feat(model-ports): add openelm_1_1b, olmo_1b, granite_3_1b_a400m

.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 +343,15 @@
     },
     "smolvlm_500m": {
       "config": "ported_models/llama_cpp_et/benchmarks/smolvlm_500m.json"
+    },
+    "openelm_1_1b": {
+      "config": "ported_models/llama_cpp_et/benchmarks/openelm_1_1b.json"
+    },
+    "olmo_1b": {
+      "config": "ported_models/llama_cpp_et/benchmarks/olmo_1b.json"
+    },
+    "granite_3_1b_a400m": {
+      "config": "ported_models/llama_cpp_et/benchmarks/granite_3_1b_a400m.json"
     }
   }
 }

ported_models/granite_3_1b_a400m/docs/RECIPE.md

@@ -0,0 +1,60 @@
+# Granite-3.0-1B-A400M Porting Recipe
+
+## Overview
+
+Adds `ibm-granite/granite-3.0-1b-a400m-instruct` (1B-total-parameter /
+400M-active-parameter sparse Mixture-of-Experts causal LM) to the
+`llama.cpp-et` framework. Confirmed via local GGUF metadata inspection:
+`general.architecture = granitemoe` -- distinct from IBM's dense `granite`
+architecture (already claimed elsewhere on this board), and the first MoE
+model attempted in this specific porting campaign.
+
+## Model Reference
+
+- **Source**: `ibm-granite/granite-3.0-1b-a400m-instruct` (Hugging Face),
+  revision `ffec3c35bdfd97a06f0b4cd5fcc92cd9b1584445`
+- **License**: Apache-2.0
+- **GGUF source**: `bartowski/granite-3.0-1b-a400m-instruct-GGUF`, file
+  `granite-3.0-1b-a400m-instruct-Q8_0.gguf`
+- **Quantization**: Q8_0,
+  `sha256=8c37dd0c10b73e9304b98a242be4adcd3050c09e9042c4862d49e2cfccf35411`
+  (verified locally against the downloaded file)
+- **Architecture**: `arch = granitemoe` per GGUF metadata, 242 tensors
+  (roughly double a similarly-sized dense model's tensor count, consistent
+  with per-expert FFN weight 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 on the CPU backend:
+
+```
+Final estimate: PPL = 5.7635 +/- 0.84793
+```
+
+This confirms the MoE routing path (`GGML_OP_MUL_MAT_ID`, indexed/batched
+matmul against a per-token-selected expert weight subset) works correctly
+on `ggml-cpu` -- the first MoE model actually exercised in this campaign.
+
+## Open question: MoE routing on the ET backend specifically (not confirmed)
+
+CPU-backend success does not prove the ET-SoC1 backend's own `MUL_MAT_ID`
+implementation works -- `ggml-et.cpp` lists it as supported (per the
+op-coverage audit in `falcon7b_recipe.md` from earlier in this campaign),
+but that has never been exercised against a real MoE model on ET sysemu or
+board. Flagging as a genuinely open verification item, not a formality.
+
+## Open items for maintainer review
+
+- Registered in `artifacts.json`, `ported_models/llama_cpp_et/benchmarks/granite_3_1b_a400m.json`,
+  and `.github/ci/benchmark_config.json` (port 18132) -- board-testable now,
+  independent of the model-ports track claim below.
+- `ported_models/submissions/model_ports/granite_3_1b_a400m.json` is the
+  model-ports track claim, pending identity approval.
+- No changes to any protected file or the vendored submodule.
+- MoE routing (`MUL_MAT_ID`) confirmed on CPU, NOT live-verified against ET
+  sysemu specifically -- see note above. Genuinely unproven on ET, not a hedge.

ported_models/granite_3_1b_a400m/oracle/perplexity_oracle.json

@@ -0,0 +1,25 @@
+{
+  "oracle_type": "perplexity_threshold",
+  "model_artifact": {
+    "repo": "bartowski/granite-3.0-1b-a400m-instruct-GGUF",
+    "revision": "main",
+    "filename": "granite-3.0-1b-a400m-instruct-Q8_0.gguf",
+    "sha256": "8c37dd0c10b73e9304b98a242be4adcd3050c09e9042c4862d49e2cfccf35411"
+  },
+  "corpus": {
+    "artifact": "wikitext2_raw_test",
+    "sha256": "173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08"
+  },
+  "command": "llama-perplexity --model granite-3.0-1b-a400m-instruct-Q8_0.gguf -f wiki.test.raw -c 128 -b 128 -ub 128 --chunks 4",
+  "reference_run": {
+    "final_ppl": 5.7635,
+    "final_ppl_stderr": 0.84793,
+    "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 [4.61, 6.92] 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 +485,60 @@
       "sha256": "d1eb8b6b23979205fdf63703ed10f788131a3f812c7b1f72e0119d5d81295150",
       "size_bytes": 108783360,
       "note": "SmolVLM 500M vision projector (SigLIP ~93M + MLP). Q8_0 quantized. Must be loaded alongside smolvlm_500m_q8_gguf."
+    },
+    "openelm_1_1b_q8_gguf": {
+      "kind": "model",
+      "framework": "llama.cpp-et",
+      "variant": "OpenELM-1_1B-Instruct-Q8_0",
+      "filename": "OpenELM-1_1B-Instruct-Q8_0.gguf",
+      "env": "OPENELM_1_1B_MODEL_PATH",
+      "source": {
+        "type": "huggingface",
+        "repo": "LiteLLMs/OpenELM-1_1B-Instruct-GGUF",
+        "revision": "main",
+        "filename": "Q8_0/Q8_0-00001-of-00001.gguf",
+        "url": "https://huggingface.co/LiteLLMs/OpenELM-1_1B-Instruct-GGUF/resolve/main/Q8_0/Q8_0-00001-of-00001.gguf"
+      },
+      "sha256": "13dc6676b2355d0356d7892d8b34d8518233d79a28f9ea1d14f94e81d7decad5",
+      "size": 1148477504,
+      "local_cache": "local-artifacts/models/OpenELM-1_1B-Instruct-Q8_0.gguf",
+      "board_path": "/data/models/OpenELM-1_1B-Instruct-Q8_0.gguf"
+    },
+    "olmo_1b_q8_gguf": {
+      "kind": "model",
+      "framework": "llama.cpp-et",
+      "variant": "OLMo-1B-hf-Q8_0",
+      "filename": "OLMo-1B-hf-Q8_0.gguf",
+      "env": "OLMO_1B_MODEL_PATH",
+      "source": {
+        "type": "huggingface",
+        "repo": "RichardErkhov/allenai_-_OLMo-1B-hf-gguf",
+        "revision": "main",
+        "filename": "OLMo-1B-hf.Q8_0.gguf",
+        "url": "https://huggingface.co/RichardErkhov/allenai_-_OLMo-1B-hf-gguf/resolve/main/OLMo-1B-hf.Q8_0.gguf"
+      },
+      "sha256": "11ad66bb4b0c4b9d4b40ccef351a506e322fc8265b87e3638b18802768d8875e",
+      "size": 1252087840,
+      "local_cache": "local-artifacts/models/OLMo-1B-hf-Q8_0.gguf",
+      "board_path": "/data/models/OLMo-1B-hf-Q8_0.gguf"
+    },
+    "granite_1b_a400m_q8_gguf": {
+      "kind": "model",
+      "framework": "llama.cpp-et",
+      "variant": "granite-3.0-1b-a400m-instruct-Q8_0",
+      "filename": "granite-3.0-1b-a400m-instruct-Q8_0.gguf",
+      "env": "GRANITE_3_1B_A400M_MODEL_PATH",
+      "source": {
+        "type": "huggingface",
+        "repo": "bartowski/granite-3.0-1b-a400m-instruct-GGUF",
+        "revision": "main",
+        "filename": "granite-3.0-1b-a400m-instruct-Q8_0.gguf",
+        "url": "https://huggingface.co/bartowski/granite-3.0-1b-a400m-instruct-GGUF/resolve/main/granite-3.0-1b-a400m-instruct-Q8_0.gguf"
+      },
+      "sha256": "8c37dd0c10b73e9304b98a242be4adcd3050c09e9042c4862d49e2cfccf35411",
+      "size": 1422237440,
+      "local_cache": "local-artifacts/models/granite-3.0-1b-a400m-instruct-Q8_0.gguf",
+      "board_path": "/data/models/granite-3.0-1b-a400m-instruct-Q8_0.gguf"
     }
   }
 }

ported_models/llama_cpp_et/benchmarks/granite_3_1b_a400m.json

@@ -0,0 +1,52 @@
+{
+  "runner": "llama_server",
+  "board": true,
+  "framework": {
+    "name": "llama.cpp-et",
+    "runner": "llama_server",
+    "source_artifact": "llama_cpp_source"
+  },
+  "artifacts_file": "../artifacts.json",
+  "canonical_variant": "granite-3.0-1b-a400m-instruct-Q8_0",
+  "score": {
+    "metric": "tokens_per_second",
+    "label": "Decode tokens/s",
+    "higher_is_better": true
+  },
+  "llama_server": {
+    "source_artifact": "llama_cpp_source",
+    "model_artifact": "granite_1b_a400m_q8_gguf",
+    "server_artifact": "llama_server",
+    "workdir_artifact": "llama_cpp_build",
+    "host": "127.0.0.1",
+    "port": 18132,
+    "device": "ET",
+    "gpu_layers": 99,
+    "ctx_size": 2048,
+    "batch_size": 256,
+    "ubatch_size": 128,
+    "parallel": 1,
+    "cache_ram_mib": 0,
+    "ready_timeout_s": 300,
+    "request_timeout_s": 420,
+    "flash_attn": false,
+    "api": "completion",
+    "prompt": "Repeat this token sequence without commentary: OK OK OK OK OK OK OK OK OK OK",
+    "max_tokens": 96,
+    "temperature": 0,
+    "ignore_eos": true,
+    "min_completion_tokens": 32,
+    "perplexity": {
+      "enabled": true,
+      "perplexity_artifact": "llama_perplexity",
+      "corpus_artifact": "wikitext2_raw_test",
+      "ctx_size": 128,
+      "batch_size": 128,
+      "ubatch_size": 128,
+      "timeout_s": 420,
+      "min_ppl": 1.0,
+      "max_ppl": 1000.0,
+      "chunks": 4
+    }
+  }
+}

ported_models/llama_cpp_et/benchmarks/olmo_1b.json

@@ -0,0 +1,52 @@
+{
+  "runner": "llama_server",
+  "board": true,
+  "framework": {
+    "name": "llama.cpp-et",
+    "runner": "llama_server",
+    "source_artifact": "llama_cpp_source"
+  },
+  "artifacts_file": "../artifacts.json",
+  "canonical_variant": "OLMo-1B-hf-Q8_0",
+  "score": {
+    "metric": "tokens_per_second",
+    "label": "Decode tokens/s",
+    "higher_is_better": true
+  },
+  "llama_server": {
+    "source_artifact": "llama_cpp_source",
+    "model_artifact": "olmo_1b_q8_gguf",
+    "server_artifact": "llama_server",
+    "workdir_artifact": "llama_cpp_build",
+    "host": "127.0.0.1",
+    "port": 18131,
+    "device": "ET",
+    "gpu_layers": 99,
+    "ctx_size": 2048,
+    "batch_size": 256,
+    "ubatch_size": 128,
+    "parallel": 1,
+    "cache_ram_mib": 0,
+    "ready_timeout_s": 300,
+    "request_timeout_s": 420,
+    "flash_attn": false,
+    "api": "completion",
+    "prompt": "Repeat this token sequence without commentary: OK OK OK OK OK OK OK OK OK OK",
+    "max_tokens": 96,
+    "temperature": 0,
+    "ignore_eos": true,
+    "min_completion_tokens": 32,
+    "perplexity": {
+      "enabled": true,
+      "perplexity_artifact": "llama_perplexity",
+      "corpus_artifact": "wikitext2_raw_test",
+      "ctx_size": 128,
+      "batch_size": 128,
+      "ubatch_size": 128,
+      "timeout_s": 420,
+      "min_ppl": 1.0,
+      "max_ppl": 1000.0,
+      "chunks": 4
+    }
+  }
+}