glm-4.6 - SWE-Bench Verified
SWE-Bench Verified resolved rate 55.4
View sourceZ.ai
Z.ai GLM series model for general text generation and reasoning tasks.
46.2
Quality Score
1163
Arena ELO
Undisclosed
Parameters
128K
Context
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Dec 2025
Released
Benchmarks
3
API
2
General
3
Recent launch, pricing, benchmark, and API signals linked to this model or its provider.
SWE-Bench Verified resolved rate 55.4
View sourceNavigation Language Models GLM-5.2 Guides API Reference Coding Plan Released Notes Terms and Policy Help Center Get Started Quick Start Overview Pricing Core Parameters SDKs Guide Migrate to GLM-5.2 Language Models GLM-5.2 HOT GLM-5.1 GLM-5 GLM-5-Turbo GLM-4.7 GLM-4.6 GLM-4.5 GLM-4-32B-0414-128K Vision Language Models GLM-5V-Turbo GLM-4.6V GLM-OCR AutoGLM-Phone-Multilingual GLM-4.5V Image Generation Models GLM-Image CogView-4 Video Generation Models CogVideoX-3 Vidu Q1 Vidu 2
SWE-Bench Verified resolved rate 55.4
Navigation Language Models GLM-4.6 Guides API Reference Coding Plan Released Notes Terms and Policy Help Center Get Started Quick Start Overview Pricing Core Parameters SDKs Guide Migrate to GLM-5.2 Language Models GLM-5.2 HOT GLM-5.1 GLM-5 GLM-5-Turbo GLM-4.7 GLM-4.6 GLM-4.5 GLM-4-32B-0414-128K Vision Language Models GLM-5V-Turbo GLM-4.6V GLM-OCR AutoGLM-Phone-Multilingual GLM-4.5V Image Generation Models GLM-Image CogView-4 Video Generation Models CogVideoX-3 Vidu Q1 Vidu 2
View sourceZ.ai documents GLM deployment through its coding plan and local-tool workflow integrations for programming assistants.
View sourceGLM-4.6 is now available through Ollama Cloud. 198K context window listed. Advanced agentic, reasoning and coding capabilities.
View sourceAs models, contexts, and workloads grow, hidden assumptions in inference infrastructure can surface as output anomalies. Reliability requires more than throughput, latency, and availability. It also requires preserving the correctness of model state behind every generation.

After fixing correctness issues, we turned to the next bottleneck: Prefill throughput and GPU memory pressure in long-context Coding Agent serving. To address this, we introduced LayerSplit, a layer-wise KV Cache storage scheme. Instead of duplicating all layers on every GPU, https://t.co/OGptVovbtf
Z.ai documents GLM deployment through its coding plan and local-tool workflow integrations for programming assistants.
Navigation Language Models GLM-5.2 Guides API Reference Coding Plan Released Notes Terms and Policy Help Center Get Started Quick Start Overview Pricing Core Parameters SDKs Guide Migrate to GLM-5.2 Language Models GLM-5.2 HOT GLM-5.1 GLM-5 GLM-5-Turbo GLM-4.7 GLM-4.6 GLM-4.5 GLM-4-32B-0414-128K Vision Language Models GLM-5V-Turbo GLM-4.6V GLM-OCR AutoGLM-Phone-Multilingual GLM-4.5V Image Generation Models GLM-Image CogView-4 Video Generation Models CogVideoX-3 Vidu Q1 Vidu 2
Navigation Language Models GLM-4.6 Guides API Reference Coding Plan Released Notes Terms and Policy Help Center Get Started Quick Start Overview Pricing Core Parameters SDKs Guide Migrate to GLM-5.2 Language Models GLM-5.2 HOT GLM-5.1 GLM-5 GLM-5-Turbo GLM-4.7 GLM-4.6 GLM-4.5 GLM-4-32B-0414-128K Vision Language Models GLM-5V-Turbo GLM-4.6V GLM-OCR AutoGLM-Phone-Multilingual GLM-4.5V Image Generation Models GLM-Image CogView-4 Video Generation Models CogVideoX-3 Vidu Q1 Vidu 2
GLM-4.6 is now available through Ollama Cloud. 198K context window listed. Advanced agentic, reasoning and coding capabilities.