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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:v0.25.1-gb10.1"
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+model = "Qwen/Qwen-AgentWorld-35B-A3B"
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+tensor_parallel_size = 1
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+pipeline_parallel_size = 1
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+
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+# Solo: ~70 GB BF16 weights, only 10 GA layers need KV cache (DeltaNet is linear).
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+# Use: sm121-launcher serve --recipe qwen-agentworld-35b --node dgx1.lan
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+# Nodes: sm121-launcher serve --recipe qwen-agentworld-35b --cluster 2nodes-dac
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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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+--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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+--enable-auto-tool-choice
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+--tool-call-parser qwen3_xml
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+--served-model-name qwen-agentworld-35b
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+"""
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