Model reference · open weights

GLM

LLMs PrimeIntellect Text gen 1 build Open weights 3k dl/mo

GLM is an open-weight language model from PrimeIntellect. GLM-0.5B (BF16) weighs 1.1 GB; the smallest configuration that runs it is RTX 3060 12 GB.

  • GLM is a text-generation model developed by PrimeIntellect and published as PrimeIntellect/GLM-0.5B.
  • It features 543M parameters and supports a context length of 131072 tokens.
  • The model operates in English and Chinese and is distributed under the MIT license.

Summary of the PrimeIntellect/GLM-0.5B model card, 2026-10-01

What it is

Released byPrimeIntellect
Released2025-09-22
Parameters543M
VRAM1.1 GB for the weights

What it runs on

Memory and cards for GLM-0.5B (BF16)

1.1 GBweights, file size
25 MBcache per 1K tokens
711 MBruntime overhead, at least
131,072 tokenscontext max
CardRequests at onceContext maxMemory
8K each32K each
RTX 3060 12 GB4812all 128K11.6 GB
RTX 4060 Ti 16 GB6716all 128K15.4 GB
RTX 3090 24 GB10726all 128K23.4 GB
RTX 4090 24 GB10726all 128K23.4 GB
RTX 5090 32 GB14536all 128K31.0 GB
L40S 48 GB20952all 128K44.0 GB
A100 80 GB37994all 128K78.2 GB
H100 80 GB35889all 128K78.1 GB
RTX PRO 6000 Blackwell 96 GB436109all 128K93.8 GB
DGX Spark (GB10) 128 GB unified503125all 128K107 GB
H200 141 GB655163all 128K138 GB
B200 180 GB842210all 128K176 GB
Memory needed at each load
Requests at once8K tokens each32K tokens each
12.0 GB2.6 GB
52.8 GB5.8 GB
83.4 GB8.2 GB
165.0 GB14.7 GB
328.2 GB27.6 GB
6414.7 GB53.3 GB

One card, with vLLM's small-card settings.

From the model card

What PrimeIntellect says about GLM

Read the model card

📖 Check out the GLM-4.5 technical blog, technical report, and Zhipu AI technical documentation. 📍 Use GLM-4.5 API services on Z.ai API Platform (Global) or Zhipu AI Open Platform (Mainland China). 👉 One click to GLM-4.5.

Model Introduction

The GLM-4.5 series models are foundation models designed for intelligent agents. GLM-4.5 has 355 billion total parameters with 32 billion active parameters, while GLM-4.5-Air adopts a more compact design with 106 billion total parameters and 12 billion active parameters. GLM-4.5 models unify reasoning, coding, and intelligent agent capabilities to meet the complex demands of intelligent agent applications.

Both GLM-4.5 and GLM-4.5-Air are hybrid reasoning models that provide two modes: thinking mode for complex reasoning and tool usage, and non-thinking mode for immediate responses.

We have open-sourced the base models, hybrid reasoning models, and FP8 versions of the hybrid reasoning models for both GLM-4.5 and GLM-4.5-Air. They are released under the MIT open-source license and can be used commercially and for secondary development.

As demonstrated in our comprehensive evaluation across 12 industry-standard benchmarks, GLM-4.5 achieves exceptional performance with a score of 63.2, in the 3rd place among all the proprietary and open-source models. Notably, GLM-4.5-Air delivers competitive results at 59.8 while maintaining superior efficiency.

For more eval results, show cases, and technical details, please visit our technical blog or technical report.

The model code, tool parser and reasoning parser can be found in the implementation of transformers, vLLM and SGLang.

Quick Start

Please refer our github page for more detail.

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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