GLM-5.2
v20260613Z.ai (Zhipu AI)
Z.ai's MIT-licensed 744B-parameter MoE (40B active) launched June 2026 with a 1M-token context via IndexShare sparse attention. Leading open-weight model on Artificial Analysis Intelligence Index v4.1 (51), with 62.1 SWE-bench Pro, 81.0 Terminal-Bench 2.1, and 99.2% AIME 2026 at $1.40/$4.40 per 1M tokens. Weights published 2026-06-16.
Trust Vector Analysis
Dimension Breakdown
🚀Performance & Reliability+
Strongest open-weight release to date on independent measures: leads Artificial Analysis Intelligence Index v4.1 (51) and GDPval-AA v2, 62.1 SWE-bench Pro, 81.0 Terminal-Bench 2.1, 99.2% AIME 2026. Launch recency (June 2026) limits consistency, latency, and uptime confidence; the model is notably token-hungry.
Vendor benchmarks corroborated by independent leaderboards (Artificial Analysis, Code Arena) within weeks of launch
Vendor-reported competition and graduate-level reasoning benchmarks; broad independent replication still pending given launch recency
Independent composite benchmarking and third-party hands-on evaluation
Early community testing with repeated prompts; limited observation window since June 2026 launch
Early median latency observations; limited data given launch recency
95th percentile response time from early third-party measurements
Official specification from model card
Review of platform availability since launch; observation window under one month
🛡️Security+
Inherits the GLM family's solid-but-unaudited open-model posture. No third-party security audit yet; the model is under a month old, so red-team coverage is thin. Self-hosting shifts responsibility to the deployer.
Review of safety documentation and GLM-family precedent against OWASP LLM01 patterns; model too new for mature red-team coverage
Early 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, anchored to GLM-family precedent
Review of API security features and best practices
🔒Privacy & Compliance+
Same posture as GLM-5: first-party API under Chinese jurisdiction is a material caveat for Western regulated industries, cleanly mitigated by the unencumbered MIT weights via self-hosting or Western hosts.
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+
Strong architectural transparency (IndexShare, MTP, benchmark tables) with rapid independent verification by Artificial Analysis and community reviewers. Training data detail is thinner than GLM-5's, and bias/safety evaluations remain unpublished. Note vendor materials cite 753B total parameters while Artificial Analysis lists 744B/40B active; active-parameter count is consistent across sources.
Evaluation of reasoning transparency and trajectory inspectability
Inference from grounded agentic benchmarks; limited dedicated factual-QA data given launch recency
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 fast third-party host adoption. The family's rapid release cadence (three flagships in five months) remains the main operational overhead; ecosystem depth for 5.2 specifically is still building given the mid-June weights release.
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; conservative given under a month since weights release
Review of licensing terms and restrictions
- +Leading open-weight model on independent measures: Artificial Analysis Intelligence Index v4.1 (51) and GDPval-AA v2
- +Top open-weight coding results: 62.1 SWE-bench Pro, 81.0 Terminal-Bench 2.1, 2nd on Code Arena WebDev
- +1M-token context (5x GLM-5.1) made affordable by IndexShare sparse attention (2.9x FLOP reduction)
- +Unencumbered MIT license with weights published three days after API launch
- +Frontier-competitive reasoning: 99.2% AIME 2026, 91.2% GPQA-Diamond, 54.7 HLE-with-tools
- +Roughly 1/6th the cost of GPT-5.5 at $1.40/$4.40 per 1M tokens
- !First-party Z.ai API processes data under Chinese jurisdiction with limited Western compliance certifications
- !Token-hungry: ~43K output tokens per benchmark task vs 24-37K for peers, inflating effective cost and latency
- !Text-only — no vision or audio modalities
- !Under a month old: consistency, uptime, and security evidence still immature
- !Limited published bias, safety, and red-team evaluations
- !Self-hosting requires over 1TB of GPU VRAM in BF16
- !Parameter count reported inconsistently (744B by Artificial Analysis vs 753B in vendor materials)
Use Case Ratings
code generation
Top open-weight coding model: 62.1 SWE-bench Pro and 81.0 Terminal-Bench 2.1, just behind Claude Opus 4.8, with a 400K coding context at 1/6th GPT-5.5's cost.
customer support
Capable and inexpensive, but token-hungry reasoning is wasteful for simple support flows.
content creation
Strong long-form generation with 1M context for whole-corpus grounding.
data analysis
Near-perfect competition math (99.2% AIME 2026) and leading agentic benchmark results for analysis pipelines.
research assistant
Leads open weights on GDPval-AA v2; 1M-token context handles entire document collections in one pass.
legal compliance
China-jurisdiction first-party API and absent Western certifications are blockers unless self-hosted; 1M context is attractive for contract corpora once mitigated.
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 (99.2% AIME, 91.2% GPQA-Diamond); pricier than GLM-5 but still budget-friendly.
creative writing
Competent prose; optimized for coding and agentic work rather than creative style.