SubQ Snap

SubQ Snap

Subquadratic
+
+

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About

GLM-5.3-Flash is Z.ai’s natively multimodal model in the GLM-5 series (previously previewed as Ox Alpha), designed to deliver strong coding, agentic, visual, and knowledge-work performance at relatively low inference cost. It uses 320 billion total parameters with 18 billion active parameters, along with a hybrid architecture that combines sparse and linear attention to reduce the cost of long-context processing. The model supports context lengths of up to one million tokens and was trained on a 30-trillion-token multimodal corpus. GLM-5.3-Flash can reason across text, images, documents, interfaces, dashboards, and other visual information while using that feedback to refine its own outputs. Z.ai reports substantial gains over GLM-5.2 on coding and agentic benchmarks, including DeepSWE and AutomationBench, while approaching higher-cost frontier models on several evaluations.

About

SubQ Snap is a long-context decision model for enterprise and agentic workflows, built to make structured decisions quickly over large amounts of information. It handles tasks such as choosing which files are relevant, selecting the next tool, checking whether a result passes, deciding whether a workflow should continue, and determining when a frontier model is needed. Instead of generating open-ended text, Snap takes context, a question, and a finite set of allowed answers, then returns a probability distribution over those answers. It supports up to 384K tokens of mixed text and image context, allowing it to reason over codebases, contracts, interaction histories, logs, screenshots, charts, diagrams, and scanned pages in a single call. Powered by Subquadratic Sparse Attention, Snap reduces the cost of reading long inputs while a decision head maps contextual representations directly to admissible answers without autoregressive generation.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers, AI engineers, agent builders, researchers, and organizations that need cost-efficient multimodal reasoning, long-context processing, advanced coding, visual analysis, and autonomous workflow capabilities

Audience

Developers and enterprise AI teams interested in a tool to make fast, structured decisions across long documents, codebases, multimodal inputs, and agentic workflows

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$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
Free Version Not Supported
Free Trial Not Supported

Pricing

$0.05 per million input tokens
Free Version Not Supported
Free Trial Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Pros & Cons from Real Users

Pros

  • What makes it exciting is that it seems built for the exact workloads developers care about right now: long-horizon coding, complex reasoning, big-context analysis, and agentic workflows. A million-token context window is especially useful if you want to drop in a large repo, long spec, research corpus, or messy project history and have the model reason across it.

Cons

  • I would treat it as something exciting to test, not something to blindly trust with sensitive work. Even the independent Ox Alpha site warns that messages are processed by the upstream model API, so I would keep secrets, private code, and customer data out of it until there is a clearer owner, model card, privacy policy, and production story.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Z.ai
Founded: 2019
China
z.ai

Company Information

Subquadratic
Founded: 2024
United States
subq.ai/introducing-subq-snap

Alternatives

Alternatives

Clef-flash

Clef-flash

Cloudflare
Clef

Clef

Cloudflare
Jev

Jev

TypeSafe AI
MiniMax M3

MiniMax M3

MiniMax
Liquid d1

Liquid d1

Liquid AI
Qwen3.5

Qwen3.5

Alibaba
Strands Decider

Strands Decider

Strands Labs

Categories

AI Coding Models Supported
AI Models Supported
Multimodal Models Supported

Categories

AI Decision Models Supported

Integrations

Cheaper Inference Supported
Claude Code Supported
DeepSeek Harness Supported
GLM Coding Plan Supported
Hermes Agent Supported
OpenClaw Supported
OpenCode Go Supported
OpenCode Zen Supported
OpenRouter Supported
Pi Agent Supported
Z.ai Supported
omp Supported

Integrations

Cheaper Inference Not Supported
Claude Code Not Supported
DeepSeek Harness Not Supported
GLM Coding Plan Not Supported
Hermes Agent Not Supported
OpenClaw Not Supported
OpenCode Go Not Supported
OpenCode Zen Not Supported
OpenRouter Not Supported
Pi Agent Not Supported
Z.ai Not Supported
omp Not Supported
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