Offers an 8B diffusion LM that allocates compute per tokenThe chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.Full definition → and decodes in parallel, with reported accuracy and throughput trade-offs on a B200. Useful for evaluating non-autoregressive inferenceRunning a trained model to get answers — the phase where AI is actually used, as opposed to trained.Full definition →, though the CC-BY-NC license blocks commercial deployment.
Terms in this piece · Glossary
LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.
inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
