Subquadratic has released SubQ Snap 1.1, tying d1-ultra and Elephant 9B for first on the Artificial Analysis Decision Index v1.0, driven by a low hallucination rate

SubQ Snap 1.1 is the new decision model from @subquadratic. It is priced at $0.04 per 1M input tokens and supports a 384K token context window, compared to 32K for d1-ultra and 16K for Elephant 9B.

Key takeaways:
➤ SubQ Snap 1.1 scores 65 on the Artificial Analysis Decision Index v1.0, tied with d1-ultra and Elephant 9B: the three models are 8 points ahead of the next model, Jev 1.14 (57).

➤ SubQ Snap 1.1's AA-Omniscience-Decision result is driven by a low hallucination rate: its non-hallucination rate of 86% is second only to Elephant 9B (93%), ahead of d1-ultra (85%). Its accuracy is 20%, compared to 32% for d1-ultra and 12% for Elephant 9B. The non-hallucination rate is the share of questions not answered correctly where the model chose "I don't know".

➤ SubQ Snap 1.1 scores 18% on HLE-MultiChoice: level with Elephant 9B (18%) and ahead of d1-ultra (15%). HLE-MultiChoice is the text-only multiple-choice subset of Humanity's Last Exam.

➤ SubQ Snap 1.1 costs $30 per 1M tasks: comparable to d1-ultra ($32), and ~3.6x the cost of Elephant 9B ($8.4), which scores the same 65.