Model reference · open weights
WebWorld is an open-weight language model from Qwen. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | Qwen |
|---|---|
| Type | Language models |
| Task | Text gen |
| Parameters (lead) | 1M |
| Context | 40k tokens |
| Runs with | transformers |
| Based on | Qwen/Qwen3-8B |
| Released | 2026-02-13 |
| Popularity | 1k downloads / month |
| Licence | Open weights |
About
WebWorld is a large-scale open-web world model series for training and evaluating web agents. It is trained on 1M+ real-world web interaction trajectories via a scalable hierarchical data pipeline, supporting:
Agents trained on WebWorld-synthesized trajectories achieve +9.9% on MiniWob++ and +10.9% on WebArena. When used for inference-time lookahead search, WebWorld outperforms GPT-5 as a world model.
| Model | Base Model | HuggingFace Link | ModelScope Link |
|---|---|---|---|
| WebWorld-8B | Qwen3-8B | 🤗 HuggingFace | 🤖 ModelScope |
| WebWorld-14B | Qwen3-14B | 🤗 HuggingFace | 🤖 ModelScope |
| WebWorld-32B | Qwen3-32B | 🤗 HuggingFace | 🤖 ModelScope |
WebWorldData: Huggingface: Qwen/WebWorldData, ModelScope: Qwen/WebWorldData
💡 Recommendation: Use 8B for fast simulation and data synthesis; use 14B/32B for higher-fidelity simulation and better long-horizon robustness. For best results in a specific environment, we recommend task-specific fine-tuning on in-domain trajectories.
transformers (recommended: latest version)torchaccelerate, vllm for efficient servingKey Notes:
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "Qwen/WebWorld-8B" # or WebWorld-14B, WebWorld-32B
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto",
torch_dtype=torch.bfloat16,
trust_remote_code=True,
).eval()
system_prompt = (
"You are a web world model. I will provide you with an initial page state "
"and a sequence of actions. For each action, predict the resulting page state.\n"
"Strictly maintain the original format. Output only the full page state "
"without explanations, code, or truncation."
)
current_state = """RootWebArea 'Global Start - Your Daily Portal', focused
\t[1] banner 'Top Header', visible
\t\t[2] link 'Set as Homepage', clickable, visible
\t\t[3] link 'Feedback', clickable, visible
\t\t[5] region 'Weather Widget', visible
\t\t\tStaticText 'New York, USA'
\t\t\t[6] image 'Sunny', visible
\t\t\tStaticText '24°C'
\t\t[8] link 'Sign In', clickable, visible
\t[10] region 'Search Area', visible
\t\t[11] image 'Global Start Logo', visible
\t\tStaticText 'Search the entire web'
\t\t[12] tablist 'Search Engine Selector', orientation='horizontal'
\t\t\t[13] tab 'Google', selected=True, clickable
\t\t\t[14] tab 'Bing', selected=False, clickable
\t\t\t[15] tab 'DuckDuckGo', selected=False, clickable
\t\t[18] combobox 'Web Search', clickable, visible, autocomplete='both', expanded=False
\t\t\t[19] textbox 'Type keywords or URL...', clickable, visible, editable, value=''
\t\t[20] button 'Search', clickable, visible
\t[30] navigation 'Category Bar', visible
\t\t[31] link 'Home', clickable, selected=True
\t\t[32] link 'News', clickable
\t\t[33] link 'Video', clickable
\t\t[34] link 'Shopping', clickable
\t\t[35] link 'Social', clickable
\t[50] main 'Site Directory', visible
\t\t[51] region 'Top Recommended', visible
\t\t\t[52] heading 'Most Popular', visible
\t\t\t[53] list 'Top Sites Grid', visible
\t\t\t\t[54] link 'Facebook', clickable
\t\t\t\t[56] link 'YouTube', clickable
\t\t\t\t[58] link 'Amazon', clickable
\t\t\t\t[60] link 'Twitter / X', clickable
\t\t\t\t[62] link 'Instagram', clickable
\t\t\t\t[64] link 'Wikipedia', clickable
\t\t\t\t[66] link 'Netflix', clickable
\t\t\t\t[68] link 'LinkedIn', clickable
\t\t[80] region 'News & Media', visible
\t\t\t[81] heading 'Latest News', visible
\t\t\t[82] link 'CNN', clickable
\t\t\t[83] link 'BBC', clickable
\t\t\t[84] link 'The Verge', clickable
\t\t[90] region 'Shopping', visible
\t\t\t[91] heading 'E-Commerce', visible
\t\t\t[92] link 'eBay', clickable
\t\t\t[93] link 'Walmart', clickable
\t\t\t[94] link 'Best Buy', clickable
\t[200] complementary 'Ads', visible
\t\t[201] image 'Ad: Travel to Japan'
\t\t[202] link 'Book Now', clickable
\t[300] contentinfo 'Footer', visible
\t\tStaticText '© 2026 Global Start Inc.'"""
user_message = (
f"Initial Page State:\n{current_state}\n\n"
f"First Action: 'click([32])'\n\n"
f"Next Page State:"
)
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_message},
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys webworld for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (webworld below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"webworld","messages":[{"role":"user","content":"Hello"}]}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.