diff --git a/recipes/models/Qwen/Qwen2.5-VL-7B-Instruct.yaml b/recipes/models/Qwen/Qwen2.5-VL-7B-Instruct.yaml index 4b21c7d3a6..5f27444e46 100644 --- a/recipes/models/Qwen/Qwen2.5-VL-7B-Instruct.yaml +++ b/recipes/models/Qwen/Qwen2.5-VL-7B-Instruct.yaml @@ -60,6 +60,7 @@ variants: precision: fp8 vram_minimum_gb: 9 description: "RedHatAI FP8 (E4M3) with dynamic per-token activation quantization" + supported_hardware: [trillium] extra_args: - "--kv-cache-dtype" - "fp8" diff --git a/recipes/models/Qwen/Qwen3-4B.yaml b/recipes/models/Qwen/Qwen3-4B.yaml index 8ef62812ae..1d24454702 100644 --- a/recipes/models/Qwen/Qwen3-4B.yaml +++ b/recipes/models/Qwen/Qwen3-4B.yaml @@ -66,6 +66,7 @@ variants: label: "FP8 Dynamic (RedHat)" vram_minimum_gb: 5 description: "RedHatAI FP8 (E4M3) with dynamic per-token activation quantization" + supported_hardware: [trillium] extra_args: - "--kv-cache-dtype" - "fp8" diff --git a/recipes/models/meta-llama/Llama-3.1-8B-Instruct.yaml b/recipes/models/meta-llama/Llama-3.1-8B-Instruct.yaml index 04450187b1..b5d0ffaaab 100644 --- a/recipes/models/meta-llama/Llama-3.1-8B-Instruct.yaml +++ b/recipes/models/meta-llama/Llama-3.1-8B-Instruct.yaml @@ -88,6 +88,7 @@ variants: label: "FP8 Dynamic (RedHat)" vram_minimum_gb: 10 description: "RedHatAI FP8 (E4M3) with dynamic per-token activation quantization" + supported_hardware: [h100, h200] extra_args: - "--kv-cache-dtype" - "fp8" @@ -98,6 +99,7 @@ variants: label: "FP8 (RedHat)" vram_minimum_gb: 10 description: "RedHatAI FP8 quantization" + supported_hardware: [h100, h200] extra_args: - "--kv-cache-dtype" - "fp8" @@ -108,6 +110,7 @@ variants: label: "FP8 Block (RedHat)" vram_minimum_gb: 10 description: "RedHatAI FP8 block quantization" + supported_hardware: [h100, h200, xeon6] extra_args: - "--kv-cache-dtype" - "fp8" diff --git a/recipes/models/meta-llama/Llama-3.3-70B-Instruct.yaml b/recipes/models/meta-llama/Llama-3.3-70B-Instruct.yaml index ce0c3e1528..8390b98fcd 100644 --- a/recipes/models/meta-llama/Llama-3.3-70B-Instruct.yaml +++ b/recipes/models/meta-llama/Llama-3.3-70B-Instruct.yaml @@ -75,6 +75,7 @@ variants: label: "FP8 (RedHat)" vram_minimum_gb: 84 description: "RedHatAI FP8 (E4M3) with dynamic per-token activation quantization" + supported_hardware: [h100, h200, b200, gb200] extra_args: - "--kv-cache-dtype" - "fp8" @@ -95,6 +96,7 @@ variants: label: "FP8 Block (RedHat)" vram_minimum_gb: 84 description: "RedHatAI FP8 block quantization" + supported_hardware: [h100, h200, b200, gb200, xeon6] extra_args: - "--kv-cache-dtype" - "fp8" @@ -105,6 +107,7 @@ variants: label: "NVFP4 (RedHat)" vram_minimum_gb: 46 description: "RedHatAI NVFP4 quantization" + supported_hardware: [b200, gb200] compatible_strategies: - single_node_tp diff --git a/recipes/models/meta-llama/Llama-4-Scout-17B-16E-Instruct.yaml b/recipes/models/meta-llama/Llama-4-Scout-17B-16E-Instruct.yaml index de845242cf..3826170e80 100644 --- a/recipes/models/meta-llama/Llama-4-Scout-17B-16E-Instruct.yaml +++ b/recipes/models/meta-llama/Llama-4-Scout-17B-16E-Instruct.yaml @@ -67,6 +67,7 @@ variants: label: "FP8 (RedHat)" vram_minimum_gb: 131 description: "RedHatAI FP8 (E4M3) with dynamic per-token activation quantization" + supported_hardware: [h100, b200, gb200] extra_args: - "--kv-cache-dtype" - "fp8" @@ -77,6 +78,7 @@ variants: label: "NVFP4 (RedHat)" vram_minimum_gb: 65 description: "RedHatAI compressed-tensors NVFP4 quantization for Blackwell GPUs" + supported_hardware: [b200, gb200] extra_args: - "--kv-cache-dtype" - "fp8" @@ -89,6 +91,7 @@ variants: label: "FP8 Block (RedHat)" vram_minimum_gb: 131 description: "RedHatAI FP8 block quantization" + supported_hardware: [h100, b200, gb200] extra_args: - "--kv-cache-dtype" - "fp8"