[diffusion] feat: support loading self-describing quanto int8 encoders (#36052)

This commit is contained in:
Mick
2026-08-24 16:37:09 +08:00
committed by GitHub
parent 5081ad5d4e
commit adc09a1f63
13 changed files with 536 additions and 43 deletions
@@ -200,6 +200,14 @@ backend.
<td><code>comfy-kitchen&gt;=0.2.27</code></td>
<td>Auto-detected; omit <code>--quantization</code>. Requires SM80+ and validates packed weights, group/channel scales, and optional codebooks before model construction. Mixed encoder files may keep their embedding tensorwise INT8. TP must preserve ConvRot group boundaries; offload is supported and FSDP is not.</td>
</tr>
<tr>
<td><code>quanto-int8</code></td>
<td>One native encoder safetensors file with an embedded Quanto quantization map</td>
<td>An explicit weight file through <code>--component-paths.&lt;component&gt;</code></td>
<td>Native encoders whose mapped linear layers consume every declared qint8 entry; MiniMax-H3's Qwen3-VL encoder is supported</td>
<td>None</td>
<td>Auto-detected weight-only qint8 storage. Each active matrix is dequantized to the compute dtype for the ordinary linear operation, so this reduces stored/resident weight memory rather than promising INT8 GEMM speed. TP and offload are supported; FSDP is not.</td>
</tr>
<tr>
<td><code>qvg-kv</code></td>
<td>Unquantized model with runtime causal KV-cache compression</td>