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redai-infra
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Model Details
Model Provider
redai-infra
Model Tree
Qwen/Qwen3-VL-8B-Thinking
Input Modalities
Output Modalities
Supported Functionality
test_all_no_internet, 309 tasks, greedy ×3)| accuracy | input cost | peak context (p95) | |
|---|---|---|---|
| Base operating point (img4, uncompressed) | 33.0% | 100% | 11.5K tok |
| This checkpoint (img2 + skip, compressed) | 37.8% | 53% | −37% |
This is a complete, directly-loadable Qwen3-VL-8B model directory. Deploy it with the compressed observation rule it was trained under — evaluating with the default rich observation underestimates it:
bash
huggingface-cli download redai-infra/hybrid-routing-context-rl --local-dir ckpts/context_rlMODEL=ckpts/context_rl CONTEXT_POLICY=skip_on_mcp_success MAX_IMAGE_HISTORY_LENGTH=2 \bash scripts/run_mcp_eval.sh
Code, configs, and full provenance: https://github.com/redai-infra/hybrid-routing-agent — see results/context_rl/PROVENANCE.md for how every number above is derived, and configs/experiments/context_rl.yaml for the exact training recipe.
markdown
@article{fan2026screenshots,title = {Screenshots or Tools? Eliciting Tool Use and Managing MultimodalContext in Hybrid GUI-MCP Computer-Use Agents},author = {Fan, Siqi and Li, Minghao and Ma, Xiaoqian and Tan, Wenhui andHuang, Xiusheng and Wu, Juntong and Zhang, Liujie and Shang, Shuoand Chen, Weihang},journal = {arXiv preprint arXiv:2608.03327},year = {2026},url = {https://arxiv.org/abs/2608.03327}}