GLM-5.1
Z.ai's MIT-licensed flagship with state-of-the-art software engineering performance, ~754B parameters, and unrestricted commercial use for enterprise AI.
Model Story
The General Language Model (GLM) family originated at Tsinghua University and the Knowledge Engineering Group (KEG) in Beijing, making it one of the longest-running open-source AI research programs. While early GLM versions focused on Chinese NLP benchmarks, the series expanded dramatically with GLM-4 in 2024 and reached frontier capability with GLM-5 in early 2026. GLM-5.1, released in April 2026, is the first in the family to achieve state-of-the-art results on SWE-Bench Pro, a rigorous benchmark for real-world software engineering.
What makes GLM-5.1 unique among frontier models is its licensing. The MIT license grants full commercial freedom: you can modify, redistribute, and even sell derivative works without restriction. For organizations building proprietary AI products or embedding models in customer-facing software, this eliminates the legal uncertainty that accompanies other open-weight releases with custom or partially commercial licenses.
GLM-5.1 also stands out for its balanced multilingual capability. While many frontier models are English-centric, GLM-5.1 was trained on a carefully curated multilingual corpus with strong performance in Chinese, English, Japanese, German, and French. This makes it a natural choice for international enterprises and Canadian organizations serving bilingual markets.
Key Specifications
| Developer | Z.ai (formerly ChatGLM / KEG Lab) |
|---|---|
| Release Date | April 2026 |
| Architecture | Sparse Mixture-of-Experts (MoE) |
| Total Parameters | ~754 billion |
| Active Parameters | ~40 billion per forward pass |
| Context Window | 200,000 tokens |
| License | MIT (full commercial freedom) |
| Knowledge Cutoff | February 2026 |
| Multimodal | Text, images, code |
| Languages | Chinese, English, Japanese, German, French, and 15+ others |
API Pricing
Pricing via OpenRouter and Z.ai API as of April 2026. The MIT license means no licensing fees, no usage caps, and no vendor lock-in. On-premises deployment on Faraday Machines eliminates per-token costs entirely; you pay only for hardware amortization and electricity.
Benchmarks
On-Premises Deployment
GLM-5.1 is Faraday Machines' top recommendation for enterprises with strict compliance requirements or those building commercial AI products. The MIT license means legal teams can sign off without the review cycles required for proprietary API terms or restrictive open-weight licenses.
The 40B active parameter footprint is larger than Kimi's 32B but smaller than many dense models. On a 3-node Faraday cluster, GLM-5.1 serves concurrent users with sub-2-second latency for typical coding and analysis queries. The 200K context window comfortably handles most enterprise document sets, and the model's strong instruction-following capability reduces the need for elaborate prompt engineering.