Z.ai: GLM 5.2 review: specs, pricing, and where it fits

The quick read

Z.ai: GLM 5.2 from z-ai is a balanced pick (#11): a 1.0M window at $0.32 input / $1.01 output per 1M tokens. It aims for capability headroom without top-tier prices—useful when neither raw cost nor absolute frontier quality is the only constraint.

Spec sheet at a glance

By the numbers: 1.0M context window; text-in / text-out; 21 exposed API parameters, including tool calling and structured outputs with reasoning support. Use these to judge fit for agentic, long-context, or structured-output workloads.

Pricing & how it compares

Pricing: $0.32 input / $1.01 output per 1M tokens. Its blended $0.66 is at or below the top-20 median ($0.66). On AI Hippo the composite board rewards cheap long-context models such as Meta: Llama 4 Scout, so a lower rank here means weaker value-per-token, not weaker capability.

Head-to-head

Its closest board neighbor is MiniMax: MiniMax M3 (1.0M ctx, $0.75/1M blended). Side by side, Z.ai: GLM 5.2 offers 1.0M ctx at $0.66/1M blended: context is similar and, on blended token price, it is cheaper. Pick between them on whichever axis your workload is bound by.

Where it fits

Best-fit workloads: whole-repo & long-document work, tool-calling agents, structured-output pipelines, multi-step reasoning, high-volume, cost-sensitive batch.

Cost in practice & verdict

A representative 100K-input + 20K-output task costs about $0.05 on Z.ai: GLM 5.2. Verdict: strong price-performance for a default, high-volume workhorse where every token counts.

Sources

• AI Hippo unified rankings
• Multi-source token pricing
• OpenRouter models API