- February 11, 2026
- 2 min read
GLM-5: The Open-Source Model for Production-Grade Coding Agents
- We’re bringing Day-0 GLM-5 support to FriendliAI Serverless Endpoints—so you can deploy production-grade coding agents with low latency and high throughput
- Powered by FriendliAI’s optimized inference engine for long-horizon agent workflows, deep backend debugging, and Opus-level reasoning
- One-click deployment with autoscaling, LoRA, and quantization—built for real production workloads
The FriendliAI team is continuing our partnership with Z.ai, to offer Day 0 support for GLM-5. The most advanced open-source foundation model built for complex systems engineering and long-horizon agent workflows is now available on Friendli Serverless Endpoints.
GLM-5’s Advancements
GLM-5 introduces new features that strengthen its abilities to reason, execute long-horizon agentic tasks, and write frontend or backend code:
- Agentic long-horizon planning and execution: GLM-5 is purpose-built for multi-stage, long-step complex tasks. It can autonomously decompose system-level requirements with an architect-level approach, while maintaining context coherence and goal alignment across automated workflows that run for hours.
- Backend refactoring and deep debugging: GLM-5 demonstrates strong depth reasoning in backend architecture design, complex algorithm implementation, and difficult bug resolution. It includes robust self-reflection and error correction mechanisms, enabling it to analyze logs, identify root causes, and iteratively fix issues after compilation or runtime failures until the system runs end-to-end.
- Automation of Knowledge Work with Office by Z.ai: GLM-5 can turn text or source materials directly into .docx, .pdf, and .xlsx files—PRDs, lesson plans, exams, spreadsheets, financial reports, run sheets, menus, and more—delivered end-to-end as ready-to-use documents. It supports multi-turn collaboration and turning outputs into real deliverables.
- An open-source alternative with Opus-level intelligence: GLM-5 directly benchmarks against Claude Opus 4.5 in code logic density and systems engineering capability, while providing open-source deployment flexibility and strong cost efficiency.
As a result, GLM-5 delivers production-grade productivity and performance gains beyond GLM-4.7, comparable with top closed-source alternatives, like Claude Opus 4.5.
In a world with Claude Code and OpenClaw, developers desperately need an open-source model that can build complex systems and power agentic applications, not just write code. That’s why FriendliAI serves GLM-5 with the lowest latency, highest throughput, and compute efficiency.
Large Model, Efficient Architecture
GLM-5 is an MIT-licensed large multimodal model pre-trained with 740 billion total parameters, 40 billion active parameters, and 28.5 trillion tokens of data. Its Mixture of Experts (MoE) architecture enables the model to retain proper context across multi-turn conversations or tasks, optimizing token utilization.
DeepSeek Sparse Attention (DSA) helps GLM-5 determine which tokens to prioritize during inference. It adapts the sparsity pattern based on input content to balance efficiency with accuracy. The team at Z.ai also incorporated slime into GLM-5, a novel asynchronous reinforcement learning infrastructure that substantially improves training throughput and efficiency for more fine-grained post-training iterations.
One-Click Deployment for GLM-5
Deploy GLM-5 with one click on FriendliAI:
- Create your Friendli Serverless Endpoint
- Configure your model and compute instances
- Enable (or disable) LoRA adapters, quantization, autoscaling, and engine configurations
API calls can be made for $1.00 per million input tokens and $3.20 per million output tokens.
Written by
FriendliAI Tech & Research
Share
General FAQ
What is FriendliAI?
FriendliAI is the Frontier Inference Cloud for Agents, delivering high throughput, low latency, and reliability at scale for agentic workloads. Through vertically optimized inference infrastructure, it delivers 2–5× faster output token speed and a 99.99% uptime SLA for high-volume production traffic.
How does FriendliAI reduce inference costs?
FriendliAI reduces inference costs through higher GPU utilization and optimized inference performance. FriendliAI's patented continuous batching technique, along with quantization, speculative decoding, KV cache offloading, multi-LoRA serving, and autoscaling, helps you serve more tokens with fewer GPUs, lowering your infrastructure costs without sacrificing performance.
Why should I choose FriendliAI over other inference providers?
FriendliAI is built for production AI agents, combining speed, reliability, and efficiency at scale. It delivers low-latency streaming, reliable long-context inference, and robust tool calling without compromising stability. According to independent OpenRouter benchmarks, FriendliAI consistently ranks among the top providers for throughput, latency, and reliability across leading open-weight models. See why customers choose FriendliAI
Which open-weight models does FriendliAI support?
Run today’s frontier open-weight models—including GLM, MiniMax, Kimi, DeepSeek, Qwen, Gemma, and more—with a simple API call. FriendliAI Model API gives you instant access to the latest models with optimized inference performance for production workloads. Explore models and pricing
How do I get started?
Getting started takes just a few minutes. [1] Sign up for FriendliAI, [2] Generate your API key, and [3] Make your first inference request with frontier open-weight models.
Still have questions?
If you want a customized solution for that key issue that is slowing your growth, support@friendli.ai or click Talk to an engineer — our engineers (not a bot) will reply within one business day.
