Model ID
Qwen/Qwen-AgentWorld-35B-A3B
Capabilities
Qwen AgentWorld 35B A3B
Qwen AgentWorld 35B A3B is a native language world model designed to simulate agent environments across MCP, Search, Terminal, SWE, Android, Web, and OS interaction domains. It features 35B total parameters with 3B activated, using a 40-layer hybrid architecture with 2,048 hidden size and 16 attention heads. The model combines Gated DeltaNet and Gated Attention layers in a 3:1 pattern with 256 routed experts, activating 8 experts per token alongside a shared expert. Trained through CPT, SFT, and RL, it supports native world modeling and a 262K-token context window.
About this model
Qwen AgentWorld 35B A3B is a native language world model designed to simulate agent environments across MCP, Search, Terminal, SWE, Android, Web, and OS interaction domains. It features 35B total parameters with 3B activated, using a 40-layer hybrid architecture with 2,048 hidden size and 16 attention heads. The model combines Gated DeltaNet and Gated Attention layers in a 3:1 pattern with 256 routed experts, activating 8 experts per token alongside a shared expert. Trained through CPT, SFT, and RL, it supports native world modeling and a 262K-token context window.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (Qwen/Qwen-AgentWorld-35B-A3B). Released under Apache 2.0. Further reading: Paper · Blog
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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