Model

GLM-5.2 (Max)

OPEN

Zhipu AI / Z.ai (Tsinghua) · GLM-5 family · released Jun 13, 2026

Highest-capability reasoning-effort tier: raises the thinking-token budget (~85k tokens on hard tasks vs High's ~50% of that) for complex, long-horizon agentic problems. Same weights as the High tier.

ReasoningCodingVisionFunction callingTool useAgentic

2455.0

Elo · rank #24

Parameters

744B

Active params

40B (MoE)

Context

1M tokens

Architecture

Mixture-of-Experts, 744B total / 40B active, DSA + 'IndexShare' sparse-attention indexer reuse (2.9x fewer per-token FLOPs at 1M context), 1M-token context; selectable High/Max reasoning-effort modes

License

MIT

Languages

—

API price (in/out)

$1.4 / $4.4

Modalities

text

Benchmark results

Bar shows position within the tracked field; marker = field best

Agents' Last ExamAgents40.6%#8

best: GPT-5.6 · 52.7%

AIMEMath99.2%#5

best: GPT-5.2 · 100.0%

GDPval-AAAgents1524#13

best: Claude Fable 5 · 1932

GPQA DiamondReasoning91.2%#19

best: GPT-5.6 · 94.6%

Humanity's Last ExamReasoning40.5%#23

best: Claude Sonnet 5 · 57.4%

IFBenchReasoning73.3%#20

best: MiniMax M3 · 83.0%

LiveCodeBenchCoding69.5%#71

best: DeepSeek-V4-Pro (Think Max) · 93.5%

MCP AtlasAgents76.8%#2

best: Kimi K3 · 84.2%

SWE-bench ProCoding62.1%#7

best: Claude Fable 5 · 80.0%

SWE-bench VerifiedCoding82.8%#6

best: Claude Fable 5 · 95.0%

τ²-Bench TelecomAgents99.1%#3

best: Claude Opus 4.6 · 99.3%

Terminal-Bench 2.0Coding81.0%#7

best: GPT-5.6 · 88.8%

Run it locally

VRAM @ Q4

—

VRAM @ FP16

—

Fits on (Q4)

Multi-node cluster required

Throughput data unavailable.

Quantizations

—

GLM-5 family

Elo progression across releases

GLM-5Feb 20262123.1 GLM-5.1Apr 20262241.1 GLM-5.2 (High)Jun 20261000.0 GLM-5.2 (Max)Jun 20262455.0

Resources

HFzai-org/GLM-5.2 DOCShttps://docs.z.ai/guides/llm/glm-5.2 APIAvailable via Zhipu AI / Z.ai (Tsinghua) API

API price $1.4/$4.4 · each benchmark row carries its own source badge (see methodology)