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Original file line number Diff line number Diff line change
Expand Up @@ -38,10 +38,6 @@
enable: false
- quantizer_name: '*router*'
enable: false
- quantizer_name: '*visual*'

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are we quantizing these modules?

@juhi10071998 juhi10071998 Jun 16, 2026

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they are excluded in 53-56 lines below-

  - quantizer_name: '*vision_tower*'
    enable: false
  - quantizer_name: '*visual*'
    enable: false

@Edwardf0t1 can confirm if this was intended though.

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@cjluo-nv Yes, removing this line is intended since it's excluded as @juhi10071998 mentioned.

enable: false
- quantizer_name: '*vision_tower*'
enable: false
- quantizer_name: 'output.*'
enable: false
# Multimodal vision branch: keep the vision encoder (SigLIP / ViT) and any
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19 changes: 19 additions & 0 deletions modelopt_recipes/huggingface/gemma4/ptq/README.md
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# Gemma 4 PTQ recipes

Recipes for the **`gemma4`** model type (multimodal, e.g.
[`google/gemma-4-31B-it`](https://huggingface.co/google/gemma-4-31B-it)). This is
a distinct architecture from the text-only `gemma` model type — see
[`../../gemma/ptq/`](../../gemma/ptq/) for that one. These recipes override the
algorithm defaults that ship in the general PTQ presets because Gemma needs
different settings to converge / stay accurate.

| Recipe | What's model-specific |
|--------|-----------------------|
| `w4a8_awq-kv_fp8_cast.yaml` | Uses `awq_lite` with `alpha_step: 1` instead of the default AWQ search (the default search overflows in TRT-LLM kernels on Gemma; the coarser sweep avoids it without measurably hurting accuracy). Numerics: INT4 block weights + FP8 inputs + FP8 KV-cache cast (constant amax, no KV calibration). |

The base numerics units and the standard disabled-quantizer list are inherited
from the shared `configs/`; only the algorithm fields are model-specific. The
multimodal vision branch (`*vision_tower*` / `*visual*` / `*embed_vision*`) is
kept in BF16 by the shared `default_disabled_quantizers` unit — quantizing it to
INT4 crashes export (`pack_int4_in_uint8` index-out-of-bounds, NVBug 6294017) and
is accuracy-harmful.
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# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# Gemma 4 (model_type=gemma4, e.g. gemma-4-31B-it) W4A8 AWQ PTQ recipe with FP8
# KV-cache cast. gemma4 is a distinct, multimodal architecture from the text-only
# `gemma` model type (see ../../gemma/ptq/). Uses a coarser optimal-scale search
# (awq_lite with alpha_step=1) to avoid the overflow observed in TRT-LLM kernels
# when using the default AWQ search on Gemma.
#
# The bare `*weight_quantizer` / `*input_quantizer` enables below would also match
# the SigLIP vision tower (`model.vision_tower.*`) and the multimodal embedding
# projection (`model.embed_vision.*`). The vision tower's MLP in-features (4304)
# are not a multiple of the INT4 block size (128), so INT4-packing them at export
# hits a device-side "index out of bounds" assert in pack_int4_in_uint8 (NVBug
# 6294017); it is also accuracy-harmful to W4A8 the vision branch. The vision
# branch is kept in BF16 by the shared `default_disabled_quantizers` unit imported
# below, which globally disables `*vision_tower*` / `*visual*` / `*embed_vision*`.

imports:
base_disable_all: configs/ptq/units/base_disable_all
default_disabled_quantizers: configs/ptq/units/default_disabled_quantizers
fp8: configs/numerics/fp8
int4_per_block: configs/numerics/int4_per_block
kv_fp8_cast: configs/ptq/units/kv_fp8_cast

metadata:
recipe_type: ptq
description: >-
Gemma 4 (multimodal) W4A8 AWQ recipe with FP8 KV-cache cast: INT4 block
weights + FP8 inputs, awq_lite with alpha_step=1 (coarser search) to avoid
TRT-LLM overflow, plus FP8 KV-cache using constant amax (no KV calibration).
The SigLIP vision tower and vision embedding projection are kept in BF16.
quantize:
algorithm:
method: awq_lite
alpha_step: 1
quant_cfg:
- $import: base_disable_all
- quantizer_name: '*weight_quantizer'
cfg:
- $import: int4_per_block
- $import: fp8
- quantizer_name: '*input_quantizer'
cfg:
$import: fp8
- $import: kv_fp8_cast
# default_disabled_quantizers (imported last so its disables win) keeps the
# multimodal vision branch — `*vision_tower*` / `*visual*` / `*embed_vision*` —
# in BF16, preventing the INT4 pack_int4_in_uint8 crash (NVBug 6294017).
- $import: default_disabled_quantizers
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