cards: document unrestricted reasoning/output budget defaults

README.md

@@ -124,6 +124,8 @@ the next section, and measure before you rely on it.
 
 Sampling: `temperature 0.6`, `top_p 0.95`, `top_k 20`, `min_p 0` for agentic coding. For cybersecurity/CTF work, swap to `top_k 40`, `min_p 0.05` (same temperature and top_p), tested on the GGUF Q4 build. This is a looser configuration leading to more divergent and exploratory thinking, which leads to more solutions on Q4 but might create issues and non-convergence on lower quants.
 
+Budget: `mlx_vlm` has no unlimited default and requires an explicit `--max-tokens`; the `512` in the examples is sized for a one-shot demo prompt, not for real work. Give real work a generous ceiling — `32768` if you cap it at all. A low token budget degrades overall performance and will not necessarily make the model converge on the correct answer any faster. This model is much better than other 35B-A3B builds at spending fewer tokens and less time in total over the course of a problem — it knows when it needs to cook and when it is done — which makes high budgets, or no budget at all, both the safer and the better setting.
+
 **Prefer to keep the files yourself?**
 
 ```bash