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Zhipu AI · GLM
No. 32

GLM-5.2

Open-weight coding flagship at a fraction of frontier cost.

OpenOpen weightsText
Field notes
Context window
1.0Mtokens
Max output
131Ktokens
Input price
$1.40/ 1M tokens
Output price
$4.40/ 1M tokens
Cached input
$0.26/ 1M tokens
Modalities
Text
Knowledge cutoff
Mar 2026
Released
Jun 2026
Parameters
753B
License
MIT
Approx. speed
Overview

What this model is

Zhipu's GLM-5.2 is a ~753B-parameter open-weight MoE (~40B active, MIT) that leads open models on Artificial Analysis' Intelligence Index (51 — the top open-weights score) while its Z.ai API list price ($1.40 in / $4.40 out) runs roughly one-sixth the closed frontier, and open-weight hosts price it lower still. It adds selectable High and Max thinking-effort reasoning modes for long-horizon coding. Its vendor-aggregate SWE-bench Pro (62.1) edges GPT-5.5's, though independent contamination-resistant runs of the GLM family land far lower, so its coding lead is softer than the headline suggests. Its 1M-token context holds an entire mid-sized codebase, and it ships as a drop-in Anthropic-compatible backend for Claude Code workflows — a value challenger rather than a frontier-reliable autonomous agent.

Strengths

  • Best-in-class open-weight coding benchmarks
  • 1M-token context for whole-repo work
  • Roughly one-sixth the cost of frontier closed models
  • Selectable High / Max thinking-effort reasoning modes
  • Permissive MIT weights, self-hostable
  • Strong math and reasoning (AIME ~99%)

Trade-offs

  • Long agentic sessions less reliable than Claude/GPT
  • Text-only flagship (vision is the separate GLM-5V)
  • Benchmark scores overstate real-world autonomy
  • Large model — throughput and latency costs

Best for

  • Cost-efficient coding assistants
  • Whole-repo refactors within a supervised loop
  • Self-hosted / on-prem deployments
  • Claude Code-compatible budget backend
  • Math and reasoning tasks

Not ideal for

  • Unsupervised long-horizon autonomous coding
  • Vision-heavy multimodal tasks
Capabilities

Capability profile

Normalized 0–100 scores, comparable across the whole catalog.

Reasoning86Coding77Math88Writing82Knowledge85Speed58Agentic75Vision10Multilingual84Long Context84
Reasoning
86
Coding
77
Math
88
Writing
82
Knowledge
85
Speed
58
Agentic
75
Vision
10
Multilingual
84
Long Context
84
Benchmarks

How it scores

Public benchmark results, with independent third-party results where available. Bars normalize percentages to 100 and Elo ratings to a 1500 ceiling.

Independent index
Artificial Analysis Intelligence Index
Composite of ~9–10 independent evals · Artificial Analysis
51/ 100
BenchmarkResult
Artificial Analysis Intelligence Indexindependent
GeneralArtificial Analysis
51%
SWE-bench Proindependent
CodingSWE-bench Pro
62.1%
GPQA Diamondindependent
ReasoningIndependent aggregators
91.2%
AIME 2025
MathVendor-reported
99.2%
Alternatives

Comparable models

Models in a roughly similar class — worth weighing against this one.