Turbo4 CUDA Data — buun (@spiritbuun, RTX 3090)
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Source: X post 2026-03-28 09:50 AM
Model: Qwen3.5-27B, wikitext-2-raw

Quality (PPL):
  Context | q8_0   | turbo3 | turbo4 | turbo3 vs q8_0 | turbo4 vs q8_0
  2K      | 5.8375 | 5.8323 | 5.8186 | -0.09%         | -0.28%
  32K     | 7.2592 | 7.2139 | 7.2478 | -0.62%         | -0.16%
  64K     | 6.4804 | 6.5122 | 6.7192 | +0.49%         | +3.69%

Key finding: turbo4 wins at 2K (+0.19% vs turbo3) but LOSES at 64K (+3.08% vs turbo3)
QJL noise accumulates with context length.

Speed:
  Metric          | q8_0  | turbo3 | turbo4
  Decode (tok/s)  | 31.25 | 30.31  | 29.43
  Decode vs q8_0  | —     | 97.0%  | 94.2%
  Prefill (tok/s) | 1133  | 1125   | 588
  Prefill vs q8_0 | —     | 99.3%  | 51.9%

turbo4 prefill is 51.9% of q8_0 — catastrophically slow.
turbo3 prefill is 99.3% — near parity.

buun's conclusion: "turbo3 is better in every way. Do not bother using turbo4."

Recommended configs (buun):
  Quality (hd256):           -ctk turbo3 -ctv turbo3 (LA-1)
  Quality (hd128, <8K ctx):  -ctk turbo3 -ctv turbo4
  Quality (hd128, >8K ctx):  -ctk turbo3 -ctv turbo3
  Max VRAM savings:          -ctk turbo3 -ctv turbo2
  Long context (32K-128K):   -ctk turbo3 -ctv turbo3 (uniform)

Our Metal findings align:
  turbo4 WITH QJL:    6.1894 PPL (+0.22% worse than turbo3)
  turbo4 WITHOUT QJL: 6.1756 PPL (identical to turbo3)
  QJL hurts on both CUDA and Metal.

@jackdaniel2025 independently confirmed: "turbo4 is not worth using"
@skinbagwbones interested in collaboration on weight+KV compression stacking
