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GLM-5.1

MIT

Z.ai · 754B (40B active) · Mixture of Experts

Improved GLM frontier model for SWE-bench style coding and long-horizon agent tasks

HuggingFace
0 downloads 0 likes 2026-04 128K context

Use Cases

chat reasoning code

Mixture of Experts

Total experts: 256
Active experts: 8
Active params: 40.0B

Quantization Options

Quant Bits VRAM Quality Status
Q2_K 2 241.9 GB low —
Q3_K_M 3 338.4 GB moderate —
Q4_K_M 4 386.7 GB good —
Q5_K_M 5 483.3 GB good —
Q6_K 6 579.8 GB excellent —
Q8_0 8 772.9 GB excellent —
F16 16 1545.4 GB lossless —

About this model

HF model card GLM
GLM-5.1 source artwork

Z.ai

754B

Mixture of Experts model for chat, reasoning, code workloads.

Context

128K

Q4 VRAM

~386.7 GB

Image saved from public model sources

Mixture of Experts Thinking Tool use Code

GLM-5.1 on your hardware

Improved GLM frontier model for SWE-bench style coding and long-horizon agent tasks. This page turns the Hugging Face model card into practical local-run numbers, so you can compare quantized VRAM, system RAM, and expected fit before downloading a large checkpoint.

Model shape

754B total parameters with 40B active. 8 of 256 experts are active per token.

Local fit target

Start with Q4_K_M: about 368.7 GB on disk and 386.7 GB VRAM before extra context and runtime overhead.

Best use cases

chat, reasoning, code

License and source

Listed as MIT from huggingface.co/zai-org/GLM-5.1.

Want the real verdict? Pick your GPU or edit the specs on this page and compare the quant table below.

Open HF repo