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LaurensBER 3 hours ago [-]
I've been using it extensively since the release and the best summary I can give is that it's good enough to use it for (almost) everything and cheap enough that the cost are irrelevant. I'm running it in Oh My Pi with a second instance running as "advisor" and even with 5-6 active sessions (effectively 12 streams) I'm struggling to spend more than 5 bucks per day.
OpenCode Go even has double limits temporarily so for 10 USD you effectively get 140 USD of tokens to spend. It would impress me if someone could burn that amount with "normal" usage. Even when running multiple sessions.
I have a Claude Max subscription but I've barely touched it, it just feels like a step back to have to think about limits and usage even though the models are stronger.
The beauty of intelligence at this cost (even if it's not SOTA) is that it opens a whole bunch of new use cases. Test failure in CI? Have the bot automatically propose a fix, its cheap enough that you can discard it w/h issues. Test coverage too low? Auto generate tests on CI for every pull-requests! Monitoring server logs, continuous security audits and investigating every received exception now becomes possible.
I'm thinking about having it automatically filter and re-rank my social media feeds so I can steer the algorithm instead of the other way around.
Perhaps other people (with enormous budgets) were already doing all of the above but for us this is a really exciting release!
abixb 51 seconds ago [-]
If what you're saying is true and accurate, then US-based AI labs are in big trouble. The only saving grace might be some sort of a 'national security' proclamation banning the use of state-of-the-art Chinese (and non-US) models across US government and enterprises, but even still, US AI labs will probably lose out massively on international market if a smaller model can match SOTA of just a few months ago.
paxys 52 minutes ago [-]
How is $5/day irrelevant? In the $150/mo range you can get effectively unlimited usage of GPT 5.6 Sol (Pro plan). Why use a much weaker model for the same price?
brynnbee 7 minutes ago [-]
Others have said similar but I disagree, I'm spending $200/m and I can easily burn through my weekly quota with a few overnight goals using 5.6 medium.
rain_iwakura 48 minutes ago [-]
not at all true. if you're truly using it across the board for smaller things (translation of pages, filtering of every individual tweet based on its relevance to you etc), the costs ramp up super quickly.
i used for work where i did less and it quickly reaches thousands if you're not careful. i can already see what some will say: skill issue et cetera - whatever.
whimblepop 38 minutes ago [-]
I thought it went without saying that GPT 5.6 Sol is the wrong model to use for things like filtering tweets. Apparently not?
paxys 13 minutes ago [-]
$100-200/mo is the subscription price. You aren’t going to go over. And you can select smaller models as well. Not everything has to be done by the most expensive one.
ux266478 26 minutes ago [-]
> In the $150/mo range you can get effectively unlimited usage of GPT 5.6 Sol
With 5 active sessions going nonstop? That seems like a pretty important qualifier.
jmathai 26 minutes ago [-]
The cost per token is super low. If you're used to paying OpenAI or Anthropic API-based fees then the same workload on DeepSeek feels free.
_aavaa_ 30 minutes ago [-]
I really doubt that the either of the pro plans are subsidized heavily enough to support you swapping v4Flash for Terra, much less Sol.
$5/days is ~330 Mtok/day, that’s a nontrivial amount of work, and none of the gpts are more efficient than deepseek at $/task if deepseek meets your quality bar.
re-thc 28 minutes ago [-]
> In the $150/mo range you can get effectively unlimited usage of GPT 5.6 Sol (Pro plan)
Not true. Sol on XHigh or Max runs out even on the $200/mo plan. It's not close to effectively unlimited. Maybe at 2x the current allowance it can.
ljosifov 13 minutes ago [-]
Hear hear. IQ tokens to cheap to meter upon us. So many things changed since last week. Now I've had Prime agent session grinding into its 20-th hour still not giving up. Been using opencode-go since Go sub appeared. What made a difference was deepseek-v4-flash and mimo-v2.5 showing. Very similar middling models ~300b so light on the gpu. 1M context and hybrid archs - so one can actually make use of that 1M (don't grind to a halt like others). In OMP I have one the primary (default), the other one as /advisor looking over the shoulder and nagging. On opencode-go in credits counting they are the bottom-2 in cost, cheaper by 200-350 times than than the top-1. Last week with deepseek-v4-flash-0731 another jump - now it's closer to the top models then to the middle. Now I don't even need the /advisor probably. Still left it there it's sometime amusing the models back and forth. :-) DeepSeek offer /v1/responses api now with flash-0731, so setup Codex to use that too. I'm loving this :-)
amelius 1 hours ago [-]
> it's good enough to use it for (almost) everything
which in your case is?
rpdillon 55 minutes ago [-]
I've posted a few times about my project that's a collection of 30k-250k webapps that are served from a WebDAV server. The apps know how to write updated copies of themselves back to the server.
My family uses it. I have gallery apps (yearbooks for each year are a lot of fun!) of us on trips and just living, an outlining app that's a mesh of Workflowy and Org Mode (it's called Fluxtral), a markdown-backed app (it uses marked.min.js, and is called Dextral) that offers documents, logs, calendars, and kanban boards, all parsed from markdown. I have a List app for gear, trips, shopping, etc. that we all can contribute to. There are utilities (world clock, calendar) and games (an oracle for RPGs, a KenKen implementation), and apps (a diagram editor that exports to SVG, a web-launcher that uses pneumonics, a Scheme-based hacking environment, and a spreadsheet that does most of what you'd expect aside from Solver and Pivot tables).
I started these projects before AI, and made slow progress over the years, but the modern versions of all this stuff have been built with Deepseek V4 Flash. I've also used Gemini in the very early days, and Kimi K2.6 later on, but these days, since I can now host Deepseek v4 Flash 0731 in a 2-bit quant on my Strix Halo box (128GB, but only about 250GB/s of memory bandwidth, so 15t/s), I used Deepseek with omp for almost everything. It's a very capable model, and I'm amazed I can run it locally and get good results. It's really revolutionary for my (small) use cases.
throwaway27448 54 minutes ago [-]
[flagged]
dan_q 1 hours ago [-]
> which in your case is?
oh, they're mad.
Aeolun 3 hours ago [-]
But DeepSeek now has a warning they’re going to sharply increase their API pricing sometime in the future.
LaurensBER 2 hours ago [-]
Dax (from Opencode) has tweeted that they can replicate or beat the price with rented GPUs. Deepseeks secret sauce is the incredibly cheap caching (magnitude cheaper than other providers).
vLLM has recently released a similar approach. It's not as effective as what DeepSeek does but still an interesting development.
I have no doubt that in due time other providers will match or perhaps even beat the current DeepSeek prices.
minraws 2 hours ago [-]
As someone who recently tried it on some blackwell cards, it's possible to match the prices especially the input can be even cheaper and output can match the costs so you can easily build a net 20-30% margin business even at current GPU prices.
The entire issue is caching, I tried to write some custom to dump to disk kv-caching using some ideas from their papers and my experience with snapshots and vm checkpoint systems, I must say they must have really squeezed that lemon it's hard.
Atleast me with Sol couldn't figure it out over a couple days, a few hours each day, which isn't much but I did feel a bit stuck with existing solutions and felt like I might have to write something from scratch. But if you are willing to put in the effort into the infra I do think it's doable. But it will be really hard to pull it off.
My congrats to anyone who manages to pull it off, they might be able to kill off most AI labs. Assuming they can find the compute, Deepseek really has killed all models for me other than Sol/Fable/Opus/K3 tier stuff.
twotwotwo 2 hours ago [-]
One read is 1) they're getting a lot of traffic for Flash, 2) they've said they're updating Pro soon and expect that to lead to a traffic spike for Pro, but 3) that would leave them overloaded, so 4) they're going to raise prices to avoid it.
It's interesting that most open models adding 1M context did it in a way that reduces KV cache size (though DeepSeek was the most aggressive, using compressed attention on all layers), but only a couple providers turned it into a discount on cache reads.
re-thc 26 minutes ago [-]
> they can replicate or beat the price with rented GPUs
They "can" is the caveat here. Rented GPUs are going up in pricing. I recently got an email that DigitalOcean pricing of GPUs were going up.
So
1. They have to get a hold of them (availability is bad)
2. They have to maintain the pricing
NorwegianDude 2 hours ago [-]
Eh, what are you guys even talking about? Deepseek is not cheapest provider as is, and it's MIT. So deepseek making it more expensive to use is just nonsense, they can only change their own pricing. It's the beauty of MIT license and open weights. If anything, these models are some of the safest in the world to use if you worry about a rug pull.
akman 2 hours ago [-]
90%+ cache hit rate is common, and so you'll see on places like openrouter that Deepseek cache cost is indeed a magnitude cheaper than the rest.
greenavocado 1 hours ago [-]
My usage thus far from api.deepseek.com
- input_cache_hit_tokens: 1,265,646,976 x 0.0000000028 = $3.5438115328
- input_cache_miss_tokens: 18,208,088 x 0.00000014 = $2.54913232
- output_tokens: 9,615,178 x 0.00000028 = $2.69224984
- request_count: 10,837 (no price)
This adds disk as a tier in the HBM → CPU → Disk KV cache hierarchy.
There's also a cluster of related KV-offload FS PRs: #49225 (read/write batching, still open) and #49152 (batch store/load in C, merged Jul 28).
It's hard to say if these are similar to the approach DeepSeek takes but they definitely seem very interesting.
onlyrealcuzzo 2 hours ago [-]
> Deepseeks secret sauce is the incredibly cheap caching (magnitude cheaper than other providers).
Can anyone working at one of the main US labs (Google, OpenAI, Anthropic) comment on WTF they haven't even tried MLA - despite the obvious massive advantages?
I know enough to know they aren't completely incompetent. So there must be a quite good reason.
But it remains a mystery to me.
DeepSeek's MLA is like almost 2 years old at this time. They've got thousands of people working on this stuff. They clearly have the ability to at least try it...
aabdi 1 hours ago [-]
They already are?
There’s a measurable performance tradeoff versus gqa so there’s reluctance.
For the most part though the new deepseek v4 tech is hca and mhc and people are still catching on like with moe and rl. Wait for 6 12 months, minimum time for next pre train.
ronsor 2 hours ago [-]
Are they not?
The big US labs are opaque and don't publish much of any technical details anymore. We don't know what they are or aren't doing, honestly.
ms8 2 hours ago [-]
Yes, there is warning, but also there are many providers on OpenRouter[0], hosting open weight model with similar pricing. The question is Will they go up as well?
DeepSeek has far cheaper cache pricing. That's the difference.
2 hours ago [-]
eli 2 hours ago [-]
I assume/hope this is about prices going up for the next release of Pro
HSO 2 hours ago [-]
even if they double it it`s from such a low base it is still supercheap
metadat 2 hours ago [-]
Source?
dolebirchwood 2 hours ago [-]
If you're on the DeepSeek Platform, you'd see this:
"We plan to raise the overall pricing for DeepSeek API services in the near future, with a significant increase expected. Please plan your usage accordingly. The specific pricing plan will be subject to official notice."
Running DeepSeek with Pi as well, any plugins you recommend running it with ( e.g. native browser for snapshots, etc. )
anramon 2 hours ago [-]
>even if it's not SOTA
And, probably 99.99% of people using LLM probably don't even need SOTA anyway.
swiftcoder 2 hours ago [-]
At least on these benchmarks, it seems to be pretty handily scoring up with the SOTA from 6 months ago?
tcp_handshaker 5 minutes ago [-]
And software keeps getting worst.
The analogy I like is that building software is running a Michelin restaurant. The moment you scale, the chef is just writing cooking books and is absent, and you move into franchising, you will be amazed at the bottom line revenue scaling, while customers will be progressively appalled with the food...
jmyeet 2 hours ago [-]
> I'm thinking about having it automatically filter and re-rank my social media feeds so I can steer the algorithm instead of the other way around.
I hadn't really thought about this but AI may well be the technology that disrupts and ultimately destroys social media.
The value proposition of something like FB or IG is, as we know, the network effect. The platform gets to extract value from user generated content. I believe that users should own the platform, a bit like the Wikimedia Foundation, because they're the ones that create value. Federation is a popular belief on HN and I've come to believe that's simply the wrong solution to the right problem.
Anyway, how these social media companies make money is by optimizing the feed for engagement. People know it too so you see people trying to build an audience by rage baiting. And then more time spent equals more advertising revenue.
But what happens when the AI can simply slurp all the posts and then filter and rank them? It destroys the engagement and advertising model. And I'm not opposed to that, honestly. It may be on eof the few good thing sto come out of AI.
Seconded. I love OpenCode and Pi, but omp is my daily driver.
ljosifov 9 minutes ago [-]
omp - current top, after using codex claude opencode pi that I still use too
dominotw 1 hours ago [-]
> Auto generate tests on CI for every pull-requests!
this seems like such a bad idea
EchoVoicy 52 minutes ago [-]
Depends on the prompt I think. If it's just "Generate tests plz" then I agree, but if its
"If this PR adds any new endpoints, ensure that there are functional and integration tests. If there are not, please investigate the feasibility and appropriateness, and create functional tests using the guide found on our wiki for guidance https://www.ourdevwiki.site/how-to-make-functional-tests" then maybe it could add some value.
But that very much depends on the specific system. Some tests are obvious, some not so much.
2 hours ago [-]
catigula 1 hours ago [-]
>Test coverage too low? Auto generate tests on CI for every pull-requests!
Terrible use-case.
wrobelda 1 hours ago [-]
Terrible comment.
_s_a_m_ 1 hours ago [-]
These posts have to be Chinese bots, these models are all trash. Used it via OpenCode for an hour, cost me one hour of my life. It is for anything complete trash.
r14c 4 minutes ago [-]
I've gotten a lot of good work done with deepseek models. Like with any generic harness there's some tuning that has to happen. I used open code for a while, but I've landed on pi.dev as my go to since its easier to tune and has better deepseek integration. iirc open code is quite bad at utilizing cache and doesn't have a lot of ways to specifically tune the harness for a particular model.
apitman 27 minutes ago [-]
I've found it to be pretty good so far.
dan_q 1 hours ago [-]
You're mad.
EchoVoicy 49 minutes ago [-]
Point 1 finger out, and you point 4 back.
greenavocado 1 hours ago [-]
(1) you used opencode
(2) what provider did you use. openrouter is trash because they shit up the model serving. no max effort and horrific cache utilization, on the order of 50-75%, absolutely garbage. beware
alex0015 58 minutes ago [-]
What should we be running deepseek on besides opencode? I chose it because I heard good things. Also provider is directly through deepseek credits.
greenavocado 56 minutes ago [-]
oh you used opencode go?
harness: omp.sh
NoboruWataya 26 minutes ago [-]
My Claude account was banned the other day. The only possible cause I can think of is that I tried to authenticate from the AI assistant in a JetBrains IDE and, not thinking, entered the details for my regular subscription rather than an API account. As soon as it became apparent that I needed an API account rather than a subscription, I just closed out of the tab. Nevertheless, about 20 minutes later I got an email saying my account was banned for a violation of the usage policy, and my appeal was rejected.
My initial thought was to sign up for ChatGPT, but I had $20 in OpenRouter so I've been trying out DeepSeek V4 Pro with Pi for the last few days and I gotta say, it's good enough for my use case. And even with paying for API usage rather than Claude's subsidised subscription, and with OpenRouter taking their cut, I will probably end up paying significantly less overall. And I really like the flexibility of being able to use whatever minimalist open source harness I want (and being able to switch providers easily, too).
(My demands probably aren't as high as many others' - I mostly use it for help with some hobbyist coding projects, and I tend to ask it questions about how to approach problems rather than just telling it to go off and code stuff for me.)
nodja 13 minutes ago [-]
I'm the same way, I have a very low/sporadic usage of any subscription I've tried. I now just use openrouter with DS4 pro/flash. It also gets rid of usage anxiety where I would try to justify the $20/month by forcing myself to use the tokens for projects as the weekly limit deadline neared.
andai 13 minutes ago [-]
I've been asking about psyops and bioweapons and I'm still going strong. I did get a Sonnet session shut down the other day though which feels like some kind of achievement.
ignoramous 11 minutes ago [-]
> My initial thought was to sign up for ChatGPT, but I had $20 in OpenRouter so I've been trying out DeepSeek V4 Pro with Pi for the last few days and I gotta say, it's good enough for my use case
If you prefer subscriptions, OpenCode Go ($10/mo), Cline Pass ($10/mo), Atlas Code ($20/mo), and CommandCode ($1/mo) serve some of the best open weights with generous limits. OpenCode Go currently gives $120 for $10 for DeepSeek Flash v4 (if you're okay with data retention).
Why? It's open weight, there are plenty providers on open router that are serving the latest v4 flash at 0.14/0.28 $.
LorenDB 51 minutes ago [-]
Yes, but even the cheapest providers on OpenRouter are charging at least 10x what DeepSeek does for cached input tokens, which is where DeepSeek gets most of the cheapness.
44 minutes ago [-]
petesergeant 16 minutes ago [-]
(nevermind, I was reading DeepInfra as Deepseek. My bad)
VulgarExigency 13 minutes ago [-]
You are missing a 0 to the left of the 2 on Deepseek's number
modeless 54 minutes ago [-]
This would be more convincing if those providers had converged on a number that was not the exact pricing of DeepSeek themselves. Clearly DeepSeek is setting the price here and without them holding it down I expect increases.
nicce 55 minutes ago [-]
The most expensive defines the price. Others need to be just slightly cheaper.
542458 3 hours ago [-]
Kimi K3 was an interesting model only a month ago, and now we're looking at the same performance for 1/20th of the price. Wild how fast this is advancing.
MarkLowenstein 1 hours ago [-]
Real question: is there anybody that is both maintaining alpha-dev capability by keeping abreast of all these daily changes, while also reserving enough time to actually work?
Seems like we've reached the event horizon of whether AI advances are worth paying attention to.
becquerel 25 minutes ago [-]
I think the play now is to just try out whatever the best new model is every time you see a headline that fundamentally reorganizes your conception of what's possible.
cyanydeez 56 minutes ago [-]
Are you saying we've reached peak Bike shedding?
petesergeant 14 minutes ago [-]
I don't think you need to be keeping abreast of them really, you just need to be using the best model you can get enough tokens from, which for many people is Fable 5 @ $200ish, ideally fanning out implementation to cheaper models
whinvik 3 hours ago [-]
Yeah either the benchmark isn't very useful anymore or V4 Flash is a really, really good model.
fallingbananna 1 hours ago [-]
GPT 5.6 Luna is an extremely cheap and still very capable model.
A chinese model being in the same ballpark of capability at half the price sounds believable to me.
ignoramous 2 hours ago [-]
In my use, DeepSeek v4 Flash (which replaced the quite excellent MiniMax M3) lags behind GLM 5.2 & Muse Spark 1.2 (let alone Kimi K3). Also, K3 is a much bigger multi-modal model, while Flash is text-only and likely optimised for coding tasks.
nwienert 2 hours ago [-]
Yep, and the v4 flash final is about 2.5x slower than preview making it no longer a fast model, in fact slower than Luna and bigger models in many cases.
Spark is actually the interesting one imo. It's significantly better, also significantly faster. If you are ok with letting Meta soak up your data (which DS does too) it's also the same price.
dyauspitr 1 hours ago [-]
Not for long, Deepseek is saying they will have a significant price jump soon. They really shouldn’t do it because they are on the cusp of capturing the scalable API market.
telotortium 46 minutes ago [-]
They need to be able to serve their market. The price increase is partly load shedding. If they improve their ability to serve their load, they can always drop it again, as OpenAI did with Luna recently.
ignoramous 2 minutes ago [-]
> as OpenAI did with Luna recently
My read is, OpenAI is neither able to claw b2b money (away from Ant) nor are they able to stave off open weights on the other. In short, they're struggling to hold onto their distant #2 position in the coding market, and these pricing changes reflect a (desperate) change in strategy.
thehamkercat 2 hours ago [-]
And now nobody seems interested in it because the price hasn't gone down
I strongly recommend trying this for programming tasks.
It is strong (not Fable strong though) with a much better “persona” than Opus, and very different blindspots. If you flip between Claude and this you will find both catch the mistakes of the other before they get out of control.
On balance I actually prefer DeepSeek for programming now, because of the way it talks.
chorizo 2 hours ago [-]
This also reflects my experience and should put to bed the distillation rumours. This model feels nothing like the Claude models, including tone and blindspots.
_s_a_m_ 1 hours ago [-]
I used it for one hour and it completely wasted my time. It is just too stupid for anything beyond println("I am retarded")
41 minutes ago [-]
andai 14 minutes ago [-]
The recently announced they're raising their prices 10x right?
Which would put them... exactly where everyone else is on this graph.
guilamu 10 minutes ago [-]
Where does this "10x" comes from?
KolmogorovComp 22 minutes ago [-]
Looking at the caching price of deepseek compared to its competitors, does it have a secret sauce or is it just subsidizing?
It's not frontier, but it's far past what we had at the beginning of the year. It's very usable. I get great instruction compliance, tool calling, and with a trivial workflows flow it has very good long-running performance as well.
evanjrowley 17 minutes ago [-]
The benchmark performance tells me DeepSeek v4 Flash could be very cost-effective at playing SNES/Gameboy games.
andai 12 minutes ago [-]
It won't be long before I can just stay home, and have my robot ride my bike for me.
walrus01 1 hours ago [-]
Oke of the great advantages of v4 flash 0731 is that even in the largest size unsloth quantized gguf, Q8 K XL, it will fit well within the resources of a 256GB DRAM server. If you have no gpu at all and are okay with setting up a workflow that handles slow token per second rate, give it a task and check back in 4-6 hours, it works great. And remember to give it more lengthy tasks to run overnight. Whatever workflow you set up, the idea is to keep it busy 24x7 doing different things in parallel.
SwellJoe 2 hours ago [-]
DeepSeek is my cheap and cheerful Chinese model of choice for API use. Has been for a while, but now it's Flash instead of Pro. Even cheaper, and now better then Pro. I feel like most of the major Chinese models are benchmaxxed, they have weird quirks every time I use them (Qwen 3.8 Max doesn't check its work and leaves stuff broken, doesn't write tests unless prompted, etc., Kimi ends up being quite expensive and rarely better than GPT Sol or Opus 5), while DeepSeek models seem to be generally as good as the benchmarks indicate: Not the best, but stronger across the board than any model within an order of magnitude of its price.
eli 1 hours ago [-]
Qwen 3.8 Max is very strong at troubleshooting and code review.
SwellJoe 57 minutes ago [-]
I'll grant it's very thorough when assigned a troubleshooting task. I'm not as confident of its code review though it is very good at security vulnerability auditing, and isn't hobbled for that work like Fable, and even Opus refuses some work in that area now.
1 hours ago [-]
surprisetalk 3 hours ago [-]
This reminds me of those pareto-style speedrun record charts when a new glitch is discovered.
When I see dramatic leaps like this, it tells me that the important hacks haven't yet been discovered.
gentlewater 2 hours ago [-]
I’ve been refreshing hacker news constantly for a week now waiting for v4 pro, after they stated it would follow «soon». I have learnt «soon» is a matter of definition.
indigodaddy 2 hours ago [-]
I guess you mean a "new" v4 pro?
ignoramous 2 hours ago [-]
> been refreshing hacker news constantly for a week now waiting for v4 pro
I'm curious... is anyone using DeepSeek V4 Flash from HugginFace? Is the cost around the same as directly form DeepSeek or from Openrouter?
minimaxir 3 hours ago [-]
It's always fun when Max reasoning is cheaper than High reasoning.
Terretta 2 hours ago [-]
Rework is expensive.
Tell your PjM who should tell your PgM who should tell your PdM, all the PMs...
Maybe if "the business" sees it is true of LLMs, they might believe it's true of giving better context to engineers up front then giving them time to think and prototype (thinking tokens are an answer prototype).
mycall 46 minutes ago [-]
I'm curious how much worse the 0731 quantizations do.
johnmlussier 49 minutes ago [-]
Been running it using Prime Agent and absolutely love it.
hnc3yfnu6f 33 minutes ago [-]
Wish more people understood this
simonw 1 hours ago [-]
That's a pretty great score for a model you can run on as (expensive) laptop.
CrosswordPuzzle 1 hours ago [-]
I'm really excited for where the open weight models go from here. I've had fun with just CPU inference on old servers that only have AVX1; here's hoping for commoditized TPU-like hardware!
nikp123 1 hours ago [-]
I just used it for some Kubernetes + FluxCD tasks and oh my is it good.
tosh 3 hours ago [-]
results comparable to gpt 5.6 luna but cheaper
promising!
minimaxir 3 hours ago [-]
Since the x-axis is log-scaled, DeepSeek is much cheaper than visually implied (mousing over the raw values, it's 1/4th the cost of Luna).
literallyroy 2 hours ago [-]
Is this pricing from Deepseek with training on usage?
Might not actually be that much cheaper, we don't know what margin OpenAI is charging on Luna API. Open models likely have much less margin.
LUmBULtERA 2 hours ago [-]
Is it still cheaper than Luna if using an OpenAI subscription? My gut is no, but I have not done the math.
swiftcoder 2 hours ago [-]
You'd have to compare against something like the OpenCode Go subscription, and I'm fairly sure deepseek napkins out cheaper in that scenario
LUmBULtERA 2 hours ago [-]
I'm still not sure, there's a promo going on now, but generally Go gives $60 of API credit and right now it might be $120 with deepseek. But $20/month OpenAI subscription I believe gives you many hundreds of API-equivalent usage? I've heard $100/month giving many thousands API-equivalent per month.
minimaxir 2 hours ago [-]
Everything is cheaper if using a subscription, but some applications require API usage.
sourcecodeplz 2 hours ago [-]
wow. i remember when GPT-5.2 (medium) was everyone's favorite.
ARC-AGI II:
- GPT-5.2 (medium) %26.7 ($0.759)
- DSV4-Flash (max) %61.4 ($0.04)
luyu_wu 3 hours ago [-]
It is wild that this a log scale of cost to me!
xyzsparetimexyz 2 hours ago [-]
That page needs a Pareto frontier display. But wow, it absolutely demolishes.
3 hours ago [-]
clayhacks 3 hours ago [-]
Why wasn’t this run against ARC-AGI-3? Or did it fail to solve anything?
chorizo 2 hours ago [-]
They tweeted that ARC-AGI-3 results take longer to run, so we’ll need wait a bit longer.
leizhou 1 hours ago [-]
so cool. does it mean it can understand the verificated code
Havoc 2 hours ago [-]
They did recently announce they're increasing prices though (got a mail yesterday I think), so not sure this analysis showing it as price outlier will last
minimaxir 2 hours ago [-]
That is only when using the DeepSeek API directly. OpenRouter has 24 different providers serving it at existing prices.
iagooar 1 hours ago [-]
I love DeepSeek V4 Flash since the pre-0731, now even more. It is the first model that is truly too cheap to meter.
But I find it having a pretty significant problem with tool calling - no idea why, but tool calling with it is SLOW. As long as the model is reasoning, all good. But give it a bunch of tools and it becomes extremely slow.
Am I the only one experiencing this?
dcchambers 2 hours ago [-]
This latest DeepSeek is almost at the "too cheap to meter" level. That's going to be a larger unlock than models like Fable/Mythos that are way too expensive to justify, IMO.
What secret sauce do they have?
throwaway_95283 2 hours ago [-]
limited resources, no modern GPUs, no $10 billion dev budgets.
pair it with codewhale, 50 agents, 200 MB of ram.
pama 47 minutes ago [-]
No secrets—all published. Very efficient attention. Excellent kernels. Great caching subsystem. Small and well trained model.
If I had the GPU size, hook it up to llama.cpp and setup the --reasoning-budget and reasoning-message; Most of that additional reasoning is a lot of garbage and you can redirect it to useful output.
That's how I handle the Qwen27B and 35B
WhitneyLand 2 hours ago [-]
The DeepSeek team is so strong, very impressive.
Imagine if they had GPU resources of western labs.
mosura 2 hours ago [-]
Necessity is the mother of invention.
SV companies get way too comfortable when they have enough in the bank to stay running more than three months.
antirez 3 hours ago [-]
Price is not a good meter. Active parameters per token are. Joule would be even better.
orbital-decay 2 hours ago [-]
It's an excellent metric, the amount of applications not viable now due to cost/latency/throughput is vastly bigger than the amount of current use cases. Even current ones do benefit, e.g. it's a great executor subagent.
Energy and intelligence are good too, sure.
fallingbananna 36 minutes ago [-]
What if we used 100% of the brain all the time?
As an end consumer, I don't care about the number of active parameters. I really do care only about the tracked metric (how well does it do the job, and how much does it cost... ideally also with time included, but that wouldn't fit on a 2D chart)
minimaxir 2 hours ago [-]
Price accounts for computational/architectural efficiency improvements whereas active parameters does not.
polytely 2 hours ago [-]
for someone with a limited budget it is actually very important because it makes me less scared to experiment.
muricula 3 hours ago [-]
Price is confounded by VC subsidies, economies of scale, and inference optimizations. I think a more interesting chart would be ARC AGI vs forwards pass flops or ARC AGI vs training tokens. Of course we don't have those numbers for the closed source models or even some of the open weight ones.
With the exception of cache costs, all providers have similar input/output costs.
kennywinker 2 hours ago [-]
Not counting the cost of making the model, which is subsidized by… someone? The chinese gov i think?
2 hours ago [-]
_aavaa_ 2 hours ago [-]
Subsidized by inference profits and volume.
npn 2 hours ago [-]
weak argument. deepseek v4 flash is open weight, you can easily find other providers with competitive price with Deepseek (except for input caching), some even half as cheap.
OpenCode Go even has double limits temporarily so for 10 USD you effectively get 140 USD of tokens to spend. It would impress me if someone could burn that amount with "normal" usage. Even when running multiple sessions.
I have a Claude Max subscription but I've barely touched it, it just feels like a step back to have to think about limits and usage even though the models are stronger.
The beauty of intelligence at this cost (even if it's not SOTA) is that it opens a whole bunch of new use cases. Test failure in CI? Have the bot automatically propose a fix, its cheap enough that you can discard it w/h issues. Test coverage too low? Auto generate tests on CI for every pull-requests! Monitoring server logs, continuous security audits and investigating every received exception now becomes possible.
I'm thinking about having it automatically filter and re-rank my social media feeds so I can steer the algorithm instead of the other way around.
Perhaps other people (with enormous budgets) were already doing all of the above but for us this is a really exciting release!
i used for work where i did less and it quickly reaches thousands if you're not careful. i can already see what some will say: skill issue et cetera - whatever.
With 5 active sessions going nonstop? That seems like a pretty important qualifier.
$5/days is ~330 Mtok/day, that’s a nontrivial amount of work, and none of the gpts are more efficient than deepseek at $/task if deepseek meets your quality bar.
Not true. Sol on XHigh or Max runs out even on the $200/mo plan. It's not close to effectively unlimited. Maybe at 2x the current allowance it can.
which in your case is?
My family uses it. I have gallery apps (yearbooks for each year are a lot of fun!) of us on trips and just living, an outlining app that's a mesh of Workflowy and Org Mode (it's called Fluxtral), a markdown-backed app (it uses marked.min.js, and is called Dextral) that offers documents, logs, calendars, and kanban boards, all parsed from markdown. I have a List app for gear, trips, shopping, etc. that we all can contribute to. There are utilities (world clock, calendar) and games (an oracle for RPGs, a KenKen implementation), and apps (a diagram editor that exports to SVG, a web-launcher that uses pneumonics, a Scheme-based hacking environment, and a spreadsheet that does most of what you'd expect aside from Solver and Pivot tables).
I started these projects before AI, and made slow progress over the years, but the modern versions of all this stuff have been built with Deepseek V4 Flash. I've also used Gemini in the very early days, and Kimi K2.6 later on, but these days, since I can now host Deepseek v4 Flash 0731 in a 2-bit quant on my Strix Halo box (128GB, but only about 250GB/s of memory bandwidth, so 15t/s), I used Deepseek with omp for almost everything. It's a very capable model, and I'm amazed I can run it locally and get good results. It's really revolutionary for my (small) use cases.
oh, they're mad.
vLLM has recently released a similar approach. It's not as effective as what DeepSeek does but still an interesting development.
I have no doubt that in due time other providers will match or perhaps even beat the current DeepSeek prices.
The entire issue is caching, I tried to write some custom to dump to disk kv-caching using some ideas from their papers and my experience with snapshots and vm checkpoint systems, I must say they must have really squeezed that lemon it's hard.
Atleast me with Sol couldn't figure it out over a couple days, a few hours each day, which isn't much but I did feel a bit stuck with existing solutions and felt like I might have to write something from scratch. But if you are willing to put in the effort into the infra I do think it's doable. But it will be really hard to pull it off.
My congrats to anyone who manages to pull it off, they might be able to kill off most AI labs. Assuming they can find the compute, Deepseek really has killed all models for me other than Sol/Fable/Opus/K3 tier stuff.
It's interesting that most open models adding 1M context did it in a way that reduces KV cache size (though DeepSeek was the most aggressive, using compressed attention on all layers), but only a couple providers turned it into a discount on cache reads.
They "can" is the caveat here. Rented GPUs are going up in pricing. I recently got an email that DigitalOcean pricing of GPUs were going up.
So
1. They have to get a hold of them (availability is bad)
2. They have to maintain the pricing
Cache:
Hit rate: 98.582% (1,265,646,976 / 1,283,855,064)Deepseek charges $0.0028 per cache read on Openrouter. The next cheapest is $0.018.
That's a massive difference and quickly adds up on coding sessions (which often hit 95%+ cached tokens).
This adds disk as a tier in the HBM → CPU → Disk KV cache hierarchy.
There's also a cluster of related KV-offload FS PRs: #49225 (read/write batching, still open) and #49152 (batch store/load in C, merged Jul 28).
It's hard to say if these are similar to the approach DeepSeek takes but they definitely seem very interesting.
Can anyone working at one of the main US labs (Google, OpenAI, Anthropic) comment on WTF they haven't even tried MLA - despite the obvious massive advantages?
I know enough to know they aren't completely incompetent. So there must be a quite good reason.
But it remains a mystery to me.
DeepSeek's MLA is like almost 2 years old at this time. They've got thousands of people working on this stuff. They clearly have the ability to at least try it...
There’s a measurable performance tradeoff versus gqa so there’s reluctance.
For the most part though the new deepseek v4 tech is hca and mhc and people are still catching on like with moe and rl. Wait for 6 12 months, minimum time for next pre train.
The big US labs are opaque and don't publish much of any technical details anymore. We don't know what they are or aren't doing, honestly.
[0] https://openrouter.ai/deepseek/deepseek-v4-flash-0731#provid...
"We plan to raise the overall pricing for DeepSeek API services in the near future, with a significant increase expected. Please plan your usage accordingly. The specific pricing plan will be subject to official notice."
And, probably 99.99% of people using LLM probably don't even need SOTA anyway.
The analogy I like is that building software is running a Michelin restaurant. The moment you scale, the chef is just writing cooking books and is absent, and you move into franchising, you will be amazed at the bottom line revenue scaling, while customers will be progressively appalled with the food...
I hadn't really thought about this but AI may well be the technology that disrupts and ultimately destroys social media.
The value proposition of something like FB or IG is, as we know, the network effect. The platform gets to extract value from user generated content. I believe that users should own the platform, a bit like the Wikimedia Foundation, because they're the ones that create value. Federation is a popular belief on HN and I've come to believe that's simply the wrong solution to the right problem.
Anyway, how these social media companies make money is by optimizing the feed for engagement. People know it too so you see people trying to build an audience by rage baiting. And then more time spent equals more advertising revenue.
But what happens when the AI can simply slurp all the posts and then filter and rank them? It destroys the engagement and advertising model. And I'm not opposed to that, honestly. It may be on eof the few good thing sto come out of AI.
this seems like such a bad idea
"If this PR adds any new endpoints, ensure that there are functional and integration tests. If there are not, please investigate the feasibility and appropriateness, and create functional tests using the guide found on our wiki for guidance https://www.ourdevwiki.site/how-to-make-functional-tests" then maybe it could add some value.
But that very much depends on the specific system. Some tests are obvious, some not so much.
Terrible use-case.
harness: omp.sh
My initial thought was to sign up for ChatGPT, but I had $20 in OpenRouter so I've been trying out DeepSeek V4 Pro with Pi for the last few days and I gotta say, it's good enough for my use case. And even with paying for API usage rather than Claude's subsidised subscription, and with OpenRouter taking their cut, I will probably end up paying significantly less overall. And I really like the flexibility of being able to use whatever minimalist open source harness I want (and being able to switch providers easily, too).
(My demands probably aren't as high as many others' - I mostly use it for help with some hobbyist coding projects, and I tend to ask it questions about how to approach problems rather than just telling it to go off and code stuff for me.)
If you prefer subscriptions, OpenCode Go ($10/mo), Cline Pass ($10/mo), Atlas Code ($20/mo), and CommandCode ($1/mo) serve some of the best open weights with generous limits. OpenCode Go currently gives $120 for $10 for DeepSeek Flash v4 (if you're okay with data retention).
Seems like we've reached the event horizon of whether AI advances are worth paying attention to.
A chinese model being in the same ballpark of capability at half the price sounds believable to me.
Spark is actually the interesting one imo. It's significantly better, also significantly faster. If you are ok with letting Meta soak up your data (which DS does too) it's also the same price.
My read is, OpenAI is neither able to claw b2b money (away from Ant) nor are they able to stave off open weights on the other. In short, they're struggling to hold onto their distant #2 position in the coding market, and these pricing changes reflect a (desperate) change in strategy.
it's still $3/$15 for all providers on openrouter
because of some Kimi license
https://openrouter.ai/moonshotai/kimi-k3#providers
Uptime looks crap, though.
It is strong (not Fable strong though) with a much better “persona” than Opus, and very different blindspots. If you flip between Claude and this you will find both catch the mistakes of the other before they get out of control.
On balance I actually prefer DeepSeek for programming now, because of the way it talks.
Which would put them... exactly where everyone else is on this graph.
[0] https://taylor.town/silver-landmines
When I see dramatic leaps like this, it tells me that the important hacks haven't yet been discovered.
https://reddit.com/r/DeepSeek is where the fellow F5ers are at.
Tell your PjM who should tell your PgM who should tell your PdM, all the PMs...
Maybe if "the business" sees it is true of LLMs, they might believe it's true of giving better context to engineers up front then giving them time to think and prototype (thinking tokens are an answer prototype).
promising!
ARC-AGI II:
- GPT-5.2 (medium) %26.7 ($0.759)
- DSV4-Flash (max) %61.4 ($0.04)
But I find it having a pretty significant problem with tool calling - no idea why, but tool calling with it is SLOW. As long as the model is reasoning, all good. But give it a bunch of tools and it becomes extremely slow.
Am I the only one experiencing this?
What secret sauce do they have?
pair it with codewhale, 50 agents, 200 MB of ram.
https://news.ycombinator.com/item?id=49198661
https://x.com/thdxr/status/2085377844515922210
That's irrelevant when you use $/task as the metric, which the OP does use.
That's how I handle the Qwen27B and 35B
Imagine if they had GPU resources of western labs.
SV companies get way too comfortable when they have enough in the bank to stay running more than three months.
Energy and intelligence are good too, sure.
As an end consumer, I don't care about the number of active parameters. I really do care only about the tracked metric (how well does it do the job, and how much does it cost... ideally also with time included, but that wouldn't fit on a 2D chart)
With the exception of cache costs, all providers have similar input/output costs.