GLM-5 API for Hermes Agent: Reasoning, Coding, and Tools
GLM-5 is a general purpose model for Hermes Agent. It is a practical starting point when a task needs reasoning, code, and tool calls but does not require a specialist visual or persistent workflow model.
These facts show where GLM-5 fits inside Hermes and which details change the cost and review path.
InputText
OutputText
Best roleMain Agent or router
ToolsFunction calls and structured output
Price noteUse the current Hermes API price card
Typical jobResearch, coding, triage, and tool calls
Where to be careful
It is a general model, not a specialist vision model.
A long task still needs a stop condition and a verification step.
Do not let it change production data without an approval gate.
Before you let the Agent run
Define the output format before the first tool call.
Allow only the tools needed for this request.
Ask for sources, tests, or a confidence note.
Route specialist work instead of forcing one model to do everything.
Start with the general model, then route by evidence.
01
Use it for balanced work
Research, coding, tool calls, structured answers, and tasks that do not need a specialist model.
02
Do not use it for every extreme case
For visual coding, persistent OpenClaw tasks, or huge repositories, use the model built for that job.
03
A simple GLM-5 routing rule
Start with GLM-5 for bounded work. Route visual tasks to GLM-5V-Turbo, persistent tool chains to GLM-5-Turbo, and project scale coding to GLM-5.2 or GLM-5.3.
Good Hermes tasks
Match the job to the model role
The same GLM family can play different roles. Use this table before you route a task.
01
Research and synthesis
Search approved sources, compare findings, and return a clear answer with evidence.
02
Everyday coding
Implement a bounded change, run checks, and explain the result.
03
Structured operations
Classify requests, call a tool, and return JSON for the next workflow step.
04
Model routing
Read the task and decide whether a specialist model should handle the next step.
A user needs a clear answerGLM-5 as the main Agent
It can research, explain, and return a structured answer.
A request needs one or two toolsGLM-5 with a small tool set
Keep the tool list short so the Agent can verify each result.
The next step is visual or project-wideRoute to GLM-5V-Turbo or GLM-5.2
A specialist model will see more of the required state.
Hermes workflow
GLM-5 is a useful default, not a permanent lock in.
Hermes can begin with GLM-5, measure what the task needs, and route visual, long context, or persistent work to a specialist model.
01 · Understand
Read the request and identify the goal, data, tools, and risk.
02 · Act
Complete the bounded task with the available tools.
03 · Check
Return structured output, tests, sources, or uncertainty.
04 · Route
Move the next step to a more specialized model if needed.
Practical case
A small team uses GLM-5 to triage support requests
Hermes receives customer requests from several channels. GLM-5 classifies each request, extracts the product and urgency, checks the internal help tool, and returns a structured record. Requests that require a screenshot go to GLM-5V-Turbo. Requests that require a large repository change go to GLM-5.2. Hermes keeps the first model as the low friction entry point and routes only the work that needs more capability.
What Hermes does in this case
01Brief
Hermes receives a support request and the customer record.
02Triage
GLM-5 extracts the product, urgency, language, and missing facts.
03Tool check
Hermes calls the approved help-center and account tools.
04Route
Visual bugs go to GLM-5V-Turbo; repository changes go to GLM-5.2.
Result
The team keeps GLM-5 as the low-friction first step and pays for specialist models only when the request needs them.
Human check
A person checks refunds, account changes, policy exceptions, and any reply that could create a legal or financial commitment.
Cost decision
Use GLM-5 as the balanced starting point.
A general model is useful when the task shape is not known yet. Once Hermes sees repeated patterns, route those patterns to a cheaper or more specialized model.
A simple cost example
For a short support request, keep the prompt small and use GLM-5 once. If the same request pattern repeats, move extraction to a lower-cost model and keep GLM-5 for the uncertain cases.
Use GLM-5 in Hermes
Use GLM-5 in Hermes
Select glm-5, define the output format, and give Hermes a clear rule for when to route the next step to another model.
curl https://api.hermes-ai.net/api/v1/chat/completions \
-H "Authorization: Bearer $HERMES_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5",
"messages": [{"role":"user","content":"Run the approved task and return a short verification report."}]
}'
FAQ
Before you route GLM-5 through Hermes
Is GLM-5 a good default model for Hermes?
It is a balanced starting point for research, coding, structured output, and tool calls. Move repeated or specialist work to a model that is cheaper or better matched.
Can GLM-5 call tools safely?
Yes, but Hermes should expose only the tools needed for the request and require a verification result before accepting side effects.
How is GLM-5 different from GLM-5.1 and GLM-5.2?
GLM-5 is the general starting point. GLM-5.1 is better for long execution loops, while GLM-5.2 is better when many files and project decisions must stay aligned.
Is GLM-5 suitable for a long autonomous coding run?
It can handle a bounded run, but longer work benefits from GLM-5.1 or GLM-5.2 plus explicit checkpoints, tests, and stop conditions.
When is a cheaper model enough?
Use a smaller model for simple extraction, classification, and short answers. Keep GLM-5 for tasks where reasoning or tool selection changes the result.
