Text / zai-org

GLM 5

GLM-5 is a text-generation model released by zai-org under the MIT license. It targets complex systems engineering and long-horizon agentic tasks. The model card states that GLM-5 scales to 744B parameters (40B active), increases pre-training data to 28.5T tokens compared with GLM-4.5, and integrates DeepSeek Sparse Attention (DSA). It supports English and Chinese, uses the transformers library, and is available in safetensors format. The model card also lists benchmark results and references API services, a technical blog, and a community.

EstimatedRepository opened Feb 11, 2026Source checked 9/25/2026Version: c183ef8c
LOCALRENTED GPUOPEN WEIGHTS
Freshness 35 out of 100. Repository age: 276 days old, Feb 11, 2026. Measures age, not quality.
Popularity 83 out of 100. 1,240,185 downloads in 30 days; 2,141 lifetime likes. Checked Nov 13, 2026. Measures adoption, not quality.
Arena Open Source Text: rank 13 of 230. Ranked model: GLM-5. Export dated Nov 11, 2026. Source checked Nov 13, 2026. Human preference ranking, not hardware suitability.
Category rankings & sources

Each position belongs to a separate Arena category. These are human preference rankings—not hardware recommendations. We do not combine the categories into one score.

Text#13of 230 open models
GLM-5zaiLicense: MIT
Export dated Nov 11, 2026Checked: Nov 13, 2026Overall board: #67
View official Text board
Web coding#30of 63 open models
GLM-5zaiLicense: MIT
Export dated Nov 11, 2026Checked: Nov 13, 2026Overall board: #92
View official Web coding board

Rankings reflect the dated export; live Arena boards can change. Open-source positions use Arena’s open-model filter. The overall position also includes the other models on that category board. Availability of weights and license terms still need to be checked separately.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source
Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source
Scores as of Nov 14, 2026. Statistics checked Nov 13, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

At a glance

Parameters
753.86B
Architecture
glm_moe_dsa
Context length
202,752
License
mit
Disk space
1404.2 GB
Software
SGLang, vLLM
View the model source
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Best for

  • Text generation
  • Complex systems engineering tasks
  • Long-horizon agentic tasks
  • Reasoning tasks
  • Coding tasks

Tradeoffs

  • The supplied model facts do not specify hardware requirements.
  • The supplied model facts do not specify compatibility details beyond pipeline, tags, and library name.
  • The supplied model facts do not specify performance beyond the included benchmark table.
  • The supplied model facts do not specify licensing beyond the MIT license.
  • The supplied model facts do not specify testing, validation, or verification details.

Ways to run it

SGLang · Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

sglang serve --model-path zai-org/GLM-5 --tp-size 8 --tool-call-parser glm47 --reasoning-parser glm45 --speculative-algorithm EAGLE --speculative-num-steps 3 --speculative-eagle-topk 1 --speculative-num-draft-tokens 4 --mem-fraction-static 0.85 --served-model-name glm-5
Official instructions

vLLM · Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

vllm serve zai-org/GLM-5 --tensor-parallel-size 8 --gpu-memory-utilization 0.85 --speculative-config.method mtp --speculative-config.num_speculative_tokens 3 --tool-call-parser glm47 --reasoning-parser glm45 --enable-auto-tool-choice --served-model-name glm-5
Official instructions

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GLM 5: hardware, VRAM & setup | YouRunAI