Backfill checkpoint aliases for Kimi-K2.7-Code and the Gemma-4 MoE releases

CHANGELOG.rst

@@ -13,6 +13,7 @@ Changelog
 
 *Quantization*
 
+- Backfill checkpoint aliases for three more published NVFP4 releases: ``moonshotai/Kimi-K2.7-Code``, ``google/gemma-4-26B-A4B-it`` and ``google/diffusiongemma-26B-A4B-it``. Each imports an existing general recipe wholesale rather than copying its body.
 - Backfill checkpoint aliases for nine more published NVFP4 releases, so each is reachable from its source model's hub path: ``zai-org/GLM-5.1`` and ``GLM-5.2``, ``MiniMaxAI/MiniMax-M2.5`` and ``MiniMax-M3``, ``deepseek-ai/DeepSeek-V3.1`` and ``DeepSeek-V3.2``, ``Qwen/Qwen3-235B-A22B-Instruct-2507`` and ``-Thinking-2507``, and ``Qwen/Qwen3.6-27B``. Each imports an existing general or architecture recipe wholesale rather than copying its body.
 - Add composed Hugging Face AutoQuantize recipes that run fixed PTQ or weight AutoQuantize before
   a separate KV-cache AutoQuantize stage, with independent resumable checkpoints for the weight and

modelopt_recipes/models/Qwen/Qwen3.8-27B/ptq/nvfp4_w4a4_mlp_fp8_attn_local_hessian.yaml

@@ -20,7 +20,7 @@ imports:
 metadata:
   description: >-
     Qwen3.8-27B local-Hessian PTQ using the NVFP4 W4A4 and FP8 W8A8 assignment exported by
-    the 5.5-bit NVFP4-max AutoQuantize sweep.
+    the 5.5-bit NVFP4-max AutoQuantize sweep, as published in nvidia/Qwen3.8-27B-NVFP4.
 
 quantize:
   $import: base

modelopt_recipes/models/google/diffusiongemma-26B-A4B-it/ptq/nvfp4_experts_only-kv_fp8_cast.yaml

@@ -0,0 +1,30 @@
+# 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.
+
+# Alias recipe for nvidia/diffusiongemma-26B-A4B-it-NVFP4 (source google/diffusiongemma-26B-A4B-it). Same recipe as `general/ptq/nvfp4_experts_only-kv_fp8_cast`: NVFP4 on the routed experts
+# only, max calibration, with an FP8 KV cache in cast mode -- the same scheme as the
+# gemma-4-26B-A4B-it release. This model nests its decoder under `model.decoder.layers`
+# rather than `model.language_model.layers`, which the recipe's `*.experts.*` patterns
+# match either way.
+
+imports:
+  base: general/ptq/nvfp4_experts_only-kv_fp8_cast
+
+$import: base
+metadata:
+  description: >-
+    google/diffusiongemma-26B-A4B-it quantized with the general expert-only NVFP4 scheme
+    (max calibration) and an FP8 KV cache in cast mode, as published in
+    nvidia/diffusiongemma-26B-A4B-it-NVFP4.

modelopt_recipes/models/google/gemma-4-26B-A4B-it/ptq/nvfp4_experts_only-kv_fp8_cast.yaml

@@ -0,0 +1,28 @@
+# 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.
+
+# Alias recipe for nvidia/Gemma-4-26B-A4B-NVFP4 (source google/gemma-4-26B-A4B-it). Same recipe as `general/ptq/nvfp4_experts_only-kv_fp8_cast`: NVFP4 on the routed experts
+# only, max calibration, with an FP8 KV cache in cast mode. The dense MLPs, router,
+# attention, vision tower and `lm_head` stay BF16.
+
+imports:
+  base: general/ptq/nvfp4_experts_only-kv_fp8_cast
+
+$import: base
+metadata:
+  description: >-
+    google/gemma-4-26B-A4B-it quantized with the general expert-only NVFP4 scheme (max
+    calibration) and an FP8 KV cache in cast mode, as published in
+    nvidia/Gemma-4-26B-A4B-NVFP4.

modelopt_recipes/models/moonshotai/Kimi-K2.7-Code/ptq/nvfp4_experts_only_input_scale1-kv_fp8_cast.yaml

@@ -0,0 +1,30 @@
+# 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.
+
+# Alias recipe for nvidia/Kimi-K2.7-Code-NVFP4 (source moonshotai/Kimi-K2.7-Code). Same recipe as
+# `general/ptq/nvfp4_experts_only_input_scale1-kv_fp8_cast`: NVFP4 on the routed experts
+# with the expert `input_scale` pinned to 1.0 -- no activation calibration -- and an FP8 KV
+# cache in cast mode. The release's exported expert `input_scale` tensors are exactly 1.0,
+# and its shared experts, attention, `lm_head` and vision tower are all left unquantized.
+
+imports:
+  base: general/ptq/nvfp4_experts_only_input_scale1-kv_fp8_cast
+
+$import: base
+metadata:
+  description: >-
+    moonshotai/Kimi-K2.7-Code quantized with the general expert-only NVFP4 scheme, expert
+    `input_scale` pinned to 1.0 (calibration-free), and an FP8 KV cache in cast mode, as
+    published in nvidia/Kimi-K2.7-Code-NVFP4.

modelopt_recipes/ptq.md

@@ -553,6 +553,15 @@ entry is a thin **alias** that imports that recipe wholesale and overrides only
   `model_type/qwen3_5_moe/ptq/nvfp4_experts_mse-fp8_rest-kv_fp8` — NVFP4 (MSE static weights)
   on the routed experts, ModelOpt-default FP8 elsewhere, and an FP8 KV cache — as published in
   `nvidia/Qwen3.5-397B-A17B-NVFP4-V2`.
+- **`models/moonshotai/Kimi-K2.7-Code/ptq/nvfp4_experts_only_input_scale1-kv_fp8_cast`**
+  aliases `general/ptq/nvfp4_experts_only_input_scale1-kv_fp8_cast` — expert-only NVFP4 with
+  the expert `input_scale` pinned to 1.0 (no activation calibration) and an FP8 KV cache in
+  cast mode — as published in `nvidia/Kimi-K2.7-Code-NVFP4`.
+- **`models/google/gemma-4-26B-A4B-it/ptq/nvfp4_experts_only-kv_fp8_cast`** and
+  **`models/google/diffusiongemma-26B-A4B-it/ptq/...`** alias
+  `general/ptq/nvfp4_experts_only-kv_fp8_cast` — expert-only NVFP4 with max calibration and an
+  FP8 KV cache in cast mode — as published in `nvidia/Gemma-4-26B-A4B-NVFP4` and
+  `nvidia/diffusiongemma-26B-A4B-it-NVFP4`.
 - **`models/zai-org/GLM-5.1/ptq/nvfp4_experts_only_input_scale1-kv_fp8_cast`** and
   **`models/zai-org/GLM-5.2/ptq/...`** alias
   `general/ptq/nvfp4_experts_only_input_scale1-kv_fp8_cast` — expert-only NVFP4 with the