GLM-5.2
Active Parameters
744B
Context Length
1M
Modality
Text
Architecture
Mixture of Experts
KV Cache Rate
3744 KB/tok
License
MIT
Release Date
13 Jun 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $1.40 · Output: $4.40
Hardware Sizing
Precision
Context
Workload Memory: 1492.06 GB
FP16 · 8K context
Base Weights: 1460.31 GB
KV Cache: 29.25 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
Cluster: 16x NVIDIA H200 141GB
1492.1 / 2030.4 GB usable · TP 8 · PP 2
Determine requirements for datacenter hardware:
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Architecture Diagram
Evaluation Benchmarks
Rank
#24
| Benchmark | Score | Rank |
|---|---|---|
StackUnseen | 0.867 | 8 |
Graduate-Level QA | 0.912 | 20 |
Coding | 0.80 | 24 |
Web Development | max 1606 | 26 |
Agent Arena | max 0.01 | 28 |
Agentic Coding | 0.52 | 34 |
General Text | max 1475 | 35 |
Mathematics | 0.90 | 35 |
Data Analysis | 0.74 | 38 |
General | 0.73 | 43 |
LiveBench Average | 0.73 | 43 |
Agentic Index | max 0.38 | 47 |
Coding Index | max 0.69 Standard 0.47 | 48 94 |
Reasoning | 0.79 | 54 |
Intelligence Index | max 0.34 Standard 0.22 | 61 142 |
Rankings
Overall Rank
#24
Coding Rank
#21
About GLM-5.2
Z.ai's flagship open-weights foundation model released June 13, 2026. A 744-billion-parameter Mixture-of-Experts model with 40 billion active parameters per token, powered by IndexShare technology. Features a stable 1M-token context window optimised for long-horizon coding and agentic workflows, multiple thinking-effort levels (High and Max), and strong benchmark performance (81.0 on Terminal-Bench 2.1, 62.1 on SWE-bench Pro). Supports thinking mode, streaming, function calling, context caching, structured output, and MCP integration. Released under MIT license with no regional restrictions. Priced at $1.40 per million input tokens and $4.40 per million output tokens.
Technical Specifications
Attention
Attention Structure
DeepSeek Sparse Attention
Attention Heads
64
Key-Value Heads
64
Attention Head Dimension
192
Position Embedding
ROPE
RoPE Theta
8,000,000
Normalization
RMS Normalization
Activation Function
Swish
Dimensions
Hidden Dimension Size
6,144
Number of Layers
78
FFN Intermediate Size (Dense)
12,288
Multi-Token Prediction Heads
1
Tokenizer
Vocabulary Size
154,880
Mixture of Experts
Total Expert Parameters
40.0B
Number of Experts
256
Active Experts
8
Shared Experts
1
FFN Intermediate Size (per Expert)
2,048
Dense Layers Before MoE
3
About GLM-5.2
Z.ai's GLM-5.2 is a 744-billion-parameter Mixture-of-Experts flagship foundation model, released June 13, 2026, designed for long-horizon coding and agentic engineering tasks. It features a usable 1M-token context window, IndexShare architecture reducing compute to 1/20th of prior generations, and multiple thinking-effort levels. Open-weights under MIT license with no regional restrictions.
Other GLM-5.2 Models
- No related models available