▲ 8 r/Neuralwatt
Anyone using K3 Fast on Neuralwatt?
Currently showing as the cheapest option right now across providers on OpenCode.
u/jpcaparas — 2 days ago
r/Neuralwatt
▲ 6 r/Neuralwatt
Need someone to help explain my NW Usage on the $20 plan
Hi Folks,
Recently tested out a $20 NW sub because I keep hearing its cheap for GLM compared to something like Ollama Cloud Pro or Opencode/CommandCode/the API
Does this picture make sense? That's my total usage with $1 overage as well. (This was in 2 Days)
Important to note I can easily last a week on Ollama Cloud Pro (with the last day giving me a bit of trouble where I switch to something else)
https://i.ibb.co/TBZdb271/Screenshot-20260817-224911.png
(I'm sorry idk how to attach pictures on reddit)
u/angelicakahn — 3 days ago
▲ 19 r/Neuralwatt
Is this believable? This is like crazy cheap
The model used is deepseek v4 flash.
With all the cached tokens, it's still crazy. 2.56B tokens for 14.51$?
u/Amazing_Concept_4026 — 3 days ago
▲ 8 r/Neuralwatt
When GLM 5.3?
Does NW have an updates page anywhere with up-to-date data without opening Discord?
Are they dropping in 5.3 as a replacement for 5.2 like they did for DS V4 Flash?
u/Fun-Aardvark-1143 — 3 days ago
▲ 35 r/Neuralwatt
Kimi K3 is fully live. Plus Flex, Session View, API compatibility, and Surge Protection
Hey everyone, we have another big batch of updates to share with you all today.
Kimi K3 is out of preview: We've spent the time since launch tuning the serving side, and K3 is now fully available for production workloads. Concurrency limits will ramp up over the next few days as our final validation completes.
Flex now covers K3: Same deal as Flex on our other models -- if your workload can tolerate some timing flexibility (batch jobs, overnight runs) this is the most economical way to run K3.
Anthropic Messages API and /v1/responses support is entering beta: If you've built against either format, you can point your existing tools at our endpoint and they'll run on Neuralwatt with the same energy visibility as everything else. We're opening beta access over the coming days as validation completes, so keep an eye out.
Session View is live for everyone: Instead of account-level totals, you now get a session-by-session breakdown of exactly what you consumed. This is the most detail we've ever offered on your usage, providing a granular view of the requests you ran, the energy they used, and what they cost.
Surge Protection: This one's new -- Surge Protection ensures you only pay for the energy that powers your work. From time to time, a request can draw more energy than the work it's doing should require. When it happens, Surge Protection catches it in real time and shields your usage from the excess. When it kicks in, you'll see it flagged in Session View, so you'll always know it stepped in.
These updates will roll out over the next several days.
Also, we're headed to NYC for Climate Week next month and are thinking about a meetup. Anyone interested? We have a poll coming; if enough of you are around, we'd love to see you.
u/Negative_Cable1967 — 9 days ago
▲ 6 r/Neuralwatt
API vs Subscription?
Which is the better deal?
u/Substantial_Fish6717 — 11 days ago
6B Tokens on Writing Pipeline - Worth it
I have a research -> writing -> qa agentic pipeline that I've been working on, I actually created it to be used by local Gemma 4 12B, since it's output token heavy. Local AI handles it well, in fact I could have used it. But since the release of Deepseek V4 Flash I thought why not adapt it for DeepSeek, it's a smarter model and it's slightly more thorough at research. Gemma is good too but it tends to rely on snippets whereas with DeepSeek it's really interested in sucking up as much info as possible before it writes. Try as I may, you can't teach a smaller model to be more 'thorough' - at least not with context engineering.
I've just run it 4,100 times, each written piece was between 1,800 and 2,500 words and I thought I'd share my cost. Total was 6B tokens at a pretty decent cache hit. It ended up being about 120mil output tokens to write all 4,100 pieces. Each run averaged between 40-80k tokens in total, maybe a bit more. I was able to almost halve my token usage by having Kimi K3 optimise the pipeline and I used a number of custom Pi add-ons to facilitate caching of documents for research as well as various scraping tasks. I also used Exa.ai for search (another $50-60 or so in API cost there).
Concurrently I also ran a few tests to see if r/Neuralwatt would be cheaper for inference using their energy pricing. They were not cheaper, in fact they were about double the price with energy, 250 pieces for US $8 versus $4 on Deepseek. Neuralwatt's pricing indicator says that the pipeline would have been cheaper at $6 for 250 if I had used token pricing. So that's interesting.
Anyway thought I'd share. It's excellent value, and given that I was able to halve my token usage by optimizing the pipeline, I'm not that scared of them doubling the price, or even tripling the price.
If they quadruple the price I think they lose to local AI inference for these types of workloads. But writing based on research is actually something local AI does really well. It also wasn't time sensitive. It was convenient for me to be able to produce these in a batch now, but I could have had them backgrounded for weeks without affecting the outcome.
u/PossessionUsed7393 — 14 days ago