Overview
GLM-5-Turbo is Z.ai's proprietary, execution-focused variant of GLM-5, released on March 15, 2026. Where GLM-5 was designed as a broad open-source flagship for coding and reasoning, GLM-5-Turbo is purpose-built for AI agent workflows—specifically OpenClaw-style tasks involving tool use, long-chain execution, and persistent automation. The model has been optimized at the training data and objective level for real-world agent scenarios, rather than retrofitted from a general-purpose base. It supports a 200K context window and up to 128K output tokens, and is available via API and GLM Coding subscriptions.
What's New
Tool Call Reliability
GLM-5-Turbo's most measurable operational improvement over GLM-5 is tool invocation reliability. Officially, Z.ai describes GLM-5-Turbo as strengthening tool and Skills integration for more stable multi-step execution in OpenClaw workflows. For multi-step AI agent pipelines that depend on sequential tool calls, the difference compounds significantly: For multi-step agent pipelines, the practical implication is improved stability across sequential tool invocations. This makes GLM-5-Turbo materially better suited for production agent systems where reliability across extended task sequences matters.
Faster End-to-End Completion
Z.ai officially positions GLM-5-Turbo as delivering faster and more stable execution for high-throughput long-chain tasks. Its positioning emphasizes stable completion on long-chain workloads rather than chat-first responsiveness but well-suited for batch agent tasks where throughput at 48 tokens per second is the relevant metric. The tradeoff is deliberate: the model prioritizes stable, complete task execution over fast initial response.
Scheduled and Persistent Task Support
GLM-5-Turbo has been specifically trained on scenarios involving scheduled triggers, continuous execution, and long-running tasks. It better understands time-related requirements (e.g., "run this every hour" or "continue until the file is processed") and maintains execution continuity through complex, multi-turn agent sessions. This addresses one of the most common failure modes in production agents: tasks that start correctly but lose coherence across extended runs.
Complex Instruction Decomposition
The model demonstrates improved comprehension for multi-layered, hierarchical instructions—decomposing nested objectives into executable steps, correctly identifying priorities, and coordinating task division across multiple agents. This is particularly relevant for enterprise deployments where instructions from non-technical users must be reliably translated into structured agent workflows.
MCP Tool Integration
GLM-5-Turbo natively integrates with Model Context Protocol (MCP) tools and external data sources, expanding agent capabilities beyond the model's built-in knowledge. Developers can connect databases, APIs, file systems, and third-party services as MCP tools, which the model can discover, invoke, and chain across tasks. This positions it as a strong foundation for OpenClaw-style autonomous systems that require access to live data and external services.
ZClawBench Results
Z.ai's internal ZClawBench benchmark evaluates end-to-end agent performance across task types that Z.ai describes as including environment setup, software development, information retrieval, data analysis, and content creation. GLM-5-Turbo outperforms GLM-5 across all five categories on this benchmark, with the most substantial gains in high-throughput data processing and multi-step automation scenarios.
Availability & Access
GLM-5-Turbo is a proprietary, closed-source model—unlike GLM-5, it is not available as open weights.
API Access
Available immediately on OpenRouter and through Z.ai's direct API (glm-5-turbo model identifier). No waitlist required for API access.
GLM Coding Subscription Rollout
- Pro subscribers ($81/quarter): Expected by the end of March 2026
- Lite subscribers ($27/quarter): Expected sometime in April 2026
- Max subscribers ($216/quarter): Access available immediately
- Enterprise early access via Google Form application (capacity-dependent)
Open-Source Availability
GLM-5-Turbo itself is proprietary; developers who need open weights today should use GLM-5 instead, but GLM-5-Turbo itself will remain proprietary.
Pricing & Plans
Z.ai API (Direct)
| Model | Input | Cached Input | Output |
|---|---|---|---|
| GLM-5-Turbo | $1.20/1M | $0.24/1M | $4.00/1M |
| GLM-5 (comparison) | $1.00/1M | $0.20/1M | $3.20/1M |
Cached input pricing enables cost reduction for repeated context (e.g., persistent system prompts). Cache storage is free during the limited-time promotional period.
OpenRouter
Available at $0.96/1M input and $3.20/1M output tokens through OpenRouter's routing.
GLM Coding Subscription
- Lite: $27/quarter (~$9/month)
- Pro: $81/quarter (~$27/month)
- Max: $216/quarter (~$72/month)
Each tier includes quota for GLM-5-Turbo usage alongside other Z.ai models. Higher tiers receive priority access and larger quotas. GLM-5-Turbo requests consume more quota than earlier model versions.
Best For
- Enterprise developers building multi-step OpenClaw agents that require reliable tool invocation across extended task chains
- Automation engineers deploying scheduled or persistent agents for data processing, file operations, and workflow orchestration
- Teams using MCP-compatible tools who need a model that can reliably discover, invoke, and chain external services
- Developers prioritizing completion stability over first-token speed for batch processing or background agent tasks
- Max GLM Coding subscribers, and Pro subscribers once rollout is complete, looking for a more reliable model for Claude Code or Kilo Code integration
- Organizations on API budgets seeking agent-optimized performance at below-$5/1M total token cost
FAQ
How does GLM-5-Turbo differ from GLM-5 in practical use?
The most significant practical difference in Z.ai's official materials is stronger support for stable tool use, timed and persistent tasks, and long-chain OpenClaw execution. For multi-step agents running 10+ tool calls per session, this reduces chain-level failures substantially. GLM-5-Turbo also completes tasks faster end-to-end (8.16s vs. 9.34–11.23s), though its first-token latency is higher. If you're building agents rather than chat interfaces, GLM-5-Turbo is the better choice. If you need open-source weights or lower first-token latency, GLM-5 remains available.
Can GLM-5-Turbo be used with Claude Code, Kilo Code, or Roo Code?
Yes. GLM-5-Turbo is accessible through OpenAI-compatible API endpoints (Z.ai API and OpenRouter), making it compatible with any coding agent framework that supports custom model endpoints. Set the base_url to Z.ai's API endpoint and the model to glm-5-turbo. GLM Coding subscription users on Max plans can access it now; Pro support is expected by the end of March 2026, and Lite support sometime in April 2026.
What is ZClawBench and how reliable are the results?
ZClawBench is Z.ai's internal benchmark for end-to-end AI agent performance across five task categories: information search, office tasks, data analysis, development and operations, and automation. The benchmark was designed based on analysis of real OpenClaw use cases. Results show GLM-5-Turbo outperforming GLM-5 across all categories—but these are company-supplied evaluations without independent third-party validation. OpenRouter's deployment telemetry (tool call error rates, throughput, latency) provides more independently observable data points.
Will GLM-5-Turbo weights be released as open source?
Z.ai has stated that capabilities and techniques from GLM-5-Turbo will be incorporated into a future open-source model release, but has not committed to releasing GLM-5-Turbo weights directly. The current release is proprietary. Developers who require open weights for fine-tuning or self-hosting should continue using GLM-5, which is available under an MIT License on HuggingFace and ModelScope.
What is OpenClaw, and why does it matter for GLM-5-Turbo?
OpenClaw is Z.ai's framework for autonomous agent workflows—similar in concept to Claude's computer use or OpenAI's Assistants API, but adapted to Z.ai's ecosystem. It covers tasks that require multi-step planning, tool invocation, file operations, and persistent execution across sessions. GLM-5-Turbo was trained specifically on OpenClaw scenarios from the data construction phase, meaning the model's internal representations are tuned for agent-style reasoning rather than conversation. This is distinct from models that add tool-use capability as a post-training feature.
