fix open-weights metadata: 29 missing weights links, 3 wrong flags

models/cohere/command-a-plus-05-2026.toml

@@ -18,3 +18,7 @@ output = 64_000
 [modalities]
 input = ["text", "image"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/CohereLabs/command-a-plus-05-2026-bf16"

models/cohere/north-mini-code-1-0.toml

@@ -62,3 +62,7 @@ score = 37
 metric = "success rate"
 source = "https://artificialanalysis.ai/articles/north-mini-code-cohere-s-small-coding-focused-moe-model"
 date = "2026-06-09"
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/CohereLabs/North-Mini-Code-1.0"

models/deepreinforce/ornith-1.0-31b.toml

@@ -1,3 +1,7 @@
+# open_weights corrected to false: the 31B Dense variant is named in the Ornith 1.0
+# announcement (https://deep-reinforce.com/ornith_1_0.html) but was never published —
+# https://huggingface.co/deepreinforce-ai ships only 9B/35B/397B and no 31B repo or
+# community quantization exists anywhere on Hugging Face.
 # Announced in the Ornith 1.0 family but not yet published on Hugging Face as
 # of 2026-06-28 — no weights URL or benchmark scores available yet. Modalities
 # and context window are provisional, assumed consistent with the rest of the
@@ -12,7 +16,7 @@ attachment = true
 reasoning = true
 temperature = true
 tool_call = true
-open_weights = true
+open_weights = false
 license = "MIT"
 
 [limit]

models/moonshotai/kimi-k3.toml

@@ -17,3 +17,7 @@ output = 131_072
 [modalities]
 input = ["text", "image", "video"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/moonshotai/Kimi-K3"

models/nvidia/llama-3.1-nemotron-70b-instruct.toml

@@ -16,3 +16,7 @@ output = 8_192
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"

models/nvidia/llama-3.1-nemotron-safety-guard-8b-v3.toml

@@ -16,3 +16,7 @@ output = 4_096
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Llama-3.1-Nemotron-Safety-Guard-8B-v3"

models/nvidia/llama-3.1-nemotron-ultra-253b.toml

@@ -16,3 +16,7 @@ output = 8_192
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Llama-3_1-Nemotron-Ultra-253B-v1"

models/nvidia/llama-3.3-nemotron-super-49b-v1.5.toml

@@ -16,3 +16,7 @@ output = 131_072
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Llama-3_3-Nemotron-Super-49B-v1_5"

models/nvidia/llama-3.3-nemotron-super-49b-v1.toml

@@ -16,3 +16,7 @@ output = 131_072
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Llama-3_3-Nemotron-Super-49B-v1"

models/nvidia/llama-nemotron-embed-vl-1b-v2.toml

@@ -16,3 +16,7 @@ output = 2_048
 [modalities]
 input = ["text", "image"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/llama-nemotron-embed-vl-1b-v2"

models/nvidia/llama-nemotron-rerank-vl-1b-v2.toml

@@ -16,3 +16,7 @@ output = 4_096
 [modalities]
 input = ["text", "image"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/llama-nemotron-rerank-vl-1b-v2"

models/nvidia/mistral-nemotron.toml

@@ -1,3 +1,6 @@
+# open_weights corrected to false: no public weights exist — nvidia/Mistral-Nemotron is
+# not on Hugging Face (the nvidia org has no *istral* repo) and the model is served
+# API-only via NVIDIA NIM (https://docs.api.nvidia.com/nim/reference/mistralai-mistral-nemotron).
 name = "Mistral Nemotron"
 description = "Mistral model for multilingual chat, reasoning, and tool-assisted workflows"
 family = "nemotron"
@@ -7,7 +10,7 @@ attachment = false
 reasoning = false
 temperature = true
 tool_call = true
-open_weights = true
+open_weights = false
 
 [limit]
 context = 128_000

models/nvidia/nemotron-3-content-safety.toml

@@ -16,3 +16,7 @@ output = 4_096
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Nemotron-3-Content-Safety"

models/nvidia/nemotron-3-nano-30b-a3b.toml

@@ -16,3 +16,7 @@ output = 262_144
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16"

models/nvidia/nemotron-3-nano-omni-30b-a3b-reasoning.toml

@@ -16,3 +16,7 @@ output = 65_536
 [modalities]
 input = ["text", "image", "video", "audio"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16"

models/nvidia/nemotron-3-super-120b-a12b.toml

@@ -16,3 +16,7 @@ output = 262_144
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16"

models/nvidia/nemotron-3-ultra-550b-a55b.toml

@@ -99,3 +99,7 @@ score = 46.7
 metric = "wins or ties"
 source = "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16"
 date = "2026-06-04"
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16"

models/nvidia/nemotron-3.5-content-safety.toml

@@ -16,3 +16,7 @@ output = 8_192
 [modalities]
 input = ["text", "image"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Nemotron-3.5-Content-Safety"

models/nvidia/nemotron-cascade-2-30b-a3b.toml

@@ -16,3 +16,7 @@ output = 32_768
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Nemotron-Cascade-2-30B-A3B"

models/nvidia/nemotron-content-safety-reasoning-4b.toml

@@ -16,3 +16,7 @@ output = 4_096
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Nemotron-Content-Safety-Reasoning-4B"

models/nvidia/nemotron-mini-4b-instruct.toml

@@ -16,3 +16,7 @@ output = 8_192
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/Nemotron-Mini-4B-Instruct"

models/nvidia/nemotron-nano-12b-v2-vl.toml

@@ -16,3 +16,7 @@ output = 128_000
 [modalities]
 input = ["text", "image", "video"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-12B-v2-VL-BF16"

models/nvidia/nemotron-nano-9b-v2.toml

@@ -16,3 +16,7 @@ output = 131_072
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2"

models/nvidia/nemotron-voicechat.toml

@@ -1,3 +1,6 @@
+# open_weights corrected to false: weights are not publicly downloadable — access is an
+# application-only Early Access Program (https://developer.nvidia.com/nemotron-voicechat-early-access)
+# and no Hugging Face repo exists. Revisit if NVIDIA opens general access.
 name = "Nemotron VoiceChat"
 description = "Nemotron multimodal model for visual reasoning and agentic AI workflows"
 family = "nemotron"
@@ -7,7 +10,7 @@ attachment = true
 reasoning = false
 temperature = true
 tool_call = true
-open_weights = true
+open_weights = false
 
 [limit]
 context = 128_000

models/openai/whisper-large-v3-turbo.toml

@@ -15,3 +15,7 @@ output = 448
 [modalities]
 input = ["audio"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/openai/whisper-large-v3-turbo"

models/openai/whisper-large-v3.toml

@@ -15,3 +15,7 @@ output = 4_096
 [modalities]
 input = ["audio"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/openai/whisper-large-v3"

models/poolside/laguna-m.1.toml

@@ -17,3 +17,7 @@ output = 32_768
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/poolside/Laguna-M.1"

models/poolside/laguna-s-2.1.toml

@@ -16,4 +16,8 @@ output = 32_768
 
 [modalities]
 input = ["text"]
-output = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/poolside/Laguna-S-2.1"

models/poolside/laguna-xs-2.1.toml

@@ -50,3 +50,7 @@ harness = "Harbor"
 version = "2.0"
 source = "https://poolside.ai/blog/introducing-laguna-xs-2-1"
 date = "2026-07-02"
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/poolside/Laguna-XS-2.1"

models/poolside/laguna-xs.2.toml

@@ -17,3 +17,7 @@ output = 32_768
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/poolside/Laguna-XS.2"

models/sarvam/sarvam-105b.toml

@@ -16,3 +16,7 @@ output = 131_072
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/sarvamai/sarvam-105b"

models/sarvam/sarvam-30b.toml

@@ -16,3 +16,7 @@ output = 128_000
 [modalities]
 input = ["text"]
 output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/sarvamai/sarvam-30b"