---
title: "GLM-4.7 for Hermes Agent: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using GLM-4.7 with Hermes Agent. Costs $0.39/M input, $1.75/M output. 203K context window. Here's when to use it and when to pick something else."
date: 2026-04-17
updatedDate: 2026-04-17
image: /images/models/provider-z-ai-hero.jpg
keywords: "glm-4.7 hermes, glm-4.7 pricing, glm-4.7 review, zhipu ai hermes, glm-4.7 api"
category: model-guide
modelData:
  provider: "Zhipu AI"
  provider_slug: "z-ai"
  full_id: "z-ai/glm-4.7"
  input_cost_per_1m: 0.39
  output_cost_per_1m: 1.75
  max_input_tokens: 202752
  max_output_tokens: 64000
  features: ["function_calling", "vision", "reasoning"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What is the cost per million tokens?"
    answer: "Input costs $0.39 per million tokens and output costs $1.75 per million tokens."
  - question: "How much context can it handle?"
    answer: "It supports a 203K token context window, which is ample for Hermes' cross-session memory."
  - question: "Does it support vision for Hermes?"
    answer: "Yes, it includes vision features, allowing Hermes to analyze images or screenshots shared across messaging platforms."
---

Current as of April 2026. GLM-4.7 from Zhipu AI is a budget-focused powerhouse for Hermes Agent deployments that need high throughput without the OpenAI price tag. It handles the 203K context window surprisingly well for long-running autonomous sessions across Slack and Discord.

## Specs

| | |
|---|---|
| **Provider** | Zhipu AI |
| **Input cost** | $0.39 / M tokens |
| **Output cost** | $1.75 / M tokens |
| **Context window** | 203K tokens |
| **Max output** | 64K tokens |
| **Parameters** | N/A |
| **Features** | function_calling, vision, reasoning |

## What it's good at

#### Aggressive Pricing

At $0.39 per million input tokens, it is significantly cheaper than GPT-4o while maintaining solid tool-use reliability for Hermes' 47 built-in functions.

#### Massive Context Window

The 203K context window allows Hermes to maintain deep persistent memory across weeks of cross-platform messaging history without losing the thread.

## Where it falls short

#### Latency Variability

Since Zhipu's infrastructure is based in China, users outside the region may experience higher latency spikes compared to US-based providers.

#### MCP Protocol Nuances

It sometimes struggles with complex nested MCP tool calls compared to Claude 3.5 Sonnet, occasionally requiring more explicit system prompting in Hermes.

## Best use cases with Hermes Agent

- **High-Volume Messaging Automation** — The low cost offsets the high token usage of continuous polling and history retrieval across 15+ messaging platforms.
- **Long-Term Memory Tasks** — The 203K context window and closed learning loop in Hermes benefit from its ability to ingest massive amounts of previous session data.

## Not ideal for

- **Real-time Low Latency Critical Apps** — Network hops to Zhipu's servers can introduce a 1-2 second delay that might annoy users on snappy platforms like Telegram.
- **High-Stakes Financial Tooling** — Its function calling can occasionally hallucinate parameters when juggling more than 10 tools at once in a single prompt.

## Hermes Agent setup

Use the OpenAI-compatible endpoint provided by Zhipu BigModel API. Ensure your API key is correctly mapped and the model ID is set to z-ai/glm-4.7 in your Hermes configuration file.

Hermes makes custom endpoints easy. Run:

```bash
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:** `z-ai/glm-4.7`

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** — GLM-4.7 offers a much larger 203K context window compared to GPT-4o-mini's 128K, making it better for Hermes' persistent memory features.
- **vs DeepSeek-V3** — DeepSeek is often cheaper for raw throughput, but GLM-4.7's 64K output limit gives it an edge for complex multi-platform reporting.

## Bottom line

GLM-4.7 is the go-to choice for Hermes users who need a massive 203K context window and reliable tool-use at a fraction of the cost of Western flagship models.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=hermes_glm-4.7" class="cta-button">TRY GLM-4.7 IN HERMES</a>

---

*For more, see our [Hermes local-LLM setup guide](https://hermes-agent.nousresearch.com/docs/guides/local-llm-on-mac).*