Z.AI
Ultra-low latency version of GLM-5.3-Flash engineered for high-concurrency real-time IDE code completion and interactive agents.
200K ctx$0.37 / 1M tok (Ultra-Low Latency MoE)
Introducing GLM-4.7-FlashZ.AIReleased January 19, 2026
GLM-4.7-Flash
Free-tier version of GLM-4.7 delivering fast inference, 200k context, and strong coding for high-frequency applications.
text-to-textProprietary APIFree API (200k Context 4.7)Context: 200K (200,000 tokens)Arena ELO: 1280
Technical Specifications
Architecture Type
Lightweight High-Throughput Transformer
Total Parameters
Compact High-Speed Scale
Context Window
200K (200,000 tokens)
Max Output Tokens
64K (64,000 tokens)
Knowledge Cutoff
January 2026
Supported Modalities
text, code
License & Access
Z.AI Free Tier Terms
Benchmark Evaluations
Mmlu
82
Humaneval
84.1
Chatbot Arena ELO
1280
Deep Architectural Overview
GLM-4.7-Flash serves as Z.AI’s primary free-tier API. It brings competitive programming capabilities at low latency, ideal for content moderation, role-play dialogue, automated unit tests, and real-time user-facing features.
Strengths & Considerations
Core Strengths
- 100% Free API access for developers
- Full 200k context window and 64k output buffer
- High generation throughput
Known Limitations
- Standard free-tier rate limits apply during peak periods
Token & API Pricing
Input Tokens (1M)$0.00
Output Tokens (1M)$0.00
Cached Input (1M)$0.0000
Pricing is verified directly against Z.AI's developer documentation and API rate sheets.
Similar & Alternative Models
Explore other frontier models from Z.AI and comparable reasoning engines.
Z.AI
The first native multimodal model in the GLM-5 series: 320B parameters (18B active) combining linear and sparse attention for low-cost visual coding.
200K ctx$0.15 / 1M tok (320B MoE Visual Coding)
Z.AI
Z.AI’s premier flagship model, delivering a 50% performance gain on Code Bench and matching Claude Mythos 5 in cybersecurity and vulnerability discovery.
1M ctx$1.40 / 1M tok (Flagship Coding & Cyber)
Z.AI
Flagship model built for project-scale context, supporting truly usable 1M-token context with 128k output.
1M ctx$1.40 / 1M tok (1M Lossless Context)