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GLM-5.2

Flagship

by Z.ai (Zhipu AI)

As of October 19, 2026, GLM-5.2 by Z.ai (Zhipu AI) costs $1.40 per 1M input tokens and $4.40 per 1M output tokens, with a 1M-token context window. It ranks 8th of 29 models on the TensorFeed Intelligence Index's older 2024 benchmark set, with a score of 75.6 (as of October 22, 2026).

GLM-5.2 is Z.ai's (Zhipu AI) flagship, shipped June 13, 2026. It is a 744 billion parameter mixture-of-experts model with a 1 million token context window, 131K max output, and a Max-effort reasoning mode, released under an MIT license. API pricing is roughly $1.40 per million input tokens and $4.40 per million output, which is on the order of 80 percent below Claude Opus 4.8. Z.ai reports 62.1 on SWE-Bench Pro, which would top GPT-5.5, and the model sits fourth overall and first among open-weight models on the Artificial Analysis Intelligence Index at 51; treat both as vendor-reported. The detail that makes it strategically interesting is the training run: roughly 100,000 Huawei Ascend 910B chips with no Nvidia silicon in the loop, at an estimated $25 million all-in. Reporting puts it at something like 40 percent of developer tokens on OpenRouter. Self-hosting at full precision needs about 1.5TB of GPU memory, roughly nineteen H100s, so the MIT license buys far more freedom than most teams can actually exercise.

Input Price

$1.40

per 1M tokens

Output Price

$4.40

per 1M tokens

Context Window

1M

tokens

Released

2026-06

Open source

Capabilities

textcodetool-usereasoning

Key Strengths

  • ✓First among open-weight models on the Artificial Analysis index
  • ✓MIT licensed with 1M context and 131K output
  • ✓Roughly 80 percent cheaper than Opus 4.8
  • ✓Trained end to end on Huawei Ascend silicon, no Nvidia
  • ✓Vendor-reported 62.1 on SWE-Bench Pro

Best For

  • ▸Cost-sensitive coding agents
  • ▸Sovereign deployments avoiding US silicon
  • ▸High-volume agentic pipelines
  • ▸Self-hosting where MIT terms matter

Benchmark Scores

BenchmarkScoreDescription
SWE-bench82.8Real-world software engineering tasks from GitHub issues (SWE-bench Verified)
MMLU-Pro86.7General knowledge and reasoning across 57 subjects
GPQA Diamond91.2Graduate-level science questions verified by domain experts
FrontierCode v1.124.5Agentic coding on frontier software engineering tasks (Main split)
Humanity's Last Exam (tools)54.7Multidisciplinary expert-level reasoning with tool access

Scores sourced from public benchmark datasets. See full benchmark leaderboard for all models.

Pricing Details

Input tokens

$1.40

per 1M tokens

Output tokens

$4.40

per 1M tokens

Estimated cost per 1K requests

$3.60

~1K input + ~500 output tokens avg

Prices are subject to change. Check the official documentation for current pricing. See the cost calculator for detailed estimates.

Open Source Model

GLM-5.2 is free to download and self-host under the MIT. Hosted API pricing varies by provider (e.g., Together, Fireworks, Groq). See our open source LLM guide for deployment options.

Quick answers

How much does GLM-5.2 cost?
As of October 19, 2026, GLM-5.2 costs $1.40 per 1M input tokens and $4.40 per 1M output tokens on the Z.ai (Zhipu AI) API.
What is the context window of GLM-5.2?
GLM-5.2 has a 1M-token context window (1,000,000 tokens).
How does GLM-5.2 rank on the TensorFeed Intelligence Index?
GLM-5.2 ranks 8th of 29 models on the TensorFeed Intelligence Index's older 2024 benchmark set, with a score of 75.6 (as of October 22, 2026). Scores from the 2024 and 2026 benchmark sets are ranked separately and never compared.

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