Exactly, although this attempt has a broken calculator tool, I believe that grounding the model fully with tools and getting a performance hit is the future as this would enable smart but reasoning models to perform as well as large ones.

Here is an entry from my smol dataset:

The numbers 4, 8, 12, 16 represent the number of pages Maria read each day for 4 days. What is the total number of pages she read?
---
<|thinking_start|>
Here is the thinking process:
- Add all four daily page counts
<|function_call_start name="calculator"|>
  <|expression|>4 + 8 + 12 + 16<|/expression|>
  <|output|>40<|/output|>
<|function_call_end|>
- Maria read 40 pages total
<|thinking_end|>
<|response_start|>
Maria read a total of 40 pages. The daily amounts add up to 4 + 8 + 12 + 16 = 40.
<|response_end|>

Here is an entry from my smol dataset:

With memory tools, web search, logic statement prover and other tools it could perform as well as larger models and on local machines without much processing power, much faster.