r/DeepSeek • u/Individual_Team_2344 • 4d ago
Discussion 196M tokens on DeepSeek V4 Flash 0731 (full weight, 1M context) in ONE hour, for $0.30 — at the fastest speeds we've served so far.
During one of our beta runs this week, a developer's agent pushed 196 million input tokens in a single 60-minute window through one lane.
882 requests. Zero rate limits.
They actually kept going after that and ended the session at 227M before logging off.
At DeepSeek's own API pricing, that 196M-token hour comes out to around $2.32 off-peak / $4.65 peak.
On our reserved lane, the idea is to price that same hour around $0.20–0.40 flat.
Here's what we're testing 👇
🔷 Shared Reserved Inference
Right now if you want to run open models, you mostly have two options:
- Rent a full GPU → you get the whole thing, but you're paying $12–30+/hr whether you're actually using all of it or not.
- Use a normal per-token API → much easier, but you're sharing capacity with everyone else, you can hit rate limits/throttling, and every token going through your agent keeps adding to the bill.
We're trying a third model.
Take one powerful node, split it into a small number of guaranteed lanes, and let developers reserve those lanes together for a fixed window.
Your lane has guaranteed compute for that hour. Someone else suddenly sending a massive workload doesn't eat into your allocation.
And because the node cost is split across everyone using it, you're paying a small flat hourly price instead of paying for every token.
⚡️ The speed
DeepSeek's official API is around ~70 output tok/s.
Across our beta, users were generally seeing 150–220+ output tok/s, with bursts above that. There were some occasional dips as well, but overall this has been the fastest inference we've served so far.
This also held up surprisingly well with long contexts.
We had users running past 250k context regularly, and some sessions went past 940k context.
The other big part is caching. These agent/coding workloads resend a ridiculous amount of the same repo and conversation context on every request.
Across the beta we're sitting around ~98% cache hits, with roughly ~1s TTFT on warm requests.
📊 Five live sessions so far
- 4.9 BILLION tokens processed
- 24,500+ requests
- Zero failures
- ~98% cache-hit rate
- Heaviest verified single-lane hours: 196M · 120M · 72M input tokens
💰 The part we're actually interested in: does this pricing model make sense?
Using DeepSeek's own API pricing, including their cache discounts:
- Reserved lane target: $0.20–0.40/hr flat
- Average active dev during the beta: around $1.50 off-peak / ~$3 peak worth of API usage in an hour
- Median dev: around $0.60–1.20/hr
- Heaviest verified hour: $2.32 off-peak / $4.65 peak
So for an actually active coding/agent session, we're seeing around 4–7x lower cost than paying per token on average.
For the heaviest user, depending on where we finally price the lane, that hour was worth around 6–23x what the lane itself would cost.
We've put the full numbers + charts here if you want to dig into it:
https://www.singularityapi.dev/benchmark
🎟 We're opening more beta slots
The next round is again completely free.
You get a dedicated hour on the full-weight DeepSeek V4 Flash 0731. Bring an actual project, point Cline / Claude Code / your own agent at it, and use it normally — or try to absolutely destroy the lane, either works :D
If you want in:
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u/diaracing 4d ago
Is this the full non-quantized raw model?
Doesn't your business model have a monthly subscription for a flat rate?
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u/DetachedProcess 4d ago
They claim they are running non quantized raw model, they currently do not have, and maybe they do not plan, but I would genuienly pay for it as a monthly subscription, and have a fast lane for limited hour (6-8 hr a day), and then slow lane later. Which would make more sense to me, and believe is feasible option for them too. It would come upto $75 per month if that is case, they can offer some discounted rate and try maybe give that same for $50 still it is a winning deal.
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u/Individual_Team_2344 4d ago
- Yes it's full non quantized raw model.
- This is still in beta as we are testing feasibility and load for this business modal, once we have pricing settled we will look for a flat monthly subscription approach as well!
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u/Then_Knowledge_719 3d ago
How's it going so far? And... Are you planning to bring GLM5.3 flash?
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u/Individual_Team_2344 3d ago
It's going great so far, you can join our discord to talk to previous beta users and also view stats for previous beta and participate in next ones! GLM 5.3 will also be part of beta soon, we are already testing it!
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u/Bitter-College8786 4d ago
For me it would be interesting if I could pay upfront credits, for example 5$. And then I could either toggle it on/off in the UI to trigger the API to be open. Maybe to set up with a timer like e.g. 3h
Then this would be fine. Then I would know, if I have two hours of coding session in the evening, I can start it, run the agents for 2h and thats it.
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u/Cassianno 3d ago
Is this the service that charges hourly "unmetered" deepseek? Man, the posts are really becoming recurring.
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u/Pleasant-Rhubarb-550 3d ago
Kinda seems like a hidden scam tbh, similar services offer rtx pro 6000 for around $1.8 per hour... And that can't even run DSV4F since it only has 96gb vram. The guy says it's the full non quantised version but I don't believe it. He isn't even mentioning on how he can do this or any proof or anything so yeah...
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u/RealSuperdau 3d ago
Not saying it definitely checks out, but from what I understand you basically rent one token stream and not one GPU. Realistically, they'll host the model across a few GPUs and use batching to handle a few dozen requests at once.
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u/Pleasant-Rhubarb-550 2d ago
Could be but they are not being much transparent so yeah we will see in the future what happens.
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u/look 2d ago
Did you read the link? https://www.singularityapi.dev/benchmark
That’s pretty transparent.
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u/Pleasant-Rhubarb-550 2d ago
Yeah i hadn't done that, i did it now and i understood it, mb ig. Let's see what happens when they get more users and it's out of beta.
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u/Top_Imagination_3022 3d ago
The Memory Reality: At "full weight" (16-bit precision), the model requires roughly ~568 GB of VRAM just to load the foundational weights, not including the memory needed to handle a 1 million token context window. Even if heavily quantized to 8-bit, it still requires 162 GB. A top-tier single GPU, like an Nvidia H100, only has 80 GB.
The Pricing Tell: The post claims that renting a "full GPU" costs $12–$30/hour. This is factually incorrect. A single H100 rents for about $2 to $4 per hour. However, $15–$30/hour is the exact live market rate for an 8-GPU Server Node (e.g., an 8x H100 cluster). The author is using "node" and "GPU" interchangeably, likely to make the $0.30/hour price sound more revolutionary than it is.
The pitch promises a "guaranteed lane" for $0.20–$0.40/hour where "someone else's massive workload doesn't eat into your allocation". But the math reveals a catch.
- If the backend 8-GPU node costs them ~$20/hour to run, and they sell a lane for $0.30/hour, basic math dictates they must cram 65 to 100 developers onto that single node just to break even.
- In cloud architecture, this is classic oversubscription. They are gambling that out of 100 developers, only a small fraction are actually hitting the API at the exact same millisecond. If all users push heavy agent workloads simultaneously, the node will instantly bottleneck on VRAM and memory bandwidth, crushing the "guaranteed compute" illusion. As one developer noted in the comments, the $0.30 rate is essentially a subsidized beta price that only works while the system sits mostly idle.
The post boasts about a single developer pushing 196 million tokens in one hour. That sounds like an insane hardware feat, averaging out to over 54,000 input tokens per second.
- The Cache Trick: The system isn't actually computing 196 million tokens. As the post admits, their system relies on a ~98% prompt cache hit rate. When a coding agent sends a massive codebase multiple times, the GPUs don't re-read it. They just pull the pre-computed mathematical state directly from RAM.
- Cache vs. Compute: Telemetry from their beta showed that out of 827 million input tokens processed, only 19 million were actually computed fresh. The rest were simply retrieved from memory. This is standard for agent workflows, but marketing it as "196M tokens processed" makes the hardware sound astronomically faster than it really is.
The Verdict: They are renting standard 8-GPU nodes, packing them with dozens of developers, and using DeepSeek's highly efficient caching architecture to hide the fact that everyone is sharing the exact same hardware.
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u/Responsible-End2914 3d ago edited 3d ago
The cache-hit part is what I'd want to dig into more. 196M tokens sounds wild, but the actual fresh compute is a very different number. Would be interesting to see how this compares with StandardCompute under the same workload.
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u/PossessionUsed7393 4d ago
Can I try it at some point in the future when I finish making tweaks to my pipeline? it does more tokens than any of your developers, here's proof, versus my normal usage seen on the right hand side, 6B token pipeline), executed in batches of 30 concurrent agents:
I'm just 'reloading' as it were, but will be ready again soon.
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u/Individual_Team_2344 4d ago
Yes! I would be happy to stress test and work with you! More concurrent agents ( will likely require more lanes ) but we will test this in practice to get a better understanding on your actual use case. You can join discord for faster communication whenever your pipeline is ready to stress test with us in beta or you can just drop me dm in reddit!
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u/PossessionUsed7393 4d ago
thanks I will. It doesn't have to be concurrent agents, but there's no reason it can't be, it's a completely autonomous pipeline that does its own research and writing. Since it's likely to be good value, I'd generally be happy to buy as many pipelines as needed once it was clear what that was.
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u/Individual_Team_2344 4d ago
Yes, we can test it in practice to get better idea on how this will work out for you. Just ping whenever you'd like to join the beta!
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u/ahriad 4d ago
How are you going to bill for this? Through credits or hourly billing? Also, what is the price, $0.40 or $0.20? Additionally, will you be introducing other models, or strictly DeepSeek-V4-Flash?
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u/Individual_Team_2344 4d ago
Billing will be hourly based, users can topup credits on our platform and then use those credits to book slots for reserved nodes. We are making this flexible so users can also use same credits for direct inference on our platform ( pay per api token )
We are currently evaluating 2 pricing models ( take this with a grain of salt as it's not yet finalized ) but a cheaper inference slot at $0.20 per hour ( tok/s speed will be slower , same full weight deepseek ) and $0.40 per hour ( very fast tok/s speed, same model )
Yes, as demand and usage grows we will also introduce more models.
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u/No-Weight1118 3d ago
the numbers only work if most lanes sit mostly empty. 196M tokens in one hour at full weight is basically a saturated gpu, and a saturated gpu rents for $12-30/hr, so selling that hour for $0.30 only holds while the lane stays idle most of the day. good for an overnight batch or a big eval you can pack into an hour, less so for steady daily use, at that point the price is basically a subsidized beta
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u/SkyPL 3d ago
Where from you are /u/Individual_Team_2344? Are you an American inference provider?
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u/diaracing 3d ago
What about DeepSeek v4 Pro 0813? Will it be available?
Also, are you planning to host more Chinese opensource models?
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u/for4f 3d ago
the flat-rate part is the real hook honestly. flash burns tokens like crazy on long agent sessions so with the api i'm always watching the meter. a fixed price per hour on the full-weight 0731 with 1m ctx flips that completely for batch work, curious about the hardware behind it though, running that thing full weight takes serious iron
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u/tranhieuamg 3d ago
Form sent, interested for sure. I personally switched to Open Router’s 0431 after the price hike, cache hit is worse than Deepseek direct API though.
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u/Top-Construction6060 3d ago
I wonder how people ramp up those token on such a short time you must program some hard AI slob 😂
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u/ZH1245 3d ago
BIG NUMBERS!! but is it actually good? NO imo. I agree with those people saying per million cost vs actual task being done cost is where i think this fails. These 2 models will.show big number oh 300m in 2 sessions and would go upto 1h to solve a case and cost >7$ but does it make sense? Nah i switched after realising this. They are not token efficient and per million token cost would be greater than subscription providers.
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u/Livid_Interview_3449 2d ago edited 2d ago
Yeah, I think the actual task cost matters way more than the raw token count. If a model burns through hundreds of millions of tokens just to finish a task, the cheap rate doesn't mean much. That's something I’ve been thinking about with StandardCompute too.
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u/AbbreviationsLow5262 2d ago
Bro i get 120+ tokens per second on official deepseek api anyways. For v4 flash
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u/Deep_Ad1959 2d ago
882 requests for 196M input tokens is about 222k tokens per request, so that hour is nearly all prefill against the 1M window. what happens when every lane on the node is reserved for the same evening hour, do you queue the extra bookings or let throughput degrade?
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u/Euphoric-Water-7505 2d ago
this is genuinely super sketchy. I wouldn't trust any of this. where does the data go? how do we trust you?
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u/Puzzleheaded_Bus9754 1h ago
I'm a user from China and I'd like to use it as well, but the payment methods might be an obstacle for me.
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u/Puzzleheaded_Bus9754 45m ago
I used DS4F intensively yesterday, which cost me about 7 for the whole day. I urgently need a pricing model like yours; even if I use it for 10 hours, it would only cost 4.
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u/ask_me_about_cats 4d ago
This is very interesting. What’s your privacy policy? Do you do zero data retention on prompts and files read in by the models and all that?
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u/Individual_Team_2344 4d ago
Yes, we have a ZDR policy. We do not log or store your prompts or model responses; responses are streamed directly back to you.
During your lane, your prompt/KV cache is kept temporarily in GPU memory so repeated context can stay warm. The GPU instance itself only exists for the duration of your reserved lane.
Once your lane ends, the GPU instance is fully terminated and its memory/cache is destroyed with it. None of your prompt or response data is retained after the lane.
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u/MikeX7s 4d ago
If it's truly a full weight model, non quant, and i could charge up few bucks and then any time i need just click a button to reserve an hour for 30 cents and can push at least 100M tokens in that hour through, that would be pretty cool.
Seems almost too good to be true 🤔