Subquadratic releases the SubQ Snap 1.1 decision model
Subquadratic releases the decision model SubQ Snap 1.1, which scores 65 on the Artificial Analysis Decision Index v1.0, tying for first place with d1-ultra and Elephant 9B and leading the third-place Jev 1.14 (57) by 8 points. Its non-hallucination rate is 86%, second only to Elephant 9B's 93% and higher than d1-ultra's 85%; its accuracy is 20%, and it scores 18% on HLE-MultiChoice. Input pricing is $0.04/1M tokens, the context window is 384K, and the cost per 1M tasks is $30, about 3.6 times that of the equally scoring Elephant 9B ($8.4).
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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.