On April 7, 2026, Z.ai (formerly Zhipu AI) released GLM-5.1 — a 754-billion-parameter open-weight Mixture-of-Experts model that claims the #1 position on SWE-Bench Pro with a score of 58.4%, edging out Claude Opus 4.6 (57.3%). Licensed under MIT and designed for agentic engineering, GLM-5.1 can autonomously sustain coding tasks for up to eight hours across hundreds of iterations.
Intermediate
GLM-5.1 is a post-training upgrade to GLM-5, built on a Dynamic Sparse Attention (DSA) MoE architecture with approximately 40 billion active parameters per token. The model is laser-focused on two areas: coding and agentic tool use.
On coding benchmarks, GLM-5.1 leads across multiple evaluations:
Math and reasoning capabilities remain strong: 95.3% on AIME 2026, 86.2% on GPQA-Diamond, and 83.8% on IMOAnswerBench.
What sets GLM-5.1 apart is its ability to sustain long-horizon agentic tasks. In demonstrations, the model autonomously built a complete Linux desktop system over an eight-hour session, performing 655 iterations of planning, execution, testing, and optimization. In another test, it increased vector database query throughput to 6.9× the initial production version through iterative experimentation.
The model supports deployment through SGLang (v0.5.10+), vLLM (v0.19.0+), xLLM, Transformers, and KTransformers. Its MIT license places no restrictions on commercial use.
GLM-5.1 represents a milestone for Chinese open-source AI: a model from Z.ai that outperforms the best closed-source competitors on SWE-Bench Pro, the industry’s most respected coding benchmark. For developers and researchers, the MIT license and broad framework support make it immediately deployable — no API key required.
