The Ledger
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Moe: Open-weight inference can hit 500 tokens/sec, 2-3x faster than proprietary APIs
“But for open weight, when you are running it, every provider can offer potentially even 10 different levels of speed going from like the slowest mode, which can be a lot cheaper to 400 tokens per second almost up to 500 in many cases for some workloads. And th…”
Moe: Most AI API services use open-source inference engines under the hood
“And this is where kind of, this is why open source inference is the current leading way right now instead of closed source inference engine. And frankly, right. All the, a lot of the open, a lot of the open, sorry. A lot of the influence cloud and API as a ser…”
Simon Moe: Users will default to open-weight AI for trusted use cases
“In the future, we'll also see for the trusted use case, people will go to open way by default because that is where you know for sure that the guardrail is lessened or you can control your guardrail for trusted use cases.”
Moe: Kimi K3 costs less than Claude or GPT but exceeds smaller open models
“Where Kimi K-Stri is not as expensive as Claude or GPT Sol, but it is a lot more expensive than JLN-F.”
Simon Moe: BERT was the first model requiring GPUs for efficient inference
“Probably BERT. And before that, it was like ResNet for computation, like images, computer vision classification. So ResNet already need to run on NVIDIA K-eighty, which is kind of one of the first SEU on AWS and other places. And, but way over, but even at thi…”
Simon Mo: vLLM supports over 1,000 model architectures
“For VRM, we support more than a thousand model architecture up to today, and a lot of those are proprietary, but also a lot of those are open-weight, right?”
Mo: Major chipmakers use vLLM as an internal benchmark
“And additionally, VLM also work closely with all the hardware vendors. So that means across like NVIDIA, AMD, Google, and Amazon, Intel, and a lot more, their newest chip will make sure VLM can run on them. And then a lot of cases they use VLM as a benchmark t…”