… The company also noted speed improvements with the GB300 NVL72 v6.0 over v5.1, ranging from 1.21 times in the Llama 3.1 405B offline benchmark to 2.77 times for DeepSeek-R1 server test. “In just the past six months, we have been able to nearly triple our performance on DeepSeek-R1, which is a very … …
… Here is how the Hopper NVL8, Grace-Blackwell NVL72, and Vera-Rubin NVL72 systems stack up in terms of throughput tokens per second per megawatt and interactivity tokens per second per user : It is immediately obvious that the larger shared GPU memory domain enabled by NVSwitch helps stretch the cur… …
… In the long run, the AI model builders will not rent huge amounts of capacity on the cloud. They will make the clouds sell them infrastructure on the cheap that they can amortize, thereby lowering the cost of tokens. …
… Nvidia developers addressed the typical tradeoffs when balancing efficiency and accuracy through architectural changes, including using a latent mixture-of-experts that call four times as many specialists for the same inference costs by compressing tokens before they reach the experts and multi-tok… …
… This is true given the current state of AI and the current cost of processing tokens. No one said it would remain true forever. …
… They care what it costs so they can justify the budget, but they are not afraid to pay a premium as long as it is not too much. This is how IBM mainframes and Power Systems machines still generate maybe $25 billion a year in revenues even in 2026. …
… The amount of kilowatts you're consuming and tokens you're generating will become much more efficient.” The myth that AI data centers, because they're liquid cooled, are consuming water, is “not true, you can avoid it and still have that efficient data center.” Though local communities are likely t…
… In any event, in the table above, output speed is expressed in tokens per second, and the time to first token TTFT is expressed in seconds. The two smaller Llama 4 models beat OpenAI’s GPT 4o in terms of smarts by a little bit and cost 21X to 31X less per million tokens processed. …
… The second workload is called decode, and it means instead of chewing on tokens to either understand a query and its context or trying to find the statistical graph of linkages between tokens in a corpus of data, the system is spitting out tokens for the answers to a query in whatever modality the … …
… That last bit is going to have to change, particularly as GenAI goes mainstream and the bargain power that enterprises, governments, academic institutions, and sovereigns is a lot lower than that of the hyperscalers, cloud builders, and model builders. ai sambanova ai inference sn50 nvidia