"Based on this framework, we have achieved high-throughput, low-latency large-scale inference services for DeepSeek V4.1 Flash. Currently, the service throughput of a single cluster is 155 trillion tokens/day, and the overall revenue is $38 per card per hour (at off-peak pricing)"
zhuanlan.zhihu.com/p/2095560…
A new frontier for on-device speech.
We're open-sourcing Phonon, a suite of TTS models under 50m parameters, setting a new standard for naturalness and accuracy across languages, with the broadest inference support to date.
Phonon-31m is available under Apache 2.0.
gradium.ai/phonon🧵
daily dose of computer architecture literature could leave you in two states
"what the hell!" - excitement, intrigued
"what the hell?" - visible confusion, disapointement
HPSFcon is going to one of the best food cities in north america!!
and if you're extra nice, the @Montreal account might even send you a little heart!!
You can share what you learned in 8 minutes. #HPSFcon 2027 is accepting lightning talks, along with sessions, panels, and posters. Proposals are due January 17. 🎤 Take the mic April 12-16 in Montréal!
Explore the topics and start your proposal today:
bit.ly/3VAd5FI
🚀 Introducing DeepInfer, our in-house inference framework, now fully open source!
Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable.
🔗 github.com/deepseek-ai/DeepI…
1/4
and yet colossus was making management decisions before the concept of an "electronic computer" was a thing
the calculus of lives lost vs risk of detections is older than any active mathematicians career.
Today we're releasing prime-rl v0.10.0 and verifiers v0.4.0
We added our new RL algorithm IPO as the default, tailored for async RL stability, as well as performance improvements and new model support
INTELLECT Policy Optimization (IPO)
In async RL, trainer and inference never agree exactly on a token's probability. IcePop masks on the ratio, which misjudges both tails
IPO masks on the probability difference instead
>arrive at HRT party
>ask the door girl if it's quant finance or estrogen
>she doesnt understand
>pull out illustrated diagram explaining the difference between quant finance and estrogen
>she laughs and says “it's a good party sir”
>go inside
>it's an estrogen party
ok so interesting; per Bloomberg quoting Jim, a lot of interest came after they ran DeepSeek R1 back in Q2, but those models were already a year old?
Haven't been watching if they've made progress on running more advanced models, maybe @davorVDR can comment?
model matrix hasn't been marked updated since December 2025 which is a little strange... github.com/tenstorrent/tt-me…
but they also haven't updated it to reflect since version .65, where as the latest tag is 0.8....
incomplete thought:
There's a reasonable argument to be made that cost cutting open models is actually a net benefit for AI safety in that it drops the available profit margins of most frontier model development
If that's the case, the economic hunger to reinvest at current...
In essence, if firms are capable of releasing (through government subsidy for geopolitical reasons) near frontier open weight models that cull the profit margins of frontier model providers, you see a natural deceleration in capital available to push frontier models forward.
...
if that happens, you extend the effective runway through scarcity of slowing down AI to allow for the finding of new, more effective interpretability and safety research.
need more consideration. Also have the secondary/tertiary effects of limiting the dictum of certain firms