Add Gemma 4 12B LTX 2.5 NVFP4 text encoder

Adds the missing NVFP4 Gemma-4 12B text encoder with LTX video/audio projections, exact DDB build policy, structural/deep analysis, hashes, and an RTX 4090 ComfyUI LTX 2.5 runtime smoke report.

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+text_encoders/gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors.ddb-qanalyse/analysis.json filter=lfs diff=lfs merge=lfs -text

MODIFICATIONS.md

@@ -8,7 +8,8 @@ Changes made by DmitryDB / DDB:
 
 - converted Dev and Distilled transformer tensors to three mixed-precision
   ComfyUI profiles: `int8`, `int8_lean_convrot`, and `nvfp4`;
-- converted the Gemma-4 LTX text encoder to two INT8 profiles;
+- converted the Gemma-4 LTX text encoder to `int8`,
+  `int8_lean_convrot`, and `nvfp4` profiles;
 - converted the rank-450 Distilled LoRA to three DDB descriptor-based profiles;
 - retained selected sensitive tensors in BF16 according to deterministic
   architecture-aware policies generated from the BF16 source inventory;

README.md

@@ -28,12 +28,13 @@ experimental quantized Distilled LoRA.
 
 These are community conversions, not official Lightricks or ComfyOrg releases.
 
-> **Pre-release validation boundary:** all 11 artifacts passed structural and
+> **Pre-release validation boundary:** all 12 artifacts passed structural and
 > deep DDB-qanalyse validation. The three transformer formats were recognized
-> by ComfyUI on a physical RTX 4090, and the quantized-LoRA runtime passed a real
-> GPU tensor-dequantization smoke. Equal-seed prompt-to-decoded-video and audio
-> quality A/B tests are still pending, so no perceptual-quality ranking is
-> claimed yet.
+> by ComfyUI on a physical RTX 4090, the NVFP4 Gemma-4/LTX text encoder passed
+> a real tokenize + forward + dual-projection smoke, and the quantized-LoRA
+> runtime passed a real GPU tensor-dequantization smoke. Equal-seed
+> prompt-to-decoded-video and audio quality A/B tests are still pending, so no
+> perceptual-quality ranking is claimed yet.
 
 ## Naming
 
@@ -43,8 +44,9 @@ These are community conversions, not official Lightricks or ComfyOrg releases.
   matrices and eight text-encoder matrices remain BF16.
 - `int8_lean_convrot` is the standard DDB lean ConvRot profile and leaves more
   room for the rest of the workflow.
-- `nvfp4` is the smallest transformer profile. It loads through the supported
-  RTX 4090/Ada fallback path; native NVFP4 acceleration is a Blackwell path.
+- `nvfp4` is the smallest transformer and text-encoder profile. It loads
+  through the supported RTX 4090/Ada fallback path; native NVFP4 acceleration
+  is a Blackwell path.
 - Quantized LoRAs use a DDB descriptor/runtime. Stock ComfyUI LoRA loading is
   **not** claimed for those three files.
 
@@ -57,7 +59,7 @@ download only the route you intend to use.
 |---|---:|---:|---:|---:|---|
 | **int8** | [20.152 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-dev-transformer-int8.safetensors?download=true) | [20.152 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-distilled-transformer-int8.safetensors?download=true) | [14.440 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-int8.safetensors?download=true) | [4.715 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/loras/ltx-2.5-22b-distilled-lora-450-int8.safetensors?download=true) | Highest precision-retention policy; use ComfyUI offload on a 24 GiB GPU. |
 | **int8_lean_convrot** | [20.027 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-dev-transformer-int8_lean_convrot.safetensors?download=true) | [20.027 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-distilled-transformer-int8_lean_convrot.safetensors?download=true) | [14.317 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-int8_lean_convrot.safetensors?download=true) | [4.216 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/loras/ltx-2.5-22b-distilled-lora-450-int8_lean_convrot.safetensors?download=true) | Standard 24 GiB DDB ConvRot route with offload. |
-| **nvfp4** | [12.641 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-dev-transformer-nvfp4.safetensors?download=true) | [12.641 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-distilled-transformer-nvfp4.safetensors?download=true) | use [lean TE](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-int8_lean_convrot.safetensors?download=true) | [2.482 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/loras/ltx-2.5-22b-distilled-lora-450-nvfp4.safetensors?download=true) | Smallest transformer; supported fallback on RTX 4090 and native acceleration on supported Blackwell hardware. |
+| **nvfp4** | [12.641 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-dev-transformer-nvfp4.safetensors?download=true) | [12.641 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/diffusion_models/ltx-2.5-22b-distilled-transformer-nvfp4.safetensors?download=true) | [10.428 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors?download=true) | [2.482 GiB](https://huggingface.co/DmitryDB/LTX-2.5-ComfyUI-Quants/resolve/main/loras/ltx-2.5-22b-distilled-lora-450-nvfp4.safetensors?download=true) | Smallest complete DDB route; supported fallback on RTX 4090 and native acceleration on supported Blackwell hardware. |
 
 File size is not complete-workflow peak VRAM. Resolution, frame count, audio,
 attention backend, text encoder, VAEs, latent upscalers, and ComfyUI offload
@@ -73,6 +75,7 @@ not yet been measured.
 | Transformer `nvfp4` | 1,425 | 15 | 8,624 tensors, PASS |
 | Gemma-4 TE `int8` | 320 | 8 | 1,326 tensors, PASS |
 | Gemma-4 TE `int8_lean_convrot` | 328 | 0 | 1,342 tensors, PASS |
+| Gemma-4 TE `nvfp4` | 310 | 18 | 1,616 tensors, PASS |
 | Distilled LoRA `int8` | 1,200 pairs | 460 pairs | 6,920 tensors, PASS |
 | Distilled LoRA `int8_lean_convrot` | 1,360 pairs | 300 pairs | 7,400 tensors, PASS |
 | Distilled LoRA `nvfp4` | 1,360 pairs | 300 pairs | 10,120 tensors, PASS |
@@ -93,6 +96,7 @@ not header-only fixtures:
 | Dev `int8` transformer recognition and quantized projection | RTX 4090, ComfyUI embedded Python | PASS (`int8_tensorwise`) |
 | Dev `int8_lean_convrot` transformer recognition and quantized projection | RTX 4090, ComfyUI embedded Python | PASS (`int8_tensorwise`) |
 | Dev `nvfp4` transformer recognition and quantized projection | RTX 4090, ComfyUI embedded Python | PASS (`nvfp4`) |
+| Gemma-4 `nvfp4` tokenize, text forward, and LTX video/audio projections | RTX 4090, Torch 2.13/cu130, ComfyUI `ltx25` branch | PASS (`LTXAVTEModel_`, `[1,25,6144]`, finite; 12.813 GB peak allocation) |
 | NVFP4 LoRA descriptor decode and finite tensor smoke | RTX 4090, DDB experimental LoRA runtime | PASS |
 | Complete equal-seed video/audio quality comparison | — | **PENDING** |
 
@@ -130,7 +134,7 @@ in `ltx-pipelines` is not claimed.
   the official 8-step / CFG 1 workflow.
 - **Most retained source precision:** `int8`.
 - **Balanced DDB 24 GiB route:** `int8_lean_convrot`.
-- **Smallest transformer:** `nvfp4` + lean TE.
+- **Smallest complete DDB route:** `nvfp4` transformer + `nvfp4` TE.
 - **Distilled LoRA experiments:** matching LoRA profile plus the compatible DDB
   quantized-LoRA runtime; do not load it with an ordinary stock LoRA loader.
 

SHA256SUMS

@@ -9,3 +9,4 @@ c9c8be9a1f48d53d8d3a7255a967ba335130ef5b7c0b15e69694866303a2b27c  loras/ltx-2.5-
 cac5b88fe23d7068c73e67c59a5108c6405d0ba3d4156910c5cba234da2adf7a  loras/ltx-2.5-22b-distilled-lora-450-nvfp4.safetensors
 5b3717c41ea2ee0a7cfeb977969f805e6d57b8b0fe82ee111c0b354dbb3d532f  text_encoders/gemma4-12b-with-proj-ltx-2.5-int8.safetensors
 03e26176210a69610255b0ffb42f0c2e13af8512d92e67d100b34e142e3fdca3  text_encoders/gemma4-12b-with-proj-ltx-2.5-int8_lean_convrot.safetensors
+63a34c47ec4ec1972faf289e9e2d58845f0b6ffb96d564761386d2c2887bf6d1  text_encoders/gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors

build_reports/gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors.build-report.json

@@ -0,0 +1 @@
+{"artifact_validation":{"expected_tensor_count":1616,"mismatch_count":0,"mismatches":[],"observed_tensor_count":1616,"profile":"nvfp4","promoted_bf16_matrix_count":18,"quantized_matrix_count":310,"schema_version":1,"status":"PASS"},"command":["F:\\AI\\ComfyUI_windows_portable\\python_embeded\\Scripts\\convert-to-quant.exe","--input","F:\\AI\\hf_originals\\Diffusion\\Lightricks__LTX-2.5\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-bf16.safetensors","--output","F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\release-staging\\text_encoders\\.gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors.ltx25-text-encoder-gemma4-12b-ltx-v1-nvfp4.partial","--comfy-quant","--simple","--device","cuda","--save-quant-metadata","--low-memory","--verbose","NORMAL","--manual-seed","20260812","--layer-config","F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\layer-config.json","--fullmatch","--nvfp4","--fallback","nvfp4","--fallback-simple"],"elapsed_seconds":153.049,"environment":{"CUDA_VISIBLE_DEVICES":"1","PYTHONNOUSERSITE":"1"},"job_id":"ltx25-text-encoder-gemma4-12b-ltx-v1-nvfp4","layer_config":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\layer-config.json","sha256":"16f823af6ff41e55fc061b1e73f6e5cd32cb6f8cced415f759d21df936c0bd6f"},"manual_seed":20260812,"output_bytes":11197310236,"output_path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\release-staging\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors","output_sha256":"63a34c47ec4ec1972faf289e9e2d58845f0b6ffb96d564761386d2c2887bf6d1","physical_gpu_index":1,"policy":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\policy.json","sha256":"a4f4aaf69ac2a9fcb30c36907796e97586dcac431dd141edae435d578ec02c1d"},"profile":"nvfp4","schema_version":1,"source":{"bytes":26263860594,"path":"F:\\AI\\hf_originals\\Diffusion\\Lightricks__LTX-2.5\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-bf16.safetensors","sha256":"1c647a94c0e902fb87f9a403cbca36a8b6d8e5867094442df1b41ae557cfd1c6"},"status":"PASS","tool":{"path":"F:\\AI\\ComfyUI_windows_portable\\python_embeded\\Scripts\\convert-to-quant.exe","sha256":"b929e7d387d0baf6753c8171f482285e49649201bc7085ebfa3ac12773d350f3"}}

journals/gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors.journal.json

@@ -0,0 +1 @@
+{"artifact_validation":{"expected_tensor_count":1616,"mismatch_count":0,"mismatches":[],"observed_tensor_count":1616,"profile":"nvfp4","promoted_bf16_matrix_count":18,"quantized_matrix_count":310,"schema_version":1,"status":"PASS"},"command":["F:\\AI\\ComfyUI_windows_portable\\python_embeded\\Scripts\\convert-to-quant.exe","--input","F:\\AI\\hf_originals\\Diffusion\\Lightricks__LTX-2.5\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-bf16.safetensors","--output","F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\release-staging\\text_encoders\\.gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors.ltx25-text-encoder-gemma4-12b-ltx-v1-nvfp4.partial","--comfy-quant","--simple","--device","cuda","--save-quant-metadata","--low-memory","--verbose","NORMAL","--manual-seed","20260812","--layer-config","F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\layer-config.json","--fullmatch","--nvfp4","--fallback","nvfp4","--fallback-simple"],"elapsed_seconds":153.049,"environment":{"CUDA_VISIBLE_DEVICES":"1","PYTHONNOUSERSITE":"1"},"job_id":"ltx25-text-encoder-gemma4-12b-ltx-v1-nvfp4","layer_config":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\layer-config.json","sha256":"16f823af6ff41e55fc061b1e73f6e5cd32cb6f8cced415f759d21df936c0bd6f"},"manual_seed":20260812,"output_bytes":11197310236,"output_path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\release-staging\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors","output_sha256":"63a34c47ec4ec1972faf289e9e2d58845f0b6ffb96d564761386d2c2887bf6d1","physical_gpu_index":1,"policy":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\policy.json","sha256":"a4f4aaf69ac2a9fcb30c36907796e97586dcac431dd141edae435d578ec02c1d"},"profile":"nvfp4","schema_version":1,"source":{"bytes":26263860594,"path":"F:\\AI\\hf_originals\\Diffusion\\Lightricks__LTX-2.5\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-bf16.safetensors","sha256":"1c647a94c0e902fb87f9a403cbca36a8b6d8e5867094442df1b41ae557cfd1c6"},"status":"PASS","tool":{"path":"F:\\AI\\ComfyUI_windows_portable\\python_embeded\\Scripts\\convert-to-quant.exe","sha256":"b929e7d387d0baf6753c8171f482285e49649201bc7085ebfa3ac12773d350f3"}}

recipes/jobs/ltx25-text-encoder-gemma4-12b-ltx-v1-nvfp4.job.json

@@ -0,0 +1 @@
+{"job_id":"ltx25-text-encoder-gemma4-12b-ltx-v1-nvfp4","journal":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\release-staging\\journals\\gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors.journal.json"},"layer_config":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\layer-config.json","sha256":"16f823af6ff41e55fc061b1e73f6e5cd32cb6f8cced415f759d21df936c0bd6f"},"manual_seed":20260812,"output":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\release-staging\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors"},"physical_gpu_index":1,"policy":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\policies\\text_encoder\\gemma4-12b-ltx-v1\\nvfp4\\policy.json","sha256":"a4f4aaf69ac2a9fcb30c36907796e97586dcac431dd141edae435d578ec02c1d"},"profile":"nvfp4","report":{"path":"F:\\AI\\Work\\LTX-2.5-ComfyUI-Quants\\release-staging\\build_reports\\gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors.build-report.json"},"schema_version":1,"source":{"bytes":26263860594,"path":"F:\\AI\\hf_originals\\Diffusion\\Lightricks__LTX-2.5\\text_encoders\\gemma4-12b-with-proj-ltx-2.5-bf16.safetensors","sha256":"1c647a94c0e902fb87f9a403cbca36a8b6d8e5867094442df1b41ae557cfd1c6"},"tool":{"path":"F:\\AI\\ComfyUI_windows_portable\\python_embeded\\Scripts\\convert-to-quant.exe","sha256":"b929e7d387d0baf6753c8171f482285e49649201bc7085ebfa3ac12773d350f3"}}

recipes/ltx25_dmitrydb.json

@@ -42,7 +42,7 @@
       "text_encoder_profile": "int8_lean_convrot"
     },
     "nvfp4": {
-      "text_encoder_profile": "int8_lean_convrot"
+      "text_encoder_profile": "nvfp4"
     }
   },
   "files": [
@@ -184,6 +184,11 @@
           "filename": "gemma4-12b-with-proj-ltx-2.5-int8_lean_convrot.safetensors",
           "policy": "text_encoder/gemma4-12b-ltx-v1/int8_lean_convrot",
           "converter_flags": ["--comfy-quant", "--simple", "--save-quant-metadata", "--low-memory", "--layer-config", "--fullmatch", "--int8", "--scaling-mode", "row", "--convrot", "--convrot-group-size", "256"]
+        },
+        "nvfp4": {
+          "filename": "gemma4-12b-with-proj-ltx-2.5-nvfp4.safetensors",
+          "policy": "text_encoder/gemma4-12b-ltx-v1/nvfp4",
+          "converter_flags": ["--comfy-quant", "--simple", "--save-quant-metadata", "--low-memory", "--layer-config", "--fullmatch", "--nvfp4", "--fallback", "nvfp4", "--fallback-simple"]
         }
       }
     },

recipes/policies/text_encoder/gemma4-12b-ltx-v1/nvfp4/layer-config.json

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