Imported from https://huggingface.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF

Qwen-AgentWorld is the first language world model to cover seven agent interaction domains within a single model. It simulates agentic environments via long chain-of-thought reasoning, predicting the next environment state given an agent’s action and interaction history. Trained through a three-stage pipeline — CPT injects environment knowledge, SFT activates next-state-prediction reasoning, RL sharpens simulation fidelity — Qwen-AgentWorld is a native world model: environment modeling is the training objective from the CPT stage onward, not a post-hoc add-on.

$ ollama launch opencode \
    --model frob/qwen-agentworld \
    -- \
    run "Create a file README with the contents 'hello world'"

> build · frob/qwen-agentworld:latest

← Write README
Wrote file successfully.

File README created with contents 'hello world'.

$ cat README 
hello world