LLMz-ai

Z.ai: GLM 5.2

GLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow...

Anyone in the Space can @-mention Z.ai: GLM 5.2 with the team's shared context - pooled credits, one chat, one memory.

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Starter is free forever - 1 Space, 100 credits/month, 1 MCP. No card.

Verdict

GLM 5.2 is a large-context Chinese-English bilingual model with a 262K token window at mid-tier pricing. It offers strong value for teams working across Chinese and English documents, especially when long-context retrieval matters more than bleeding-edge reasoning. The $1.40/$4.40 per Mtok pricing sits between budget and premium tiers, making it a reasonable choice for bilingual workflows that need extended context but can tolerate slightly older architecture. Reach for this when you need Chinese-English translation or analysis over long documents and want more context than GPT-4o at comparable cost.

Best for

Chinese-English document translation
Long bilingual content analysis
Cross-language summarization tasks
Extended context retrieval in Chinese
Cost-conscious multilingual workflows

Strengths

The 262K context window handles full-length documents, research papers, and multi-turn conversations without truncation. Bilingual training means it switches naturally between Chinese and English within a single prompt, useful for translation review or mixed-language codebases. Pricing undercuts many Western models with similar context capacity, making it viable for high-volume bilingual work. The Z.ai deployment suggests optimized inference for Asian markets with lower latency for regional users.

Trade-offs

No public benchmark data makes it hard to gauge reasoning performance against GPT-4o, Claude, or Gemini on standardized tasks. The model likely trails frontier models on complex reasoning, coding, and math given its mid-tier pricing and regional focus. Output pricing at $4.40 per Mtok adds up quickly for generation-heavy tasks like long-form writing. Teams working primarily in English may find better value and performance with established Western models unless Chinese language support is essential.

Specifications

Provider: z-ai
Category: llm
Context length: 262,144 tokens
Max output: 262,144 tokens
Modalities: text
License: proprietary
Released: 2026-06-16

Pricing

Input: $1.40/Mtok
Output: $4.40/Mtok
Model ID: z-ai/glm-5.2

Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.

Team cost calculator

Seats5 peopleMessages / seat / day80Avg turn size2 ktokOutput share30 %

Estimated monthly spend

$40.48

17.6M tokens / month
5 seats · 80 msgs/day

Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.

Providers

Provider	Context	Input	Output	P50 latency	Throughput	30d uptime
z-ai	262k	$1.40/Mtok	$4.40/Mtok	—	—	—

Performance

Performance snapshots are collected daily. Check back after the next ingestion run.

Benchmarks

Public benchmark scores are not available yet for this model. Check back after the next ingestion run.

Works well with

Top MCPs

Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.

How Switchy teams use it

Not enough Spaces have used this model yet to share anonymised team stats. We wait for at least 50 distinct Spaces per week before publishing any aggregate.

Starter prompts

Bilingual Contract Review

I have a contract in both Chinese and English. Compare the two versions and identify any differences in meaning, missing clauses, or translation errors that could affect legal interpretation.

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Long Document Summarization

Summarize this 200-page document in 500 words, maintaining all critical dates, figures, and policy changes. Organize by section and flag any contradictions between chapters.

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Cross-Language Code Comments

Translate these Python function docstrings from Chinese to English, preserving technical accuracy and parameter descriptions. Keep code examples unchanged.

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Research Paper Analysis

Read this 40-page research paper and extract the hypothesis, methodology, dataset details, and main findings. Note any limitations the authors acknowledge.

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Multilingual Customer Support

A customer wrote in Chinese but attached English error logs. Diagnose the issue, explain the root cause in Chinese, and provide step-by-step troubleshooting in both languages.

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