DeepSeek API Pricing Update

Old DeepSeek Flash 0731 prices have been independently reproduced.[1] The issue is DeepSeek being inundated and not having capacity to serve the demand, hence the price increases to significantly dampen demand. Never mind international demand either--just think about the magnitude of Chinese domestic demand. Prices for anything related to AI or computing in general (mobile phones, cloud data centre hosting, etc) will continue to climb fast as demand for computer chips _far_ exceeds supply. DeepSeek doesn't have an option other than to just work away on improving their technology in the period of time before computer chips once again become a commodity. For example, DeepSeek's cache ratio for their models apparently leads to 1/2 GPU time requirement versus the second best provider.[2]

[1] https://nitter.net/thdxr/status/2085377844515922210#m

[2] https://nitter.net/thdxr/status/2087610161636471289#m

According to their post:

  (Input / Output / Cache Read, [$/M])
  DeepSeek-V4-Flash: 
    Prev: 0.14 / 0.28 / 0.0028 
    Off-Peak: 0.22 (1.6x) / 0.66 (2.4x) / 0.007 (2.5x)
    Peak: 0.44 (3.1x) / 1.32 (4.7x) / 0.014 (5.0x)

  DeepSeek-V4-Pro: 
    Prev: 0.435 / 0.87 / 0.003625
    Off-Peak: 0.66 (1.5x) / 1.98 (2.3x) / 0.022 (6.1x) 
    Peak: 1.32 (3.0x) / 3.96 (4.6x) / 0.044 (12.1x)

gpt-5.6-luna: $0.20 / $1.20 / $0.02 / $0.25 (In / Out / Cache Read / Cache Write)

EDIT: formatting

EDIT2: giving up on the formatting :-/

As well as the headline in/out changes, people heavily using agentic coding tools will want to note the 6x (off peak) and 12x (peak) increase to cache hit pricing on Pro (since cache hit can easily make up 90%+ of input on long sessions).

DeepSeek was hugely underpricing cache hit pricing before and even after this increase they're still cheaper on that metric than every other provider I'm aware of, but it will put an end to those "I used 1 billion tokens and spent $4" reports.

Opencode said they are working on matching the old prices using their own inference.

Right now, they give 4100 credits for Luna and 63 000 for Deepseek on their prepaid plan (both are 2x)

About 3x increase. Luna is now a much better deal. Hope they don't increase their prices in response.

It doesn't make any sense unless they are going to exit from inference market. They will be literally one of the costliest option (by output, for flash) if use openrouter as source.

Makes sense, basically increased price for peak hours when they don't have enough infra to serve everyone. Can expect the return of prices back.

Ah well. I spend about $5/month with Deepseek, so now I’ll have to find room in my budget for $15. Might have to tip my barista less or something.

This now places deepseek flash v4 from DeepSeek themselves at higher prices than openrouter (depending on caching). Will be interesting to see if third party prices remain the same.

the neat thing about the models being open-weights is there's a dozen other providers on OpenRouter still at the old price, or lower

It doesn't make any sense unless they are going to exit from inference market. They will be literally one of the costliest option (by output, for flash) if use openrouter as source.

Makes sense, basically increased price for peak hours when they don't have enough infra to serve everyone. Can expect the return of prices back.

Ah well. I spend about $5/month with Deepseek, so now I’ll have to find room in my budget for $15. Might have to tip my barista less or something.

According to their post:

  (Input / Output / Cache Read, [$/M])
  DeepSeek-V4-Flash: 
    Prev: 0.14 / 0.28 / 0.0028 
    Off-Peak: 0.22 (1.6x) / 0.66 (2.4x) / 0.007 (2.5x)
    Peak: 0.44 (3.1x) / 1.32 (4.7x) / 0.014 (5.0x)

  DeepSeek-V4-Pro: 
    Prev: 0.435 / 0.87 / 0.003625
    Off-Peak: 0.66 (1.5x) / 1.98 (2.3x) / 0.022 (6.1x) 
    Peak: 1.32 (3.0x) / 3.96 (4.6x) / 0.044 (12.1x)

gpt-5.6-luna: $0.20 / $1.20 / $0.02 / $0.25 (In / Out / Cache Read / Cache Write)

EDIT: formatting

EDIT2: giving up on the formatting :-/

Opencode said they are working on matching the old prices using their own inference.

Right now, they give 4100 credits for Luna and 63 000 for Deepseek on their prepaid plan (both are 2x)

About 3x increase. Luna is now a much better deal. Hope they don't increase their prices in response.

> EDIT: formatting

Keep at it, I believe in you.

The problem with DS Flash/Pro is that they are extreme reasoning heavy and step heavy. Step = cache hit. Reasoning = output hit. So the impact on those price increases will be felt much stronger.

I think that Flash is still a usable model but Pro is DOA... Even before the price difference between Flash and Pro, vs the intelligence / problem solving / tool calling did not make sense. But now that gap has widen even more. And there are just too many competitors models now close to that Pro price range.

Especially when we compare that competitive models offer subscription services that easily cut down the token price by 1:10. That makes Pro especially a bad value.

We shall see what the 3th party market is going to do, but i suspect that prices will be increased. If the argument was that DeepSeek increases price as they lack capacity, a company with access to billions, other 3th party providers that need to rent and have less optimized infrastructures will increase prices. Especially if they get hit hard with people moving around.

Its like we always see the same issue with popular models.

* GLM 5.2 is good, capacity issues, API price up, subscription heavy nerfs. * Kimi K3 is good, capacity issues, API price up, subscription heavy nerfs. * DeepSeek V4 GA is good, capacity issues, API price up * OpenAI GLM 5m, 10m active users. Subscription usage is sneakily tightened more and more. * Anthropic Opus too popular, ...

That is the main issue. The AI users are people who actively easily move between companies. Pushing peak loads to each unprepared company, releasing load on the "less desired". And round we go ...

I doubt they will match old cache read pricing- that’s most important in agentic coding.

Luna vs v4 Flash, sure.

But DeepSeek v4 Pro is a far more capable model and still cheaper than anything that it competes with, from what I can see.

Why not? They probably only offered those deals because of DeepSeek aggressive pricing. Now that DeepSeek is 3x more expensive it's time to revert those discounts.

This now places deepseek flash v4 from DeepSeek themselves at higher prices than openrouter (depending on caching). Will be interesting to see if third party prices remain the same.

the neat thing about the models being open-weights is there's a dozen other providers on OpenRouter still at the old price, or lower

It does seem to me that DeepSeek themselves aren't so much interested in being a service provider. They do it, and offer the service, but their pronouncements seem to be that they're more interested in being for now closer to a research lab with a longer term play for something more dramatic later.

Unfortunately in this case that's not true at all, there was no provider with genuinely close or the same effective prices (mostly based on cache hit cost) to old v4 flash or v4 pro. People have this misconception that other providers must be much cheaper than the official one in case of open weight models.

If you check on OpenRouter, some other providers serve V4 Flash at seemingly cheaper normal input/output tokens rates, but with a huge caveat: they have at least a 5x increase of the cache hit cost of the official API, some have a 10x+. No provider comes close to Deepseek's old low cache prices, and cache is 90%+ of what matters in agentic sessions.

Closest comparison:

- Deepseek: $0.14/$0.28 with $0.0028 cache hit cost for official API

- DeepInfra: $0.08/$0.18 (cheaper base rates!) with $0.016 cache hit (almost 6x!! Deepseek's current cache cost)

Another great example is Kimi K3, official API is $3/$15 and the cheapest provider on OpenRouter is $2.8/$14, only a tiny difference.

The question is if they'll increase prices as well.

The problem with DS Flash/Pro is that they are extreme reasoning heavy and step heavy. Step = cache hit. Reasoning = output hit. So the impact on those price increases will be felt much stronger.

Especially when we compare that competitive models offer subscription services that easily cut down the token price by 1:10. That makes Pro especially a bad value.

Its like we always see the same issue with popular models.

That is the main issue. The AI users are people who actively easily move between companies. Pushing peak loads to each unprepared company, releasing load on the "less desired". And round we go ...

> EDIT: formatting

Keep at it, I believe in you.

I doubt they will match old cache read pricing- that’s most important in agentic coding.

Luna vs v4 Flash, sure.

But DeepSeek v4 Pro is a far more capable model and still cheaper than anything that it competes with, from what I can see.

Why not? They probably only offered those deals because of DeepSeek aggressive pricing. Now that DeepSeek is 3x more expensive it's time to revert those discounts.

Closest comparison:

- Deepseek: $0.14/$0.28 with $0.0028 cache hit cost for official API

- DeepInfra: $0.08/$0.18 (cheaper base rates!) with $0.016 cache hit (almost 6x!! Deepseek's current cache cost)

Another great example is Kimi K3, official API is $3/$15 and the cheapest provider on OpenRouter is $2.8/$14, only a tiny difference.

The question is if they'll increase prices as well.

Tibo said it’s permanent, whatever that means

Probably means it's not intended as temporary, but not that the price will never change again

[1] https://nitter.net/thdxr/status/2085377844515922210#m

[2] https://nitter.net/thdxr/status/2087610161636471289#m

Reproduced on the CUDA stack right?

Let's say DeepSeek is being forced to use the CANN stack, and the new pricing reflects the cost when 100% of inference is done with Huawei chips. Then, I suppose we can infer that:

* CANN stack is 1.5x~2.3x less efficient in compute

* CANN stack has 6x lower inter-connect capacity

> computer chips once again become a commodity

Ascend 950 is going for $7k to $9k with mediocre looking specs. $16k for RTX Pro 6000, $6k for RTX Pro 5000. This is not looking good.

Reproduced on the CUDA stack right?

Let's say DeepSeek is being forced to use the CANN stack, and the new pricing reflects the cost when 100% of inference is done with Huawei chips. Then, I suppose we can infer that:

* CANN stack is 1.5x~2.3x less efficient in compute

* CANN stack has 6x lower inter-connect capacity

> computer chips once again become a commodity

Ascend 950 is going for $7k to $9k with mediocre looking specs. $16k for RTX Pro 6000, $6k for RTX Pro 5000. This is not looking good.

It would have to be reproduced on a CUDA stack because AFAIK Huawei don't sell the Ascend 950PR (for inference) to anyone, rather, they operate them as part of the Huawei Cloud and only allow select customers (such as DeepSeek) to rent them.

The CEO of DeepSeek recently revealed to investors a lot about the resources available to DeepSeek, and the gap between Huawei and NVIDIA. Select quotes from the transcript (translation is a bit patchy on the source website though):

"We currently have roughly 20,000 H-equivalent compute cards"

"Huawei 950—right now Huawei gives us 16,000 cards, this should be publicly stateable."

"Like Huawei gives us roughly 16,000 cards of capacity, internet giants maybe get a hundred-something thousand, we get ten-something thousand—I think this ratio is also relatively... but this is probably just how much capacity Huawei has."

"16,000 Huawei 950 cards only equal 4,000 B-series cards."

"Huawei’s supernode, Huawei’s 950 supernode, in performance and price can completely substitute for NVIDIA’s GB200, GB300. The price is definitely more expensive, but limitedly so. Fifty percent more expensive, a hundred percent more expensive—a hundred percent more doesn’t matter, two hundred percent more doesn’t matter. For example, a hundred percent more expensive—I think it can already be considered a price-level substitute."

"I think domestic hardware might need a few years."

"I don’t quite believe that five years from now, we’ll still be stuck on the production capacity problem. Right now we’re definitely stuck on the production capacity problem—this year, next year, the year after, I think we might still be stuck on the production capacity problem, but five years later, I think maybe not necessarily—I’m still relatively optimistic."

[1] https://www.fredgao.com/p/deepseeks-liang-wenfeng-breaks-his