GLM-5
v20260211Z.ai (Zhipu AI)
Z.ai's MIT-licensed 744B-parameter MoE (40B active) with 77.8% SWE-bench Verified, 92.7% AIME 2026, and open-source leadership on BrowseComp and agentic benchmarks. Trained on 28.5T tokens with DeepSeek Sparse Attention.
Trust Vector Analysis
Dimension Breakdown
🚀Performance & Reliability+
Among the strongest open-weight models released to date: 77.8% SWE-bench Verified, 92.7% AIME 2026, 86.0% GPQA-Diamond, with independent confirmation of open-source leadership on BrowseComp, Vending Bench 2, and MCP-Atlas.
Industry-standard coding benchmarks with independent third-party verification
Graduate and competition-level reasoning benchmarks requiring multi-step problem solving
Independent agentic and general-capability benchmarking across domains
Community testing with repeated prompts and long agent runs
Median latency for API requests with standard prompt sizes
95th percentile response time across diverse workloads
Official specification from model card
Review of platform availability and self-hosting fallback options
🛡️Security+
Solid for an open model; no published third-party security audit. Self-hosting shifts responsibility to the deployer.
Review of safety documentation and community testing against OWASP LLM01 patterns
Testing against adversarial prompt datasets; deployer-dependent for self-hosted use
Analysis of privacy policies and self-hosting data-control options
Safety testing across harmful content categories
Review of API security features and best practices
🔒Privacy & Compliance+
First-party Z.ai API operates under Chinese jurisdiction — a material caveat for Western regulated industries. The unencumbered MIT license makes self-hosting or Western-host deployment a clean mitigation.
Review of provider jurisdiction and third-party hosting options
Analysis of privacy policy and data usage terms
Review of terms of service and deployment-dependent retention
Review of data protection capabilities and customer responsibilities
Verification of compliance certifications and audit reports
Review of self-hosting deployment options enabling zero retention
👁️Trust & Transparency+
Above-average transparency for an open frontier model: architecture, training scale, and benchmarks well documented with independent verification. Bias and safety evaluations remain thin.
Evaluation of reasoning transparency and trajectory inspectability
Testing on factual QA and grounded research benchmarks
Review of published bias benchmarks and community evaluations
Qualitative assessment of confidence expression in outputs
Review of documentation completeness and clarity
Review of public disclosures about training data
Analysis of built-in safety mechanisms
⚙️Operational Excellence+
Clean MIT licensing and strong ecosystem support. Note the rapid successor cadence: GLM-5.1 shipped within two months and GLM-5.2 (1M context, MIT) within four; evaluate which version your hosts actually serve. GLM-5 weights remain available.
Review of API design, consistency, and feature completeness
Review of SDK quality, documentation, and maintenance
Review of versioning practices and weight availability across releases
Review of available monitoring tools and metrics
Assessment of documentation, community, and support responsiveness
Analysis of third-party hosting, integrations, and tooling
Review of licensing terms and restrictions
- +Frontier-competitive results: 77.8% SWE-bench Verified, 92.7% AIME 2026, 86.0% GPQA-Diamond
- +Independently verified open-source leadership on BrowseComp, Vending Bench 2, and MCP-Atlas
- +Unencumbered MIT license with full self-hosting rights
- +Efficient inference: 40B active of 744B total with DeepSeek Sparse Attention
- +Very competitive API pricing (~$0.60/$1.92 per 1M tokens)
- +Well-documented training scale (28.5T tokens) and architecture
- !First-party Z.ai API processes data under Chinese jurisdiction with limited Western compliance certifications
- !Text-only — no vision or audio modalities
- !Rapid successor cadence (GLM-5.1 within two months, GLM-5.2 with 1M context by June 2026) creates version-tracking overhead
- !Limited published bias, safety, and red-team evaluations
- !Self-hosting a 744B MoE requires substantial GPU infrastructure
- !English-language enterprise support is thin compared to Western providers
Use Case Ratings
code generation
77.8% SWE-bench Verified with independent verification; best-in-class open-weight coding at ~$0.60/$1.92 per 1M.
customer support
Capable and inexpensive, but not specialized for support workflows.
content creation
Strong long-form generation at very low cost.
data analysis
Excellent mathematical reasoning (92.7% AIME 2026) and agentic tool use for analysis pipelines.
research assistant
Open-source leader on BrowseComp and MCP-Atlas; strong grounded web research.
legal compliance
China-jurisdiction first-party API and absent Western certifications are blockers unless self-hosted.
healthcare
Not recommended via first-party API; self-hosted deployment in a compliant environment is the only viable path.
financial analysis
Top-tier quantitative reasoning; regulated firms should self-host or use certified Western hosts.
education
Outstanding math and science tutoring (92.7% AIME, 86.0% GPQA-Diamond) at budget pricing.
creative writing
Competent prose; optimized for reasoning and agentic work rather than creative style.