Z.AI · Hermes 모델 가이드

GLM-5.1 API를 Hermes Agent에서 사용하기

GLM-5.1 is designed for work that takes more than a few turns. Hermes can give it a goal, a project, tools, and a way to verify progress while it plans, builds, tests, and improves the result.

Playground 열기 →대시보드 열기 →

GLM 모델 작업, 파일, 도구, 사람의 확인을 연결하는 Hermes Agent 워크플로

Hermes에서 확인할 기술 정보

Long horizon coding agent

These facts show where GLM-5.1 fits inside Hermes and which details change the cost and review path.

InputText, repository context, and tool state

OutputText, code, and tool calls

Best roleLong-horizon coding Agent

ToolsShell, tests, browser, and project tools

Price noteBudget by run and verification round

Typical jobMigration, optimization, and sustained delivery

주의할 점

A long run can drift if the goal and stop conditions are vague.
Every improvement needs a measurement, not only a confident explanation.
Production release still needs a human owner.

Agent 실행 전 확인

Write a measurable definition of done.
Keep a small change boundary for each round.
Save benchmark and test output after every round.
Stop when the goal is met or the budget is reached.

모델 이름이 아니라 작업에 맞춰 선택하세요.

Use it for sustained execution

Complex engineering, autonomous optimization, production grade builds, and repeated test and fix loops.

Do not use it for a quick draft

Short copy, simple questions, and small edits do not need a model built for long execution.

A simple GLM-5.1 routing rule

Use GLM-5.1 when the task has a clear goal but needs many rounds of execution and improvement. Use GLM-5.2 for broader project context or GLM-5.3 for the hardest decisions.

Hermes에 맞는 작업

일에 맞는 모델 역할 선택

같은 GLM 제품군도 맡는 역할은 다릅니다. 작업을 먼저 보고 라우팅하세요.

Autonomous feature build

Move from requirements to implementation, tests, fixes, and a delivery report.

Performance optimization

Run a benchmark, inspect the result, change the code, and measure the next run.

Engineering migration

Plan a migration, update dependent files, run checks, and list remaining risks.

Complex research build

Turn a paper or data source into a runnable project with repeatable verification.

The change needs many build-test-fix roundsGLM-5.1 as the execution Agent

It keeps the goal visible while the work continues.

The task is a large repository mapUse GLM-5.2 first

Project-wide context is the main bottleneck.

The task is a difficult final decisionAsk GLM-5.3 or a human reviewer

A deeper review is safer than another open-ended run.

Hermes 워크플로

The goal stays visible while the model works.

Hermes should save the goal, current progress, tests, and stop conditions. GLM-5.1 can continue the work, but it still needs clear boundaries and human approval for important releases.

01 · Set the goal

Define the outcome, tools, limits, tests, and what counts as done.

02 · Run the loop

Plan, implement, test, inspect, and adjust the next step.

03 · Track progress

Hermes records completed work, failed attempts, and open risks.

04 · Deliver

The model prepares the result and a human approves production release.

Practical case

A performance task improves through repeated measurement

A team asks Hermes to improve a slow data pipeline without changing its public API. GLM-5.1 maps the pipeline, creates a baseline benchmark, identifies a bottleneck, implements a change, and runs the benchmark again. Hermes keeps the results of every round. If a change improves speed but breaks a test, the model must fix the regression before continuing. The final delivery includes the code, benchmark results, and unresolved risks.

이 사례에서 Hermes가 하는 일

01Baseline

Hermes records the current test and performance result.

02Change

GLM-5.1 edits one bounded part of the pipeline.

03Measure

Hermes reruns the benchmark and compares the result.

04Repeat

The next round is allowed only when tests still pass.

결과

The final delivery includes code, measurements, passed checks, and the risks that remain open.

사람의 검토

A person approves changes to production systems, data migrations, security rules, and release decisions.

비용 판단

Use GLM-5.1 when restarts cost more than tokens.

Long tasks can use many tokens. The benefit is fewer manual restarts and better continuity across planning, tests, and fixes. For small tasks, choose a cheaper model and keep the workflow short.

간단한 비용 예시

A long task may use many tokens, but it can still be cheaper than restarting a complex engineering job by hand after every failed attempt.

Use GLM-5.1 in Hermes

Select glm-5.1, define the goal and stop conditions, and require a progress report after each meaningful execution phase.

Playground 열기 →API Key 받기 →

curl https://api.hermes-ai.net/api/v1/chat/completions \
  -H "Authorization: Bearer $HERMES_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.1",
    "messages": [{"role":"user","content":"Run the approved task and return a short verification report."}]
  }'

FAQ

자주 묻는 질문

What makes GLM-5.1 different from a normal coding model?

It is designed for sustained work: planning, implementation, testing, fixing, and delivery across many steps.

Can it work without supervision?

Hermes can let it continue, but production changes, sensitive actions, and final release still need human approval.

How do I stop an endless task?

Set a budget, a time limit, a test goal, and explicit stop conditions in the Hermes task brief.

Is it useful for performance work?

Yes. A benchmark and a repeatable test loop make its optimization workflow easier to measure.

When should I use GLM-5.2?

Use GLM-5.2 when the task depends on understanding a large project context or many cross file decisions.

공식 문서 보기 ↗Playground 열기 ↗

HERMES API · GLM-5.1

Use GLM-5.1 in Hermes

Select glm-5.1, define the goal and stop conditions, and require a progress report after each meaningful execution phase.

Playground 열기 →대시보드 열기 →