GLM-5.1

glm-5.1

GLM-5.1 is described as a major upgrade for coding, long-horizon tasks, and agentic engineering. Source materials emphasize the ability to plan, execute, and improve work over extended periods, producing more complete engineering-grade results. It should be positioned as a developer and agent model for sustained software work rather than a general Q&A model.

Context Window

200K tokens

Maximum Output

131.1K tokens

Release Date

Mar 27, 2026

Modalities

GLM-5.1 Pricing

Token Tier	Input Price	Output Price	Cache Read	Cache Create 5m	Cache Read 5m
<=32K	$0.8571/M	$3.4286/M	$0.1714/M	$1.0714/M	$0.0857/M
>32K	$1.1429/M	$4/M	$0.2286/M	$1.4286/M	$0.1143/M

GLM-5.1 API Capabilities

Reasoning

Supported

Tool calling

Supported

Temperature parameter

Supported

Attachments

Not supported

Knowledge Base

—

Endpoint Protocols

Completions APIMessages APIgemini

GLM-5.1 Model Highlights

GLM-5.1 is a text-only flagship model built for sustained autonomous execution, agentic engineering and complex repository or terminal tasks.

Sustained Autonomous Execution

Can work autonomously on a single task for up to eight hours, covering planning, execution, iterative optimization and final delivery.

Agentic Engineering

Improved coding and sustained execution support autonomous agents that must plan, implement, evaluate and revise engineering work.

Repository and Terminal Reasoning

Handles repository generation and real-world terminal workloads that require understanding project structure and execution feedback.

GLM-5.1 Use Cases

GLM-5.1 is suited to extended coding-agent sessions, repository construction and iterative engineering optimization driven by execution feedback.

Autonomous Feature Development

Plan and implement a substantial feature over a long session, run checks and refine the result until it meets the stated requirements.

Repository Generation

Translate a software specification into a multi-file repository with coherent architecture, implementation and supporting configuration.

Terminal-Driven Optimization

Run commands, inspect errors or benchmark results and repeatedly revise an implementation to improve correctness or performance.

How to Use GLM-5.1 via the TokenHub API

Create API key

import OpenAI from "openai"

const client = new OpenAI({
  apiKey: process.env.TOKENHUB_API_KEY,
  baseURL: "https://us-api.tokenhub.com/v1",
})

const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)

GLM-5.1 Benchmarks

Index score
Artificial Analysis Intelligence IndexArtificial Analysis Intelligence Index summarizes broad model capability across evaluation families.	Artificial Analysis broad capability aggregate	40.2
Artificial Analysis Coding IndexArtificial Analysis Coding Index summarizes model performance on coding and software engineering tasks.	Artificial Analysis software task aggregate	43.4
Knowledge & Reasoning
GPQAGPQA is a graduate-level science benchmark designed to test expert reasoning.	Advanced science problem solving	86.8%
HLEHLE is a broad, challenging benchmark for expert-level knowledge and reasoning across many domains.	Broad expert-level exam set	28.0%
Coding & Engineering
SciCodeSciCode evaluates Python programming for scientific computing, including algorithmic implementation from scientific context.	Scientific coding challenges	43.8%
Terminal-Bench HardTerminal-Bench Hard evaluates whether an AI agent can complete difficult tasks in a terminal environment.	Hard terminal task execution	43.2%
Instruction Following & Agent Tasks
IFBenchIFBench measures how reliably a model follows detailed instructions and constraints.	Prompt constraint adherence	76.3%
AA-LCRAA-LCR measures reasoning quality over extended context windows.	Long-context reasoning	62.3%
τ²-Benchτ²-Bench evaluates conversational agents in realistic workflows with tool and state constraints.	Agent workflow tasks	97.7%

Metrics sourced from Artificial Analysis

GLM-5.1 FAQ

GLM-5.1: capabilities, use cases, limits, and TokenHub guidance.

How should teams view GLM-5.1?+

GLM-5.1 is a Z.AI model for sustained autonomous engineering and iterative delivery.

What is GLM-5.1 best for?+

Best for iterative engineering delivery, complex coding and tool-heavy automation, especially when reliable multi-step execution is the priority.

What is GLM-5.1's main strength?+

Key strength: sustained autonomous planning, execution, testing, and refinement.

Is GLM-5.1 always the best choice?+

It belongs to an older generation and may lack newer capabilities. For the latest capabilities matter, consider GLM-5.2.

What is the safest setup?+

Use the exact ID shown by TokenHub; follow your account docs and verify current features.

Ready to use GLM-5.1?

Use one API key to access GLM-5.1 and more AI models through TokenHub.

Create API key

GLM-5.1

GLM-5.1 Pricing

GLM-5.1 API Capabilities

GLM-5.1 Model Highlights

Sustained Autonomous Execution

Agentic Engineering

Repository and Terminal Reasoning

GLM-5.1 Use Cases

Autonomous Feature Development

Repository Generation

Terminal-Driven Optimization

How to Use GLM-5.1 via the TokenHub API

GLM-5.1 Benchmarks

Models Similar to GLM-5.1

Media and Discussions

X (Twitter)

Reddit

YouTube

GLM-5.1 FAQ

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