Hermes Routing Policy
AI · · 3 min read
Hermes Routing Policy
This is the default model-routing policy for Hermes jobs.
Principles
- Use the cheapest model that can do the job well.
- Escalate only when the task is ambiguous, high-stakes, long-horizon, or quality-sensitive.
- Never route reminders, trivial formatting, or tiny maintenance tasks through frontier models.
- Use strong premium models for synthesis, planning, and user-facing writing.
- Use explicit fallback chains so rate limits do not break workflows.
Global Defaults
- Default internal worker:
DeepSeek V4 Flash - Default reasoning worker:
DeepSeek V4 Pro - Default premium synthesis:
Claude Opus 4.7 - Default ideation / creative strategy:
GPT-5.4 - Default long-horizon / architecture:
GLM-5.1
Exact Model Assignments by Job Type
1) Daily reminders, alerts, status pings
Use when the job is mostly formatting, sending, or checking a single condition.
- Primary:
gpt-5.4-mini - Fallback 1:
DeepSeek V4 Flash - Fallback 2:
Qwen3.5 Plus
Examples:
- daily reminders
- cron delivery wrappers
- threshold alerts
- healthcheck notifications
- simple summaries with no deep synthesis
2) Knowledge-base ingest, extraction, and cleanup
Use when the job is mostly parsing, deduping, or summarizing source material.
- Primary:
DeepSeek V4 Flash - Fallback 1:
Qwen3.6 Plus - Fallback 2:
DeepSeek V4 Pro
Examples:
- URL ingest
- article capture
- transcript cleanup
- note normalization
- metadata extraction
3) User research / market research / article synthesis
Use when the job needs synthesis across messy inputs and judgment.
- Primary:
Claude Opus 4.7 - Fallback 1:
Kimi K2.6 - Fallback 2:
DeepSeek V4 Pro
Examples:
- research briefings
- competitor analysis
- product discovery
- source comparison
- “what does this mean?” tasks
4) Brainstorming / ideation / naming / product strategy
Use when the job needs breadth, taste, and non-obvious alternatives.
- Primary:
GPT-5.4 - Fallback 1:
Claude Opus 4.7 - Fallback 2:
Qwen3.6 Plus
Examples:
- feature ideation
- naming
- product positioning
- content hooks
- strategic options
5) Coding, implementation, and normal agentic workflows
Use when the job is a real build task but not yet a huge refactor.
- Primary:
DeepSeek V4 Pro - Fallback 1:
Kimi K2.6 - Fallback 2:
DeepSeek V4 Flash
Examples:
- feature implementation
- bug fixes across a few files
- terminal-heavy automation
- standard agent workflows
- code review and PR feedback
6) Large refactors, architecture, long autonomous runs
Use when the task spans many files, requires deep planning, or runs for hours.
- Primary:
Kimi K2.6 - Fallback 1:
GLM-5.1 - Fallback 2:
Claude Opus 4.7
Examples:
- multi-file refactors
- architecture decisions
- long-horizon autonomous runs
- complex orchestration
- agent-swarm style coordination
7) Debugging and terminal-heavy automation
Use when the task is exploratory and changes direction a lot.
- Primary:
Qwen3.6 Plus - Fallback 1:
DeepSeek V4 Pro - Fallback 2:
DeepSeek V4 Flash
Examples:
- runtime debugging
- script repairs
- log analysis
- environment troubleshooting
- cron job recovery
8) Multimodal / screenshot-to-code / visual reasoning
Use when the task involves images, UI screenshots, or mixed modalities.
- Primary:
MiMo-V2-Omni - Fallback 1:
GPT-5.4 - Fallback 2:
Claude Opus 4.7
Examples:
- screenshot-to-code
- UI audits
- visual debugging
- mixed image + text reasoning
Hermes Job Routing Rules
Internal ops
- Use
DeepSeek V4 Flashby default. - Escalate to
DeepSeek V4 Proonly when the job spans multiple steps or depends on uncertain interpretation.
User-facing synthesis
- Use
Claude Opus 4.7orGPT-5.4. - Do not use flash-tier models for polished external writing unless it is truly trivial.
Research
- Start with
Claude Opus 4.7. - If the task is broad or long-horizon, escalate to
Kimi K2.6. - If the task is price-sensitive but still analytical, use
DeepSeek V4 Pro.
Code work
- Start with
DeepSeek V4 Pro. - Escalate to
Kimi K2.6for refactors or complex orchestration. - Use
DeepSeek V4 Flashfor tiny fixes and mechanical edits.
Reminders and simple notifications
- Keep on
gpt-5.4-miniorDeepSeek V4 Flash. - Never spend premium reasoning on routine delivery.
Suggested Hermes Defaults
If you want a simple universal setup:
- Default Hermes model:
gpt-5.4-mini - Default worker for automation:
DeepSeek V4 Flash - Default research model:
Claude Opus 4.7 - Default coding model:
DeepSeek V4 Pro - Default architecture model:
Kimi K2.6
Fallback Discipline
Use this fallback order whenever a job fails because of rate limits or weak output:
- Primary model
- Fallback 1
- Fallback 2
- Degrade to a smaller model only if the task is mechanical
Do not keep retrying the same model after a 429, 503, or clearly bad-output loop.