GLM-5.3-Flash
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What is Nemotron 3.5 Lightning?
NVIDIA's Nemotron 3.5 Lightning represents an advanced mixture-of-experts model that features an impressive 30 billion parameters, with 3 billion of these actively engaged, and is specifically designed to deliver efficient, high-throughput performance for AI agents that operate continuously over extended periods. This model is crafted for the execution aspects of agentic systems, skillfully handling common tasks such as invoking tools, verifying outputs, carrying out routine commands, and assigning responsibilities to subagents, while larger reasoning models focus on strategic planning and orchestration. By utilizing a mixture-of-experts framework, it selectively engages a limited number of parameters for each input token, effectively combining the vast potential of a larger model with substantially decreased computational requirements. The training process is fine-tuned for popular agent harnesses, significantly improving inference speed through methods like speculative decoding, multi-token prediction, DFlash, and DSpark, which enhance its adaptability to various operational contexts. Moreover, it supports BF16 and NVFP4 checkpoints, ensuring deployment flexibility across platforms ranging from local systems such as DGX Spark and GeForce RTX hardware to large-scale data center environments. This innovative design not only amplifies AI capabilities but also positions Nemotron 3.5 Lightning as a pivotal resource for the evolution of intelligent systems, paving the way for future advancements in the field.
What is GLM-5.3-Flash?
GLM-5.3-Flash is an efficiency-focused multimodal AI model from Z.ai that combines advanced reasoning, coding, agentic execution, and visual intelligence. It is the first GLM-5-series model designed with native multimodal capabilities, allowing it to work directly with both textual and visual inputs. The architecture uses 320 billion total parameters while activating only 18 billion at a time, significantly reducing the amount of computation required for inference. A hybrid attention design blends linear attention for local information with sparse attention for retrieving important context from much larger inputs. Z.ai also uses technologies such as IndexPool and Manifold-Constrained Hyper-Connections to improve memory efficiency, latency, and model scaling. The model can operate with context windows of up to one million tokens, making it suitable for large repositories, lengthy documents, extended agent sessions, and complex multimodal workflows. GLM-5.3-Flash was trained on a 30-trillion-token multimodal corpus intended to strengthen reasoning across code, images, interfaces, documents, spreadsheets, presentations, and other business artifacts. In software development scenarios, the model can visually inspect rendered applications, evaluate its own output, and iteratively correct layout, functionality, or interaction issues. Z.ai’s reported benchmark results show large improvements over GLM-5.2 in areas such as software engineering and automation, while placing GLM-5.3-Flash close to leading frontier systems on several coding and agentic evaluations. Before its formal release, the model was anonymously tested under the name ox-alpha on OpenCode and OpenRouter, where Z.ai says it became one of the most widely used models during its testing period. GLM-5.3-Flash is available through Z.ai’s API and coding products as well as through downloadable weights on Hugging Face, with deployment support for SGLang, vLLM, and TokenSpeed.
Integrations Supported
Hermes Agent
OpenClaw
NVIDIA NemoClaw
Integrations Supported
Hermes Agent
OpenClaw
Cheaper Inference
Claude Code
DeepSeek Harness
GLM Coding Plan
OpenCode Go
OpenCode Zen
OpenRouter
API Availability
API Availability
Has API
Pricing Information
Pricing not provided
Pricing Information
$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
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
NVIDIA
Date Founded
1993
Company Location
United States
Company Website
nvidia.com
Company Facts
Organization Name
Z.ai
Date Founded
2019
Company Location
China
Company Website
z.ai
Categories and Features
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
AI Reasoning Models
Not specified
Large Language Models
Not specified
Multimodal Models
Not specified
Open-Weight AI Models
Not specified