Z.AI: GLM 5.2Active

z-ai/glm-5.2

GLM-5.2 supports a larger context window and output length, with up to 1M context and 128K output tokens. It adds streaming output for tool calls via tool_stream=true, enabling real-time access to tool call arguments. Like the GLM-4.7 series, it supports deep thinking with thinking={ type: "enabled" }, where thinking is enforced once enabled, and introduces reasoning_effort to control reasoning intensity under chain-of-thought mode. It also delivers stronger coding performance and more advanced reasoning capabilities.

By:Z.aiInput Type:Output Type:Publish time:2026-06-17

Providers

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ProviderCache Hit RateContext

Volcengine

volcengine

-$1.4/ M tokens$4.4/ M tokensRead:0.28/ M tokensWrite:0.0025/ M tokens1M--

Alibaba Cloud

alibaba

74.1%$1.4/ M tokens$4.4/ M tokensRead:0.14-0.28/ M tokensWrite:1.75/ M tokens1M3.29s26.8tps

Streamlake

streamlake

-$1.4/ M tokens$4.4/ M tokensRead:0.26/ M tokensWrite:-/ M tokens1M--

Baidu

baidu

37.5%$1.4/ M tokens$4.4/ M tokensRead:0.26/ M tokensWrite:-/ M tokens1M2.06s44.9tps

TencentCloud

tencent-cloud

-$1.4/ M tokens$4.4/ M tokensRead:0.28/ M tokensWrite:-/ M tokens1M1.92s32.1tps

BigModel

bigmodel

14.6%$1.4/ M tokens$4.4/ M tokensRead:0.26/ M tokensWrite:-/ M tokens1M1.61s43.0tps

Uptime

24hours

Direct request success rate on AI Gateway and per-provider.

Throughput

24hours

P50 throughput on live AI Gateway traffic, in tokens per second (TPS).

Latency

24hours

P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds.

Activity

Token volume and request traffic to this model over time.

Token Consumption

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows

Metrics sourced fromArtificial Analysis

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for. View All

Token Ranking

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