DeepSeek-V4

On Terminal-Bench 2.1, Laguna S 2.1 scores 70.2%, ahead of DeepSeek-V4-Pro-Max's 64% at roughly a fourteenth of the parameter count. Poolside built it in under nine weeks and prices it at 10 cents per million input tokens on OpenRouter, weights open in BF16, FP8, INT4, and GGUF.

The catch surfaced on Hacker News fast: several deployment recipes ship with "thinking" switched off by default, and without it the numbers don't reproduce locally — one tester said the model looked mediocre until he forced the flag on himself.

DeepSeek dropped a paper on DSpark, a speculative-decoding module bolted onto its V4 models, claiming 57–78% faster per-user generation at the same hardware capacity — and shipped the weights to Hugging Face the same day.

The thread's sharpest voice wasn't about the math. It was the warning that token-sellers eyeing an IPO have a market that's 'almost solely developers', open models a step behind, and no customer boasting higher profits from AI. Also noted: the headline isn't even the paper's title, and speculative decoding dates to 2022.