feat: centralize model configurations and benchmark settings into a new models.py module and update Dockerfile and scripts to use it.

scripts/models.py

@@ -0,0 +1,98 @@
+MODEL_TABLE = {
+    # 1. Llama 3.1 8B Instruct
+    # MAD uses 131k tokens. We scale to 32k for 32GB VRAM safety.
+    "meta-llama/Meta-Llama-3.1-8B-Instruct": {
+        "trust_remote": False,
+        "valid_tp": [1, 2],
+        "max_num_seqs": "64",
+        "max_tokens": "32768" 
+    },
+    
+    "google/gemma-3-12b-it": {
+        "trust_remote": False,
+        "valid_tp": [1, 2],
+        "max_num_seqs": "64",
+        "max_tokens": "32768" 
+    },
+    # 2. GPT-OSS 20B (MXFP4)
+    # MAD Row 0 uses 8192. We match this exactly.
+    "openai/gpt-oss-20b": {
+        "trust_remote": True,
+        "valid_tp": [1, 2],
+        "max_num_seqs": "64",
+        "max_tokens": "8192"
+    },
+    
+    "openai/gpt-oss-120b": {
+        "trust_remote": True,
+        "valid_tp": [1],
+        "max_num_seqs": "64",
+        "max_tokens": "8192"
+    },
+
+
+    "Qwen/Qwen3-14B-AWQ": {
+        "trust_remote": True,
+        "valid_tp": [1], # Too big for single GPU
+        "max_num_seqs": "32", # Lower concurrency for safety
+        "max_tokens": "16384", # Lower batch size because Eager mode is CPU intensive
+        "enforce_eager": False, 
+        "env": {"VLLM_USE_TRITON_AWQ": "1"} # Fixes "Unsupported Hardware" error
+    },
+
+    # 4. Qwen 30B 4-bit
+    "btbtyler09/Qwen3-Coder-30B-A3B-Instruct-gptq-4bit": {
+        "trust_remote": True,
+        "enforce_eager": False, 
+        "valid_tp": [1, 2],
+        "max_num_seqs": "64",
+        "max_tokens": "32768"
+    },
+
+    "btbtyler09/Qwen3-Coder-30B-A3B-Instruct-gptq-8bit": {
+        "trust_remote": True,
+        "enforce_eager": False, 
+        "valid_tp": [1, 2],
+        "max_num_seqs": "64",
+        "max_tokens": "32768"
+    },
+
+    "zai-org/GLM-4.7-Flash": {
+        "trust_remote": True,
+        "enforce_eager": False, 
+        "valid_tp": [1, 2],
+        "max_num_seqs": "64",
+        "max_tokens": "32768",
+    },
+
+    # 5. Qwen 80B AWQ
+    # Size: ~48GB. Fits on 2x32GB (64GB). Leftover for Cache: ~16GB.
+    # Config: 20k ctx fits in that cache. Eager mode required for stability.
+     "dazipe/Qwen3-Next-80B-A3B-Instruct-GPTQ-Int4A16": {
+        "trust_remote": True,
+        "valid_tp": [1], # Too big for single GPU
+        "max_num_seqs": "32", # Lower concurrency for safety
+        "max_tokens": "16384", # Lower batch size because Eager mode is CPU intensive
+        "enforce_eager": True, 
+        "env": {"VLLM_USE_TRITON_AWQ": "1"} # Fixes "Unsupported Hardware" error
+    },
+
+}
+
+MODELS_TO_RUN = [
+    "meta-llama/Meta-Llama-3.1-8B-Instruct",
+    "google/gemma-3-12b-it",
+    "Qwen/Qwen3-14B-AWQ",
+    "openai/gpt-oss-20b",
+    "openai/gpt-oss-120b",
+    "zai-org/GLM-4.7-Flash",
+    "btbtyler09/Qwen3-Coder-30B-A3B-Instruct-gptq-4bit",
+    "btbtyler09/Qwen3-Coder-30B-A3B-Instruct-gptq-8bit",
+    "dazipe/Qwen3-Next-80B-A3B-Instruct-GPTQ-Int4A16",
+]
+
+# Hardware / Global Defaults
+GPU_UTIL = "0.90"
+OFF_NUM_PROMPTS = 200
+OFF_FORCED_OUTPUT = "512"
+DEFAULT_BATCH_TOKENS = "8192"

scripts/start_vllm.py

@@ -12,16 +12,21 @@ SCRIPT_DIR = Path(__file__).parent.resolve()
 BENCH_DIR = SCRIPT_DIR.parent / "benchmarks"
 OPT_DIR = Path("/opt")
 
-# Check /opt first (Container), then local fallback
+
+# Check /opt first (Container), then local fallback for results file location
 if (OPT_DIR / "run_vllm_bench.py").exists():
     sys.path.append(str(OPT_DIR))
 else:
     sys.path.append(str(BENCH_DIR))
+    # Also ensure current script dir is in path for local 'models' import if not already
+    sys.path.append(str(SCRIPT_DIR))
 
 try:
-    from run_vllm_bench import MODEL_TABLE, MODELS_TO_RUN
+    import models
+    MODEL_TABLE = models.MODEL_TABLE
+    MODELS_TO_RUN = models.MODELS_TO_RUN
 except ImportError:
-    print("Error: Could not import run_vllm_bench.py config.")
+    print("Error: Could not import models.py config.")
     sys.exit(1)
 
 if (OPT_DIR / "max_context_results.json").exists():

scripts/start_vllm_cluster.py

@@ -13,16 +13,20 @@ SCRIPT_DIR = Path(__file__).parent.resolve()
 BENCH_DIR = SCRIPT_DIR.parent / "benchmarks"
 OPT_DIR = Path("/opt")
 
+
 # Check /opt first (Container), then local fallback
 if (OPT_DIR / "run_vllm_bench.py").exists():
     sys.path.append(str(OPT_DIR))
 else:
     sys.path.append(str(BENCH_DIR))
+    sys.path.append(str(SCRIPT_DIR))
 
 try:
-    from run_vllm_bench import MODEL_TABLE, MODELS_TO_RUN
+    import models
+    MODEL_TABLE = models.MODEL_TABLE
+    MODELS_TO_RUN = models.MODELS_TO_RUN
 except ImportError:
-    print("Error: Could not import run_vllm_bench.py config.")
+    print("Error: Could not import models.py config.")
     sys.exit(1)
 
 if (OPT_DIR / "max_context_results.json").exists():