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@@ -0,0 +1,25 @@
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+engine = "vllm"
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+name = "Qwen-AgentWorld-35B-A3B (vLLM)"
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+docker_image = "ghcr.io/timothystewart6/vllm-gb10:v0.23.0-gb10.1"
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+model = "Qwen/Qwen-AgentWorld-35B-A3B"
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+required_nodes = 2
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+tensor_parallel_size = 2
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+pipeline_parallel_size = 1
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+distributed_backend = "mp"
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+
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+# 35B total / 3B active MoE — world model for agentic environment simulation.
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+# 2× DGX Spark (GB10), 128 GB shared each.
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+# TP=2 → ~35 GB/node for weights, room for 262K context.
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+# Requires --language-model-only (no vision weights in checkpoint).
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+
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+entrypoint = ["vllm", "serve"]
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+
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+args = """
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+--port 30000
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+--max-model-len 262144
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+--reasoning-parser qwen3
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+--language-model-only
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+--trust-remote-code
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+--gpu-memory-utilization 0.90
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+--enable-prefix-caching
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+"""
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