diff --git a/models.yaml b/models.yaml
index 1f45a2a..542c8ed 100644
--- a/models.yaml
+++ b/models.yaml
@@ -74,3 +74,22 @@ models:
       - {name: der_beam4, value: 17.46, source: rababa/docs/RESULTS.md#hebrew-diacritization}
     parity: {samples: 600, cer_delta: 0.0}
     license: BSD-3-Clause
+  tha-g2p-base-1.0:
+    task: g2p
+    scripts: [Thai, IPA]
+    precision: fp32
+    filename: tha-g2p-base-1.0-fp32.zip
+    parts:
+      - url: https://github.com/interscript/ml-models/releases/download/tha-g2p-base-1.0/tha-g2p-base-1.0-fp32.zip.part-00
+        sha256: c4525414e5dec91a54d055ca9f1acd51c198f81fbfc55977aa82c1fb038d58d7
+        size: 1500000000
+      - url: https://github.com/interscript/ml-models/releases/download/tha-g2p-base-1.0/tha-g2p-base-1.0-fp32.zip.part-01
+        sha256: f5d11fbd75f92e8b5471add867418e2dd4f49a5e258b9ded2f3b5ffa630abe24
+        size: 1281174343
+    sha256: f341a5868867a9847d3f897d1fcc4d1d63b9a59b8913871bcf4ecab48f4fa895
+    size: 2781174343
+    metrics:
+      - {name: per_teacher, value: 4.43, source: interscript/ml-models docs/RESULTS.md#tha-g2p-base-1.0}
+      - {name: per_student, value: 9.19, source: interscript/ml-models docs/RESULTS.md#tha-g2p-base-1.0}
+    parity: {samples: 1219, cer_delta: 0.0}
+    license: BSD-3-Clause
diff --git a/models/tha-g2p-base/tha-g2p-base-1.0.metadata.yaml b/models/tha-g2p-base/tha-g2p-base-1.0.metadata.yaml
index fb631e5..673c470 100644
--- a/models/tha-g2p-base/tha-g2p-base-1.0.metadata.yaml
+++ b/models/tha-g2p-base/tha-g2p-base-1.0.metadata.yaml
@@ -8,25 +8,26 @@ opset: 14
 decoder: kv
 precision: fp32
 license: BSD-3-Clause
-trained_from: >-
-  sequence-level KD from the B-K/umt5-thai-g2p-v2-0.5k teacher (4.43%
-  PER on this harness; secryst's saved umt5 artifacts are unusable —
-  transformers 5.15 dropped the untied lm_head — and the volume's
-  epitran corpus is tone-less, so the published 2.32% tier is
-  unrecoverable until secryst regenerates it); 48,757 beam-4
-  teacher-generated labels; ByT5-base init google/byt5-base; checkpoint
-  secryst-checkpoints:/secryst_thai_g2p_distill_small/run-004/best
+trained_from: sequence-level KD from the B-K/umt5-thai-g2p-v2-0.5k teacher (4.43%
+  PER on this harness; secryst's saved umt5 artifacts are unusable — transformers
+  5.15 dropped the untied lm_head — and the volume's epitran corpus is tone-less,
+  so the published 2.32% tier is unrecoverable until secryst regenerates it); 48,757
+  beam-4 teacher-generated labels; ByT5-base init google/byt5-base; checkpoint secryst-checkpoints:/secryst_thai_g2p_distill_small/run-004/best
 metrics:
-  - name: per_teacher
-    value: 4.43
-    protocol: >-
-      beam-4, corpus-level PER (total_ed/total_gold over chars of
-      joined-piece decode); 1,219 Kaikki Thai test sentences;
-      B-K/umt5-thai-g2p-v2-0.5k teacher
-    source: interscript/ml-models docs/RESULTS.md#tha-g2p-base-1.0
-  - name: per_student
-    value: 9.19
-    protocol: >-
-      beam-4, corpus-level PER, same harness as the teacher; gate
-      +4.76pp <= +5pp (docs/DISTILL-SOURCE-PROMPT.md); exact match 90.81%
-    source: interscript/ml-models docs/RESULTS.md#tha-g2p-base-1.0
+- name: per_teacher
+  value: 4.43
+  protocol: beam-4, corpus-level PER (total_ed/total_gold over chars of joined-piece
+    decode); 1,219 Kaikki Thai test sentences; B-K/umt5-thai-g2p-v2-0.5k teacher
+  source: interscript/interscript-ml docs/RESULTS.md#tha-g2p-base-1.0
+- name: per_student
+  value: 9.19
+  protocol: beam-4, corpus-level PER, same harness as the teacher; gate +4.76pp <=
+    +5pp (docs/DISTILL-SOURCE-PROMPT.md); exact match 90.81%
+  source: interscript/interscript-ml docs/RESULTS.md#tha-g2p-base-1.0
+parity:
+  samples: 1219
+  cer_delta: 0.0
+sha256:
+  decoder-kv.onnx: 357d5c50d7d6832fe7da9f76efb2e2dfdb2707e3abbb93be18a266f4b181b7bc
+  decoder.onnx: f102db0e8957629f615f78669da6f9959015be07e1c2048185f24100492e98b2
+  encoder.onnx: dcaa2fa2e87bc6892babfed859fecdf3f50c4326cf443b04dc8acc939fd523fe