Current as of April 2026. o4-mini-deep-research is OpenAI’s specialized reasoning model that balances a $2/$8 price point with a massive 100K output limit, making it a powerhouse for Hermes Agent’s autonomous loops.
Specs
| Provider | OpenAI |
| Input cost | $2.00 / M tokens |
| Output cost | $8.00 / M tokens |
| Context window | 200K tokens |
| Max output | 100K tokens |
| Parameters | N/A |
| Features | function_calling, vision, reasoning, web_search |
What it’s good at
Extended Reasoning Cycles
The model performs deep chain-of-thought processing before executing tools, which significantly reduces errors in complex Hermes workflows involving shell commands or MCP protocols.
Massive 100K Output Window
Unlike standard mini models, this version can generate 100,000 tokens in a single response, allowing Hermes to compile exhaustive research reports or complex automation scripts without truncation.
Integrated Web Search
Native web_search capabilities allow the agent to verify real-time data across the internet before posting to platforms like Discord or Slack, ensuring high information accuracy.
Where it falls short
High Output Premium
At $8 per million output tokens, it is over 13 times more expensive than GPT-4o-mini, which can lead to high costs during long-running autonomous sessions.
Latency Overhead
The reasoning phase adds several seconds of delay to every turn, making it less responsive for real-time chat interactions on Telegram or WhatsApp compared to non-reasoning models.
Best use cases with Hermes Agent
- Cross-Platform Research Tasks — Hermes can use the 200K context and web search to monitor Slack, research technical issues, and then deploy fixes via SSH or Modal with high logical consistency.
- Complex Memory Synthesis — The reasoning capabilities excel at analyzing months of persistent cross-session memory to refine the agent’s identity and decision-making logic.
Not ideal for
- Simple Notification Relays — Paying $8/1M for output is wasteful for basic CRUD operations or simple message forwarding where GPT-4o-mini at $0.60/1M suffices.
- High-Speed Command Execution — The time-to-first-token is too slow for users who need immediate feedback for simple shell commands or quick status checks.
Hermes Agent setup
Set the model ID to openai/o4-mini-deep-research and ensure your timeout settings are high enough to accommodate the extended reasoning period before the first token is emitted.
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:
openai/o4-mini-deep-research
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 GPT-4o-mini — GPT-4o-mini is much cheaper at $0.15/$0.60 but lacks the deep reasoning and web search features required for complex autonomous planning.
- vs Claude 3.5 Haiku — Haiku is faster for tool-use and cheaper for output, but it lacks the 100K output ceiling and native web search integration found in o4-mini-deep-research.
- vs o1-mini — o1-mini provides similar reasoning but lacks the ‘Deep Research’ specific optimizations and native search tools that Hermes can leverage for external verification.
Bottom line
This is the best value-to-reasoning model for Hermes users who need deep logic and web-verified automation without paying the $15/$60 premium of flagship models.
TRY O4 MINI DEEP RESEARCH IN HERMES
For more, see our Hermes local-LLM setup guide.