Current as of April 2026. UI-TARS 1.5 7B is a vision-language model from ByteDance specifically trained to perceive and interact with user interfaces. For Hermes Agent users, it functions as a specialized ‘visual eye’ for automation tasks that require navigating apps or websites without accessible APIs.
Specs
| Provider | ByteDance |
| Input cost | $0.10 / M tokens |
| Output cost | $0.20 / M tokens |
| Context window | 128K tokens |
| Max output | 2K tokens |
| Parameters | N/A |
| Features | Standard chat |
What it’s good at
Precise UI Grounding
The model is highly effective at translating visual screenshots into actionable coordinates, allowing Hermes to click and drag with high accuracy.
Cost-Efficiency
At $0.10 per million input tokens and $0.20 per million output tokens, it is an affordable option for high-frequency visual monitoring tasks.
Large Context Window
The 128K context window allows Hermes to maintain a significant history of visual states and terminal outputs during long autonomous runs.
Where it falls short
Limited Reasoning Depth
Being a 7B parameter model, it lacks the complex logical reasoning required for high-level multi-platform strategy compared to 70B+ models.
Short Output Limit
The 2K max output token limit can truncate complex tool-use responses or detailed reasoning chains in Hermes.
Proprietary Constraints
The proprietary nature and specific training focus on UI mean it can be unpredictable when asked to perform general-purpose reasoning outside of an interface.
Best use cases with Hermes Agent
- Legacy Software Automation — It can ‘see’ and interact with old desktop or web applications that lack modern APIs, enabling Hermes to bridge gaps between platforms.
- Visual Monitoring — Hermes can monitor a dashboard or Slack channel visually and trigger shell commands based on UI changes or specific visual cues.
Not ideal for
- Complex MCP Tool Chaining — The model often struggles to manage the logic required to chain multiple Model Context Protocol tools in a single turn.
- Long-Form Data Synthesis — The 2K output limit prevents the model from generating comprehensive cross-platform summaries or detailed logs across multiple sessions.
Hermes Agent setup
When configuring for Hermes, ensure your screenshot capture resolution is high enough for the model to identify small UI elements, but watch your token usage as image inputs consume context quickly.
Hermes makes custom endpoints easy. Run:
hermes model
Choose Custom endpoint from the menu. Enter the base URL and model identifier when prompted:
- Base URL:
https://api.haimaker.ai/v1 - Model:
bytedance/ui-tars-1.5-7b
Hermes stores the selection and uses it for all subsequent agent runs across whatever platforms you have wired up (Telegram, Discord, Slack, etc.). Tune HERMES_STREAM_READ_TIMEOUT and related env vars if you’re hitting slow providers.
How it compares
- vs Llama 3.1 8B — Llama 3.1 8B is faster for pure text-based tool use, but it lacks the native UI-centric vision capabilities that UI-TARS provides for visual automation.
- vs GPT-4o-mini — GPT-4o-mini offers superior general reasoning and logic for a similar price point, though UI-TARS is more specialized for coordinate-based UI interaction.
Bottom line
UI-TARS 1.5 7B is a niche powerhouse for Hermes Agent users who need to automate visual interfaces on a budget, but it should not be the primary choice for complex reasoning.
For more, see our Hermes local-LLM setup guide.