but we shouldn't have to debate it. An Auto option at each level would preclude this kind of decisioning. Pick a discrete model, that's what you get. Pick Auto (Deepseek v4 Flash Auto vs Deepseek v4.x Flash), and let the vendor decide. I think OpenRouter uses this method.
m3kw9 7d ago
They expect vibe coders to use their models only lol
KoolKat23 7d ago
I imagine they need the compute. Can expand market share with more users for same amount of compute. But I agree with you. I have a dumb workflow that worked well with v4-flash-0731 and I suspect is directing to a newer model that now breaks it.
- petu 7d ago
  4.1 releases tomorrow, right now you're supposed to be served by same old model
nolok 7d ago
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.
- hyperpape 7d ago
  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.
  - nolok 7d ago
    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.
    - hyperpape 7d ago
      That would absolutely be a dick move on the part of the website and would confuse users. Also, in this case, the game name is not “Game A” but something like “Deep Seek v4 Pro”, which they have previously chosen to use to describe Deep Seek v4 Pro, not Deep Seek v4.1 Flash.
    - genxy 7d ago
      You should look at why you are protecting your earlier comment rather than changing your mind or understanding why so many people disagree with you.
- gpugreg 7d ago
  > those things are not deterministic Determinism was an explicit goal of DeepSeek-V4. From their paper: https://arxiv.org/html/2606.19348v1#S3.SS3 https://arxiv.org/html/2606.19348v1#S3.SS3 > we implement end-to-end, bitwise batch-invariant, and deterministic kernels with minimal performance overhead Of course, providers may not implement deterministic inference for various reasons, but it is possible.
samuelknight 7d ago
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.
- DetroitThrow 7d ago
  Yes exactly. Automatic model downgrade seems horrible for a lot of production workloads, even if you are deterministically constraining the behavior of your agents.
jmathai 7d ago
LLMs add enough nondeterminism to a workflow. Swapping them without the user knowing adds substantially more.
- cyanydeez 7d ago
  relying on cloud models for anything that gives you ROI is tying a loose noose.
  - jmathai 7d ago
    This is true :P.
ycui7 7d ago
llm is not a deterministic program. the same model won't even return deterministic answer. what's the point keep the model freezed? if you want deterministic returns, you should set the temperature to 0 to get the best possibility of deterministic.
- IanCal 6d ago
  Because we care about the distribution of the outputs and how that impacts a specific use case.
- zamadatix 7d ago
  Strict determinism is a different, but related, issue. E.g. if I've written a role playing character using a specific model I may want to pin the character to that model until I've been able to test the model being "better" doesn't affect the feel of the character before switching. That doesn't mean I need the character's responses to be completely deterministic, but that doesn't imply I'm fine with the character having a different quality or feel of response just because the new model is out. It'd be nice if there was a more explicit way to signal in the request "I want what you think is best per dollar for this class of answer" vs "I want this model to answer".
g023 7d ago
its probably more expensive to run, and I'm thinking 4.1 flash is a smaller more efficient model. You can always host your own. This is what they need to do to stay competitive.
bicx 7d ago
I wonder if this is a sign of things to come for dirt-cheap model hosting: no servers running old versions, only new versions. Just to keep costs down.

by aftbit 7d ago

weego 7d ago

You absolutely cannot consider an LLM production build number something to be pinned against as a static dependency in a product chain, so it's a non-issue.

weird-eye-issue 7d ago
It's very easy to tell who is not running production applications using these models based on comments like this
- Xunjin 7d ago
  Let me give you the benefit of the doubt, can you expand what you run in production?
  - vikramkr 7d ago
    In the openai api and many other rapid you can pretty trivially pin not only the model but also the specific snapshot you want to use by using the model id for that snapshot. It's not that big a deal and has been available for years
  - weird-eye-issue 7d ago
    I'm the founder of a SaaS in the marketing industry with tens of thousands of paying users and we have lots of AI powered workflows where small changes between model versions can make some big differences so whenever we update models we have to thoroughly test them which is why we pin them at specific versions which has been a best practice (and common sense) for the last 3+ years
samuelknight 7d ago
Yes you can and you should. Providers have SLAs for when models roll off support and this has been the case for APIs long before LLMs. For example https://platform.claude.com/docs/en/about-claude/model-deprecations#model-status https://platform.claude.com/docs/en/about-claude/model-depre... and https://developers.openai.com/api/docs/deprecations https://developers.openai.com/api/docs/deprecations

darksaints 7d ago

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.

monster_truck 7d ago

I'm not sure that anyone is running production workloads against an API that bills twice as much for a chunk of the day. One of the best things about Deepseek is that you can host it yourself and get a ridiculous multiple of usage for what the same dollar amount would yield from their API

happycube 7d ago
It'd be very expensive to get a setup that can run non-flash well. If they were still at original price I'd get a couple of DGX Sparks myself to run Flash models at a decent quant/context combo.
Sha1rholder 7d ago
> I'm not sure that anyone is running production workloads against an API that bills twice as much for a chunk of the day. I'm not sure that anyone will mind running production workloads against an API that bills half as much for a chunk of the day.

teamv02 7d ago

I don't really agree, but we shouldn't have to debate it. An Auto option at each level would preclude this kind of decisioning. Pick a discrete model, that's what you get. Pick Auto (Deepseek v4 Flash Auto vs Deepseek v4.x Flash), and let the vendor decide. I think OpenRouter uses this method.

m3kw9 7d ago

They expect vibe coders to use their models only lol

KoolKat23 7d ago

I imagine they need the compute. Can expand market share with more users for same amount of compute. But I agree with you. I have a dumb workflow that worked well with v4-flash-0731 and I suspect is directing to a newer model that now breaks it.

petu 7d ago
4.1 releases tomorrow, right now you're supposed to be served by same old model

nolok 7d ago

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.

hyperpape 7d ago
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.
- nolok 7d ago
  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.
  - hyperpape 7d ago
    That would absolutely be a dick move on the part of the website and would confuse users. Also, in this case, the game name is not “Game A” but something like “Deep Seek v4 Pro”, which they have previously chosen to use to describe Deep Seek v4 Pro, not Deep Seek v4.1 Flash.
  - genxy 7d ago
    You should look at why you are protecting your earlier comment rather than changing your mind or understanding why so many people disagree with you.
gpugreg 7d ago
> those things are not deterministic Determinism was an explicit goal of DeepSeek-V4. From their paper: https://arxiv.org/html/2606.19348v1#S3.SS3 https://arxiv.org/html/2606.19348v1#S3.SS3 > we implement end-to-end, bitwise batch-invariant, and deterministic kernels with minimal performance overhead Of course, providers may not implement deterministic inference for various reasons, but it is possible.

samuelknight 7d ago

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.

DetroitThrow 7d ago
Yes exactly. Automatic model downgrade seems horrible for a lot of production workloads, even if you are deterministically constraining the behavior of your agents.

jmathai 7d ago

LLMs add enough nondeterminism to a workflow. Swapping them without the user knowing adds substantially more.

cyanydeez 7d ago
relying on cloud models for anything that gives you ROI is tying a loose noose.
- jmathai 7d ago
  This is true :P.

ycui7 7d ago

llm is not a deterministic program. the same model won't even return deterministic answer. what's the point keep the model freezed? if you want deterministic returns, you should set the temperature to 0 to get the best possibility of deterministic.

IanCal 6d ago
Because we care about the distribution of the outputs and how that impacts a specific use case.
zamadatix 7d ago
Strict determinism is a different, but related, issue. E.g. if I've written a role playing character using a specific model I may want to pin the character to that model until I've been able to test the model being "better" doesn't affect the feel of the character before switching. That doesn't mean I need the character's responses to be completely deterministic, but that doesn't imply I'm fine with the character having a different quality or feel of response just because the new model is out. It'd be nice if there was a more explicit way to signal in the request "I want what you think is best per dollar for this class of answer" vs "I want this model to answer".

g023 7d ago

its probably more expensive to run, and I'm thinking 4.1 flash is a smaller more efficient model. You can always host your own. This is what they need to do to stay competitive.

bicx 7d ago

I wonder if this is a sign of things to come for dirt-cheap model hosting: no servers running old versions, only new versions. Just to keep costs down.