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gqadict
confirmedshipPython · PyTorchModel behavior & reasoningJuly 22, 2026
the question
Does sharing one value matrix across a grouped-query head group lower the group's realized output rank relative to full multi-head attention?
what came out
Sharing V shrinks the group's value dictionary by exactly G (16=d_v vs 128=G*d_v at G=8), yet the concatenated output rank stays min(N, G*d_v)=128, equal to full MHA, because each head keeps an independent pattern and output projection. The cap bites only if the attention patterns are tied, collapsing rank to d_v=16.
method & receipts
- Result: confirmed
- Tested — a correctness/benchmark suite ships alongside the code.
→ read the code and re-run it
github.com/v-code01/gqadict