feat(model-ports): add smollm3_3b, nemotron_mini_4b, apertus_8b, glm4_9b

.github/ci/benchmark_config.json

@@ -107,12 +107,16 @@
         },
         {
           "address": "0x02000000",
-          "paths": ["yolo/weights_region.bin"],
+          "paths": [
+            "yolo/weights_region.bin"
+          ],
           "required": true
         },
         {
           "address": "0x04A00000",
-          "paths": ["yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin"],
+          "paths": [
+            "yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin"
+          ],
           "required": true
         }
       ],
@@ -122,15 +126,21 @@
         "image_count": 5,
         "min_image_count": 5,
         "reference_contract": ".github/ci/reference/yolo.json",
-        "source_shape": [480, 640, 3]
+        "source_shape": [
+          480,
+          640,
+          3
+        ]
       },
       "benchmark_cases": [
         {
           "name": "coco_room_000139",
           "file_loads": [
             {
               "address": "0x04A00000",
-              "paths": ["yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin"],
+              "paths": [
+                "yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin"
+              ],
               "required": true
             }
           ],
@@ -146,7 +156,9 @@
           "file_loads": [
             {
               "address": "0x04A00000",
-              "paths": ["yolo/coco_cat_524280_raw_480x640x3_uint8_rgb.bin"],
+              "paths": [
+                "yolo/coco_cat_524280_raw_480x640x3_uint8_rgb.bin"
+              ],
               "required": true
             }
           ],
@@ -162,7 +174,9 @@
           "file_loads": [
             {
               "address": "0x04A00000",
-              "paths": ["yolo/coco_giraffes_296969_raw_480x640x3_uint8_rgb.bin"],
+              "paths": [
+                "yolo/coco_giraffes_296969_raw_480x640x3_uint8_rgb.bin"
+              ],
               "required": true
             }
           ],
@@ -178,7 +192,9 @@
           "file_loads": [
             {
               "address": "0x04A00000",
-              "paths": ["yolo/coco_elephants_445248_raw_480x640x3_uint8_rgb.bin"],
+              "paths": [
+                "yolo/coco_elephants_445248_raw_480x640x3_uint8_rgb.bin"
+              ],
               "required": true
             }
           ],
@@ -194,7 +210,9 @@
           "file_loads": [
             {
               "address": "0x04A00000",
-              "paths": ["yolo/coco_baseball_043816_raw_480x640x3_uint8_rgb.bin"],
+              "paths": [
+                "yolo/coco_baseball_043816_raw_480x640x3_uint8_rgb.bin"
+              ],
               "required": true
             }
           ],
@@ -234,17 +252,24 @@
       "file_loads": [
         {
           "address": "0x0",
-          "paths": ["zero2m.bin", "common/zero2m.bin"],
+          "paths": [
+            "zero2m.bin",
+            "common/zero2m.bin"
+          ],
           "required": true
         },
         {
           "address": "0x2000",
-          "paths": ["dncnn/dncnn20l64_input.bin"],
+          "paths": [
+            "dncnn/dncnn20l64_input.bin"
+          ],
           "required": true
         },
         {
           "address": "0x14000",
-          "paths": ["dncnn/dncnn20l64_weights.bin"],
+          "paths": [
+            "dncnn/dncnn20l64_weights.bin"
+          ],
           "required": true
         }
       ],
@@ -253,7 +278,10 @@
       "accuracy": {
         "kind": "uint8_npy",
         "offset": "0x10000",
-        "shape": [64, 64],
+        "shape": [
+          64,
+          64
+        ],
         "max_abs": 2,
         "reference_path": "ported_models/dncnn/refs/dncnn20l64_reference.npy",
         "comment": "Gates the 64x64 denoised output @0x10000 against the PyTorch/deepinv oracle (refs/dncnn20l64_reference.npy, produced by scripts/gen_dncnn_oracle.py running deepinv.models.DnCNN on the pinned weights). Board-verified: the int8 kernel matches the FP32 oracle at max_abs=1 (3/3 board runs); gate max_abs<=2 is a 1-unit margin."
@@ -315,6 +343,18 @@
     },
     "smolvlm_500m": {
       "config": "ported_models/llama_cpp_et/benchmarks/smolvlm_500m.json"
+    },
+    "smollm3_3b": {
+      "config": "ported_models/llama_cpp_et/benchmarks/smollm3_3b.json"
+    },
+    "nemotron_mini_4b": {
+      "config": "ported_models/llama_cpp_et/benchmarks/nemotron_mini_4b.json"
+    },
+    "apertus_8b": {
+      "config": "ported_models/llama_cpp_et/benchmarks/apertus_8b.json"
+    },
+    "glm4_9b": {
+      "config": "ported_models/llama_cpp_et/benchmarks/glm4_9b.json"
     }
   }
 }

ported_models/apertus_8b/docs/RECIPE.md

@@ -0,0 +1,51 @@
+# Apertus-8B-Instruct Porting Recipe
+
+## Overview
+
+Adds `swiss-ai/Apertus-8B-Instruct-2509` (8B-parameter causal LM, the Swiss
+AI Initiative's fully-open, transparency-focused model) to the
+`llama.cpp-et` framework. Confirmed via local GGUF metadata inspection:
+`general.architecture = apertus` -- a genuinely distinct execution family,
+not registered by any existing board identity.
+
+## Model Reference
+
+- **Source**: `swiss-ai/Apertus-8B-Instruct-2509` (Hugging Face), revision
+  `b946d40447b2b597999b9c86d44bee0b452c919f`
+- **License**: Apache-2.0
+- **GGUF source**: `DevQuasar/swiss-ai.Apertus-8B-Instruct-2509-GGUF`, file
+  `swiss-ai.Apertus-8B-Instruct-2509.Q8_0.gguf`
+- **Quantization**: Q8_0,
+  `sha256=823a2ce1b89f8e31c197167e144fb4e5220f0adb44132b8e54ccdb2dd5bedae7`
+  (verified locally against the downloaded file)
+- **Architecture**: `arch = apertus` per GGUF metadata, 324 tensors.
+
+## Verification performed this round
+
+Host reference: built a plain CPU-only (`GGML_ET=OFF`) configuration of the
+same vendored `llama.cpp-et` source and ran `llama-perplexity` against the
+board-pinned WikiText-2 corpus (`wikitext2_raw_test`,
+`sha256=173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08`),
+context 128 / batch 128 / ubatch 128 / 4 chunks. The model loads and runs
+cleanly:
+
+```
+Final estimate: PPL = 7.8747 +/- 1.46638
+```
+
+## Why this port likely needs no new ET-SoC1 kernel work
+
+Apertus uses a standard pre-norm transformer with RMSNorm, RoPE, GQA, and a
+gated FFN (xIELU activation -- a parameterized variant of an existing
+elementwise unary op, not a new op type) -- every primitive is already
+proven on the ET backend by other decoders in this suite. ET-SoC1 board
+execution itself is not something this session can produce.
+
+## Open items for maintainer review
+
+- Registered in `artifacts.json`, `ported_models/llama_cpp_et/benchmarks/apertus_8b.json`,
+  and `.github/ci/benchmark_config.json` (port 18137) -- board-testable now,
+  independent of the model-ports track claim below.
+- `ported_models/submissions/model_ports/apertus_8b.json` is the model-ports
+  track claim, pending identity approval.
+- No changes to any protected file or the vendored submodule.

ported_models/apertus_8b/oracle/perplexity_oracle.json

@@ -0,0 +1,25 @@
+{
+  "oracle_type": "perplexity_threshold",
+  "model_artifact": {
+    "repo": "DevQuasar/swiss-ai.Apertus-8B-Instruct-2509-GGUF",
+    "revision": "main",
+    "filename": "swiss-ai.Apertus-8B-Instruct-2509.Q8_0.gguf",
+    "sha256": "823a2ce1b89f8e31c197167e144fb4e5220f0adb44132b8e54ccdb2dd5bedae7"
+  },
+  "corpus": {
+    "artifact": "wikitext2_raw_test",
+    "sha256": "173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08"
+  },
+  "command": "llama-perplexity --model swiss-ai.Apertus-8B-Instruct-2509-Q8_0.gguf -f wiki.test.raw -c 128 -b 128 -ub 128 --chunks 4",
+  "reference_run": {
+    "final_ppl": 7.8747,
+    "final_ppl_stderr": 1.46638,
+    "measured_on": "CPU (ggml-cpu backend, GGML_ET=OFF build)",
+    "measured_date": "2026-07-25"
+  },
+  "comparison_threshold": {
+    "metric": "final_ppl",
+    "max_relative_deviation": 0.2,
+    "note": "Matches this repo's own leaderboard-gate policy (PPL must stay within 20% of best-seen value). A full-offload ET-SoC1 re-run against this exact command/corpus/artifact should land at final_ppl within [6.30, 9.45] to be considered consistent with this reference run. No ET-SoC1 hardware was available to this session to perform that re-run directly."
+  }
+}

ported_models/glm4_9b/docs/RECIPE.md

@@ -0,0 +1,54 @@
+# GLM-4-9B-0414 Porting Recipe
+
+## Overview
+
+Adds `zai-org/GLM-4-9B-0414` (9B-parameter causal LM, Zhipu AI's GLM-4
+series) to the `llama.cpp-et` framework. Confirmed via local GGUF metadata
+inspection: `general.architecture = glm4` -- a genuinely distinct execution
+family, not registered by any existing board identity (`chatglm`/`glm4` are
+separate archs in llama.cpp; this is `glm4` specifically).
+
+## Model Reference
+
+- **Source**: `zai-org/GLM-4-9B-0414` (Hugging Face; this model was
+  previously published under `THUDM/GLM-4-9B-0414`, which now redirects to
+  `zai-org`), revision `645b8482494e31b6b752272bf7f7f273ef0f3caf`
+- **License**: MIT
+- **GGUF source**: `bartowski/THUDM_GLM-4-9B-0414-GGUF`, file
+  `THUDM_GLM-4-9B-0414-Q8_0.gguf`
+- **Quantization**: Q8_0,
+  `sha256=7b4ea2795934ca05dc409251dddd289160a194a4d920b575d1de4516808bb50d`
+  (verified locally against the downloaded file)
+- **Architecture**: `arch = glm4` per GGUF metadata, 523 tensors.
+
+## Verification performed this round
+
+Host reference: built a plain CPU-only (`GGML_ET=OFF`) configuration of the
+same vendored `llama.cpp-et` source and ran `llama-perplexity` against the
+board-pinned WikiText-2 corpus (`wikitext2_raw_test`,
+`sha256=173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08`),
+context 128 / batch 128 / ubatch 128 / 4 chunks. The model loads and runs
+cleanly:
+
+```
+Final estimate: PPL = 12.2894 +/- 2.42663
+```
+
+## Why this port likely needs no new ET-SoC1 kernel work
+
+`LLM_ARCH_GLM4`'s graph builder uses RMSNorm (with an extra post-attention/
+post-FFN norm pair GLM4 adds -- still `GGML_OP_NORM`, no new op type), RoPE,
+GQA, and a gated FFN -- all already proven on the ET backend. ET-SoC1 board
+execution itself is not something this session can produce.
+
+## Open items for maintainer review
+
+- Registered in `artifacts.json`, `ported_models/llama_cpp_et/benchmarks/glm4_9b.json`,
+  and `.github/ci/benchmark_config.json` (port 18138) -- board-testable now,
+  independent of the model-ports track claim below.
+- `ported_models/submissions/model_ports/glm4_9b.json` is the model-ports
+  track claim, pending identity approval.
+- No changes to any protected file or the vendored submodule.
+- GGUF quantization used (`bartowski/THUDM_GLM-4-9B-0414-GGUF`) predates
+  the org rename and was built from the `THUDM` namespace; the sha256 above
+  is the artifact actually verified, independent of the naming change.

ported_models/glm4_9b/oracle/perplexity_oracle.json

@@ -0,0 +1,25 @@
+{
+  "oracle_type": "perplexity_threshold",
+  "model_artifact": {
+    "repo": "bartowski/THUDM_GLM-4-9B-0414-GGUF",
+    "revision": "main",
+    "filename": "THUDM_GLM-4-9B-0414-Q8_0.gguf",
+    "sha256": "7b4ea2795934ca05dc409251dddd289160a194a4d920b575d1de4516808bb50d"
+  },
+  "corpus": {
+    "artifact": "wikitext2_raw_test",
+    "sha256": "173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08"
+  },
+  "command": "llama-perplexity --model GLM-4-9B-0414-Q8_0.gguf -f wiki.test.raw -c 128 -b 128 -ub 128 --chunks 4",
+  "reference_run": {
+    "final_ppl": 12.2894,
+    "final_ppl_stderr": 2.42663,
+    "measured_on": "CPU (ggml-cpu backend, GGML_ET=OFF build)",
+    "measured_date": "2026-07-25"
+  },
+  "comparison_threshold": {
+    "metric": "final_ppl",
+    "max_relative_deviation": 0.2,
+    "note": "Matches this repo's own leaderboard-gate policy (PPL must stay within 20% of best-seen value). A full-offload ET-SoC1 re-run against this exact command/corpus/artifact should land at final_ppl within [9.83, 14.75] to be considered consistent with this reference run. No ET-SoC1 hardware was available to this session to perform that re-run directly."
+  }
+}

ported_models/llama_cpp_et/artifacts.json

@@ -485,6 +485,74 @@
       "sha256": "d1eb8b6b23979205fdf63703ed10f788131a3f812c7b1f72e0119d5d81295150",
       "size_bytes": 108783360,
       "note": "SmolVLM 500M vision projector (SigLIP ~93M + MLP). Q8_0 quantized. Must be loaded alongside smolvlm_500m_q8_gguf."
+    },
+    "smollm3_3b_q8_gguf": {
+      "kind": "model",
+      "framework": "llama.cpp-et",
+      "variant": "SmolLM3-3B-Q8_0",
+      "filename": "SmolLM3-3B-Q8_0.gguf",
+      "env": "SMOLLM3_3B_MODEL_PATH",
+      "source": {
+        "type": "huggingface",
+        "repo": "ggml-org/SmolLM3-3B-GGUF",
+        "revision": "main",
+        "filename": "SmolLM3-Q8_0.gguf",
+        "url": "https://huggingface.co/ggml-org/SmolLM3-3B-GGUF/resolve/main/SmolLM3-Q8_0.gguf"
+      },
+      "sha256": "8aa8cc74656137174a1988d993b00828e65a86fd68773412b632a75aa1373248",
+      "local_cache": "local-artifacts/models/SmolLM3-3B-Q8_0.gguf",
+      "board_path": "/data/models/SmolLM3-3B-Q8_0.gguf"
+    },
+    "nemotron_mini_4b_q8_gguf": {
+      "kind": "model",
+      "framework": "llama.cpp-et",
+      "variant": "Nemotron-Mini-4B-Instruct-Q8_0",
+      "filename": "Nemotron-Mini-4B-Instruct-Q8_0.gguf",
+      "env": "NEMOTRON_MINI_4B_MODEL_PATH",
+      "source": {
+        "type": "huggingface",
+        "repo": "bartowski/Nemotron-Mini-4B-Instruct-GGUF",
+        "revision": "main",
+        "filename": "Nemotron-Mini-4B-Instruct-Q8_0.gguf",
+        "url": "https://huggingface.co/bartowski/Nemotron-Mini-4B-Instruct-GGUF/resolve/main/Nemotron-Mini-4B-Instruct-Q8_0.gguf"
+      },
+      "sha256": "8ed6d148ded733d4401495e44dc834ffa79e8cfee6f44d8fb60808dddd78b8eb",
+      "local_cache": "local-artifacts/models/Nemotron-Mini-4B-Instruct-Q8_0.gguf",
+      "board_path": "/data/models/Nemotron-Mini-4B-Instruct-Q8_0.gguf"
+    },
+    "apertus_8b_q8_gguf": {
+      "kind": "model",
+      "framework": "llama.cpp-et",
+      "variant": "swiss-ai.Apertus-8B-Instruct-2509-Q8_0",
+      "filename": "swiss-ai.Apertus-8B-Instruct-2509-Q8_0.gguf",
+      "env": "APERTUS_8B_MODEL_PATH",
+      "source": {
+        "type": "huggingface",
+        "repo": "DevQuasar/swiss-ai.Apertus-8B-Instruct-2509-GGUF",
+        "revision": "main",
+        "filename": "swiss-ai.Apertus-8B-Instruct-2509.Q8_0.gguf",
+        "url": "https://huggingface.co/DevQuasar/swiss-ai.Apertus-8B-Instruct-2509-GGUF/resolve/main/swiss-ai.Apertus-8B-Instruct-2509.Q8_0.gguf"
+      },
+      "sha256": "823a2ce1b89f8e31c197167e144fb4e5220f0adb44132b8e54ccdb2dd5bedae7",
+      "local_cache": "local-artifacts/models/swiss-ai.Apertus-8B-Instruct-2509-Q8_0.gguf",
+      "board_path": "/data/models/swiss-ai.Apertus-8B-Instruct-2509-Q8_0.gguf"
+    },
+    "glm4_9b_q8_gguf": {
+      "kind": "model",
+      "framework": "llama.cpp-et",
+      "variant": "GLM-4-9B-0414-Q8_0",
+      "filename": "GLM-4-9B-0414-Q8_0.gguf",
+      "env": "GLM4_9B_MODEL_PATH",
+      "source": {
+        "type": "huggingface",
+        "repo": "bartowski/THUDM_GLM-4-9B-0414-GGUF",
+        "revision": "main",
+        "filename": "THUDM_GLM-4-9B-0414-Q8_0.gguf",
+        "url": "https://huggingface.co/bartowski/THUDM_GLM-4-9B-0414-GGUF/resolve/main/THUDM_GLM-4-9B-0414-Q8_0.gguf"
+      },
+      "sha256": "7b4ea2795934ca05dc409251dddd289160a194a4d920b575d1de4516808bb50d",
+      "local_cache": "local-artifacts/models/GLM-4-9B-0414-Q8_0.gguf",
+      "board_path": "/data/models/GLM-4-9B-0414-Q8_0.gguf"
     }
   }
 }