Z.ai
GLM-5.3-FlashX
glm-5.3-flashx
Total Context
1M
Max Output
131.1K
Released
N/A
Input$0.2857 / M tokens
Output$1 / M tokens
GLM-5.1
glm-5.1GLM-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
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 Index | Artificial Analysis broad capability aggregate | 40.2 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 43.4 |
| Knowledge & Reasoning | ||
| GPQA | Advanced science problem solving | 86.8% |
| HLE | Broad expert-level exam set | 28.0% |
| Coding & Engineering | ||
| SciCode | Scientific coding challenges | 43.8% |
| Terminal-Bench Hard | Hard terminal task execution | 43.2% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 76.3% |
| AA-LCR | Long-context reasoning | 62.3% |
| τ²-Bench | 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.
Media and Discussions
Selected public videos and posts related to this model.
X (Twitter)
Z.ai ·
Introducing GLM-5.1: The Next Level of Open Source - Top-Tier Performance: #1 in open source and #3 globally across SWE-Bench Pro, Terminal-Bench, and NL2Repo. - Built for Long-Horizon Tasks: Runs autonomously for 8 hours, refining strategies through thousands of iterations. https://t.co/YQZLhKVwik
https://pbs.twimg.com/media/HFUF9iPakAAr0Og.jpgView originalZ.ai ·
GLM-5.1 is available to ALL GLM Coding Plan users! https://t.co/E63z53nXOX https://t.co/75l0sGGt1W
https://pbs.twimg.com/media/HEacaB4XkAAFtLt.jpgView originalZ.ai ·
The "triple usage" period for GLM-5.1 and GLM-5-Turbo is now extended to June 30. Availability: Anytime except 2-6 AM ET.
View originalReddit
GLM 5.1: pretty decent
View originalGLM 5.1 crushes every other model except Opus in agentic benchmark at about 1/3 of the Opus cost
zylskysniper ·
Read full post
r/LocalLLaMA - GLM 5.1 crushes every other model except Opus in agentic benchmark at about 1/3 of the Opus cost (https://preview.redd.it/glm-5-1-crushes-every-other-model-except-opus-in-agentic-v0-s9lg647zjeug1.png?width=1161&format=png&auto=webp&s=21c2689967a3e24aad9fecd4292950ed7118b7bf) I want to know whether GLM is another benchmark optimized model or actually useful in agents like OpenClaw, so I tested GLM 5.1 in our agentic benchmark. Turns out it reaches Opus 4.6 level performance with just 1/3 of the cost (~$0.4 per run vs ~$1.2 per run) based on my tests. It outperforms all other models tested. Pushes the cost effectiveness frontier quite a bit. I don't quite trust any static benchmarks, seen many models optimized for it, ranking high on those leaderboard but not working well in real agentic tasks. So we uses OpenClaw to test the agentic performance of models in real environment + real tasks (user submitted). Chatbot Arena/LMArena style battle, LLM as judge. Based on the result, I would say GLM 5.1 is one of the top models for OpenClaw type of agents now. Qwen 3.6 also did a good job, but it does not support prompt caching yet (on openrouter) so the current price is inflated. With prompt caching I except it to reach minimax m2.7 level cost per run and becomes another great choice for cost effectiveness. Full leaderboard, cost-effectiveness analysis, and methodology can be found at https://app.uniclaw.ai/arena?via=reddit . Strongly recommend submitting your own task and see how different models on it. [Edit 1] It seems many people confused price per token and price per task. GLM 5.1 price per token is < 1/5 of Opus. But GLM also uses about 2x token per task compared to Opus, on the same task, based on our benchmark. Reason is that GLM uses tools aggressively, more than 2x tool calls per task compared to Opus. That's why the actual cost per task is about 1/3 of Opus.
GLM 5.1 sits alongside frontier models in my social reasoning benchmark
cjami ·
View originalYouTube
The Only GLM 5.1 Review You Need To Watch
BridgeMind
View originalI Tried NEW GLM-5.1 on a Longer Task (compared to Opus 4.6)
AI Coding Daily
View originalDeepSeek V4 vs Kimi K2.6 vs GLM-5.1: Which One Should Your Business Actually Use #ai
Raheel Malik | AI
View original