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Description
GLM-5.3-Flash is a multimodal foundation model from Z.ai built for high-efficiency reasoning, coding, agents, and visual understanding. The model contains 320 billion parameters in total but activates only 18 billion parameters during inference, helping reduce compute requirements. Its architecture combines linear attention with sparse attention so it can efficiently handle both local dependencies and relevant information spread across very long contexts. Z.ai also introduced IndexPool to reduce the memory and latency overhead associated with long-context retrieval at context lengths reaching one million tokens. The model was pretrained on a 30-trillion-token multimodal dataset that incorporates both textual and visual information. GLM-5.3-Flash is designed for software engineering tasks, autonomous workflows, frontend development, computer use, document analysis, and other professional workloads that benefit from visual reasoning. Its visual coding capabilities allow it to inspect rendered interfaces, identify layout or interaction problems, and use those observations to revise its work. Benchmark results published by Z.ai show that it improves substantially over GLM-5.2 on multiple coding and agentic tests while remaining competitive with more expensive frontier models. GLM-5.3-Flash can be accessed through Z.ai services and is also available as downloadable model weights for deployment through supported open inference frameworks.
Description
SubQ Snap is a sophisticated decision-making model designed for both enterprise and agentic workflows, enabling rapid, structured decisions across extensive datasets. It effectively manages various tasks, including identifying relevant files, choosing the appropriate tool, verifying result validity, assessing whether to proceed with a workflow, and determining the necessity of a frontier model. Unlike traditional text generators, Snap operates by taking into account specific context, a posed question, and a limited range of possible answers to produce a probability distribution for those responses. It can process up to 384K tokens, integrating diverse forms of information such as codebases, contracts, interaction histories, logs, screenshots, charts, diagrams, and scanned documents within a single query. Utilizing Subquadratic Sparse Attention technology, Snap significantly diminishes the resources needed to analyze lengthy inputs, while its decision head adeptly correlates contextual representations to permissible answers without relying on autoregressive text generation. This innovative approach enhances efficiency and accuracy in decision-making processes across various applications.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Cheaper Inference
Yes
Claude Code
Yes
DeepSeek Harness
Yes
GLM Coding Plan
Yes
Hermes Agent
Yes
OpenClaw
Yes
OpenCode Go
Yes
OpenCode Zen
Yes
OpenRouter
Yes
Pi Agent
Yes
Integrations
Cheaper Inference
No
Claude Code
No
DeepSeek Harness
No
GLM Coding Plan
No
Hermes Agent
No
OpenClaw
No
OpenCode Go
No
OpenCode Zen
No
OpenRouter
No
Pi Agent
No
Pricing Details
$0.15 per 1M tokens (input)
Input: $0.15 per 1M tokens
Output: $0.50 per 1M tokens
Cached input: $0.03 per 1M tokens
Output: $0.50 per 1M tokens
Cached input: $0.03 per 1M tokens
Free Trial
No
Free Version
No
Pricing Details
$0.05 per million input tokens
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Z.ai
Founded
2019
Country
China
Website
z.ai
Vendor Details
Company Name
Subquadratic
Founded
2024
Country
United States
Website
subq.ai/introducing-subq-snap