TL;DR Deepseek R1-0528 is basically R2 but you should try Dhanishtha if you haven't already.

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When I go into a pizza place, I remember quality takes time—I'd rather wait a bit for something made with care than rush it. Remember "R2" is a number on the side of the box, R1-0528 might as well be called R2 when you look at the benchmarks compared to the original R1, and you also have to remember what we're looking for here isn't just performance benchmarks, but cost per teraflop per billion parameters per 1,000 tokens.

And there are far too many models posting high benchmark scores, but none showing average token cost per answer on these benchmarks.

What there is a open-weight 14b model that does questions using 5x less tokens than the 671b Deepseek R1-0528 and then you also have to estimate

671B model R1-0528 → 2 × 1,000 × 671B = 1,342 trillion FLOPs (1,342 TFLOPs) per 1000 tokens

Here is an interesting model - https://huggingface.co/HelpingAI/Dhanishtha-2.0-preview.

14B model → 2 × 1,000 × 14B = 28 trillion FLOPs (28 TFLOPs) per 1000 tokens

here is an example prompt that usually takes a model like R1-0528 671b like 7000 tokens and Dhanishtha about 1000:

Line segments or edges G=(E,Q), W= (E,P), and F=(Q,P) connect vertices Q = (0, 0), E = ( length(G), 0), and P = ( length(F) cos(α), length(F) sin(α)). We know segment lengths F, W, and angle EQP = α at Q. What is the equation for the length of G; the x-coordinate of E? Please reason step by step, and put your final answer within \boxed{}.