GLM-5.3

GLM-5.3 is Z.AI’s Frontier coding flagship from August 14, 2026, with 744 billion total and 40 billion active parameters. All improvements over GLM-5.2 stem from post-training: Terminal-Bench 3.0 rose from 4.6 to 28.3 percent, ExploitBench more than doubled. Reasoning is mandatorily active, context one million tokens. Weights available since 08/28/2026 under the bespoke GLM-5.3 license (MIT-like, $10B MaaS security review gate); Chinese cloud infrastructure.

Zhipu AI Version 5.3 Commercial use permitted MoE 744 B (40 B active) 1000 K Context 04/2026 $1.4 / $4.4 per 1M

  • Restricted Weights
  • Server
  • OpenRouter
  • Text
  • Agentic Orchestrator
  • Long Context
  • Batch

Sovereign Risk: HIGH The developer Z.AI is headquartered in China. The model’s development is therefore subject to Chinese legislation, which represents an elevated risk in the international context with regard to data security and state influence. As of the current date (August 23, 2026), the weights have not yet been released; the model is exclusively available via the GLM Coding Plan and the Z.AI cloud infrastructure, meaning all requests are routed through Chinese servers. Risk mitigation through local deployment is not currently possible.

Key metrics

Score · Latency · Cost · Quality

Total Score Gold
82.25
Routine
50.63
Reasoning
31.62

Rank #1

LLM Judge Avg
4.18
100 Coverage
Avg Task Duration
58.51
Batch
Token Rate
136.97
Output Rate
P95 Latency
207.18
Top 5 %
Total Tokens
357300
Output Volume
Cost per 1K
$0.0044
USD / 1K Requests
Benchmark Cost
$1.57
Total · 357300 tok

Benchmark modules

10 modules · weighted · vs. model median & top performer

GLM-5.3 Best model Ø All models
Code Quality 84.84
CLI Benchmark 95.33
Logical Reasoning 77.2
UX Writing 79.81
Documentation 80.52
Content Transform. 86
Cultural Intelligence 81.32
Synthesis Quality 73.33
Tool Execution 90
ToolUse Score 79.5
Benchmark Cost $1.57

Token efficiency & latency

Consumption per module vs. model median

Token consumption per module

Performance profile