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Average Ratings 0 Ratings

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ease
features
design
support

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Description

GLM-5 is a next-generation open-source foundation model from Z.ai designed to push the boundaries of agentic engineering and complex task execution. Compared to earlier versions, it significantly expands parameter count and training data, while introducing DeepSeek Sparse Attention to optimize inference efficiency. The model leverages a novel asynchronous reinforcement learning framework called slime, which enhances training throughput and enables more effective post-training alignment. GLM-5 delivers leading performance among open-source models in reasoning, coding, and general agent benchmarks, with strong results on SWE-bench, BrowseComp, and Vending Bench 2. Its ability to manage long-horizon simulations highlights advanced planning, resource allocation, and operational decision-making skills. Beyond benchmark performance, GLM-5 supports real-world productivity by generating fully formatted documents such as .docx, .pdf, and .xlsx files. It integrates with coding agents like Claude Code and OpenClaw, enabling cross-application automation and collaborative agent workflows. Developers can access GLM-5 via Z.ai’s API, deploy it locally with frameworks like vLLM or SGLang, or use it through an interactive GUI environment. The model is released under the MIT License, encouraging broad experimentation and adoption. Overall, GLM-5 represents a major step toward practical, work-oriented AI systems that move beyond chat into full task execution.

Description

GPT-5.3-Codex-Spark is OpenAI’s first model purpose-built for real-time coding within the Codex ecosystem. Engineered for ultra-low latency, it can generate more than 1000 tokens per second when running on Cerebras’ Wafer Scale Engine hardware. Unlike larger frontier models designed for long-running autonomous tasks, Codex-Spark specializes in rapid iteration, targeted edits, and immediate feedback loops. Developers can interrupt, redirect, and refine outputs interactively, making it ideal for collaborative coding sessions. The model features a 128k context window and is currently text-only during its research preview phase. End-to-end latency improvements—including WebSocket streaming and inference stack optimizations—reduce time-to-first-token by 50% and overall roundtrip overhead by up to 80%. Codex-Spark performs strongly on benchmarks such as SWE-Bench Pro and Terminal-Bench 2.0 while completing tasks significantly faster than its larger counterpart. It is available to ChatGPT Pro users in the Codex app, CLI, and VS Code extension with separate rate limits during preview. The model maintains OpenAI’s standard safety training and evaluation protocols. Codex-Spark represents the beginning of a dual-mode Codex future that blends real-time interaction with long-horizon reasoning capabilities.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

OpenClaw Yes 
APIFree Yes 
Cheaper Inference Yes 
Cherry Studio Yes 
Claw Code Yes 
Cline Yes 
Codex CLI No 
Codex Security No 
GLM-5-Turbo Yes 
Kilo Code Yes 
Microsoft Foundry No 
Ollama Yes 
OpenAI No 
OpenAI Codex No 
Oxlo.ai Yes 
Qoder Yes 
Shiori Yes 
Tabbit Browser Yes 
Yonoo Yes 
Zo Computer Yes 

Integrations

OpenClaw Yes 
APIFree No 
Cheaper Inference No 
Cherry Studio No 
Claw Code No 
Cline No 
Codex CLI Yes 
Codex Security Yes 
GLM-5-Turbo No 
Kilo Code No 
Microsoft Foundry Yes 
Ollama No 
OpenAI Yes 
OpenAI Codex Yes 
Oxlo.ai No 
Qoder No 
Shiori No 
Tabbit Browser No 
Yonoo No 
Zo Computer No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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

2023

Country

China

Website

z.ai/

Vendor Details

Company Name

OpenAI

Founded

2015

Country

United States

Website

openai.com

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