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GLM-5.2 Review

GLM-5.2 is a 750 billion parameter, open-source large language model from Zhipu AI, designed for coding tasks with a focus on cost-effectiveness and long-horizon task execution.

shipped Jun 22, 2026freemium
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GLM-5.2 — product screenshot

Why it matters

1A 750 billion parameter open-weight model released on June 16, 2026, by Zhipu AI (Z.ai).
2Achieves a score of 51 on the Artificial Analysis Intelligence Index, ranking as the highest-scoring open-weight model.
3API pricing starts at approximately $0.95 per 1 million input tokens via third-party providers.
4Features architectural improvements including IndexShare and an Improved Multi-Token Prediction (MTP) Layer.

Stork’s verdict on GLM-5.2

GLM-5.2 offers cost-effective, long-horizon coding, but its raw intelligence won't always beat top closed models.

GLM-5.2 reviewed by Stork AI · stork.ai/en/glm-5-2

Specs

API Docs

View Documentation →

API Available

Yes, public API

overview

What is GLM-5.2?

GLM-5.2 is a large language model tool developed by Zhipu AI (Z.ai) that enables developers and enterprises to execute long-horizon tasks, particularly excelling in extended-context reasoning, advanced coding, and agentic workflows. It is an open-weight model with 750 billion parameters, designed for cost-effectiveness and efficient processing of complex, multi-step tasks. Released on June 16, 2026, following an early access period on June 13, 2026, GLM-5.2 has gained attention for its capabilities in software engineering, document analysis, and content creation. Its architecture incorporates IndexShare, which reduces per-token FLOPs by 2.9 times at a 1M context length, and an Improved Multi-Token Prediction (MTP) Layer, increasing speculative decoding acceptance length by up to 20%.

features

Key Features of GLM-5.2

GLM-5.2 incorporates several technical and operational features designed to optimize its performance and utility for complex AI tasks.

  • 750 billion parameter large language model architecture.
  • Open-source with an MIT license, facilitating self-hosting and fine-tuning.
  • API available for integration into custom applications and workflows.
  • Specialized for advanced coding tasks, including code review, debugging, and modernization.
  • Engineered for long-horizon task execution and agentic workflows, maintaining context over extended periods.
  • Cost-effective pricing structure, including cached input rates and competitive API costs.
  • Supports extended-context reasoning over large volumes of information, up to 1 million tokens.
  • Architectural improvements: IndexShare for FLOPs reduction and Improved Multi-Token Prediction (MTP) Layer for faster generation.
  • Offers prompt-based rate limits for GLM Coding Plans (e.g., 120 prompts per 5-hour cycle for Lite plan).

use cases

Who Should Use GLM-5.2?

GLM-5.2 is engineered for specific professional applications requiring robust AI capabilities, particularly in technical and creative domains.

  • Software Engineers: For autonomous code review, debugging, modernization of legacy systems, and large-scale code implementation.
  • AI Agent Developers: To construct and manage long-horizon agentic workflows that demand multi-step planning and persistent context.
  • Data Analysts & Researchers: For comprehensive analysis of extensive document collections, contracts, logs, or technical manuals.
  • Content Creators: For summarizing lengthy conversations, operational histories, and generating versatile content efficiently.
  • Design Professionals: For generating UI/UX feedback, providing creative direction, and developing brand language that resonates with design principles.

how to use

How to Use GLM-5.2

GLM-5.2 can be accessed through Z.ai's official API or via GLM Coding Plans for integration into various IDEs and tools. Enterprises can also deploy it on dedicated AI clusters through OCI Enterprise AI.

  • 1Register for an account on the Z.ai developer platform (z.ai).
  • 2Obtain API keys from the developer overview (https://www.z.ai/developer/overview) for programmatic access to GLM-5.2.
  • 3Integrate the GLM-5.2 API into custom applications for coding, content generation, or document analysis tasks.
  • 4Subscribe to a GLM Coding Plan (Lite, Pro, Max) to utilize GLM-5.2 within supported Integrated Development Environments (IDEs).
  • 5For enterprise deployment, leverage OCI Enterprise AI's Model Import feature, available as of July 2, 2026, to run GLM-5.2 on dedicated AI clusters.

pricing

GLM-5.2 Pricing & Plans

GLM-5.2 operates on a freemium model with various pricing tiers, including subscription-based GLM Coding Plans and pay-as-you-go API access. Z.ai offers promotional rates for coding plans and different pricing structures for cached versus standard API usage, with usage deductions during peak hours. Usage of GLM-5.2 and GLM-5-Turbo models is deducted at 3x during peak hours and 2x during off-peak hours.

  • Freemium: Free access to basic functionalities.
  • GLM Coding Lite plan: Varies, includes 120 prompts per 5-hour cycle and approximately 400 prompts weekly.
  • GLM Coding Pro plan: Varies (e.g., promotional rate around $15/month, standard monthly rates potentially ~$72), includes 600 prompts per 5-hour cycle.
  • Pay-as-you-go (Cached Input): $0.00026 per 1k tokens ($0.26 per 1 million tokens).
  • Pay-as-you-go (Standard API on Z.ai): Approximately $1.40 per 1 million input tokens and $4.40 per 1 million output tokens.
  • Third-Party API (e.g., OpenRouter): Starting around $0.95 per 1 million input tokens and $3.00 per 1 million output tokens.

Pros

  • +750 billion parameter open-weight model with an MIT license, allowing for self-hosting and fine-tuning.
  • +Exceptional performance on long-horizon coding and agentic workflows, maintaining context over extended sessions.
  • +Significantly more cost-effective than top-tier closed models like Claude Opus 4.8 or GPT-5.5.
  • +Achieves a high score of 51 on the Artificial Analysis Intelligence Index, ranking as the highest-scoring open-weight model.
  • +Incorporates architectural innovations such as IndexShare and an Improved Multi-Token Prediction (MTP) Layer for enhanced efficiency and speed.
  • +Strong capabilities in extended-context reasoning and processing large volumes of information.

Cons

  • −Its 'raw intelligence' may not consistently surpass top-tier closed models like Claude Opus or GPT-5.5 in all general reasoning tasks.
  • −Code review performance can vary, with coverage potentially dropping on more complex codebases.
  • −Usage of GLM-5.2 and GLM-5-Turbo models is deducted at 3x during peak hours and 2x during off-peak hours for GLM Coding Plans.
  • −Pricing structures can be complex, with different rates for cached input, standard API, and third-party providers.
  • −Requires integration via API or specific coding plans, not offered as a standalone consumer application.

Similar Tools

GLM-5.2 vs Competitors

GLM-5.2 is positioned as a leading open-weight model that directly challenges proprietary frontier models, offering a balance of high performance, cost-effectiveness, and the advantages of an open-source license. It consistently ranks as the highest-scoring open-weight model on independent evaluations like the Artificial Analysis Intelligence Index, where it scores 51.

1
DeepSeek-V4 / DeepSeek CoderOn Stork

DeepSeek offers a range of highly capable, cost-effective open-weight models specifically designed for coding and reasoning, with strong performance on benchmarks.

DeepSeek-V4 Pro (1.6T total, 49B active) and DeepSeek-Coder-V2 (236B total, 21B active) are open-weight models with MIT or Apache 2.0 licenses, similar to GLM-5.2's open-source nature. DeepSeek models are known for their competitive pricing, with V4 Flash being particularly cost-efficient, and offer long context windows (1M for V4, 128K for Coder-V2), comparable to GLM-5.2's 1M context window.

2
Mistral AI (Codestral)On Stork

Mistral AI provides a family of powerful, efficient, and cost-effective models, with specialized variants like Codestral specifically optimized for coding tasks.

Mistral offers a freemium chat product and competitive API pricing, similar to GLM-5.2's freemium model and focus on cost-effectiveness. Codestral is a coding-focused model, directly competing with GLM-5.2's primary use case, and Mistral models support long context windows (e.g., 128K for Mistral Small 3.1).

3
Code Llama (Meta)↗

Code Llama is a family of open-source large language models specifically fine-tuned by Meta for code generation, infilling, and understanding natural language instructions about code.

Code Llama is open-source and free for research and commercial use, directly aligning with GLM-5.2's open-source and cost-effective nature. While its parameter counts vary (e.g., 7B to 70B), it offers strong coding performance and supports large input contexts (up to 100K tokens), making it a direct competitor for coding tasks.

4
Qwen (Alibaba Cloud)↗

Qwen is a series of open-weight, multimodal LLMs from Alibaba Cloud with strong coding capabilities and support for long-context reasoning and multilingual tasks.

Qwen models, such as Qwen3-Coder-480B-A35B (480B total / 35B active), are open-weight (Apache 2.0) and excel in coding benchmarks, similar to GLM-5.2's focus. They offer long context windows (256K natively, expandable to 1M via Yarn), making them strong alternatives for complex coding and agentic workflows.

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