Skip to content
Apertis
Get started

Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Nemotron 3 Nano Omni (Free)NVIDIARemove
  2. GLM 5.3 FlashZ.AIRemove
nemotron-3-nano-omni-30b-a3b-reasoning:free vs glm-5.3-flash
AttributeNemotron 3 Nano Omni (Free)nemotron-3-nano-omni-30b-a3b-reasoning:freeGLM 5.3 Flashglm-5.3-flash
Pricing
Input$0 / 1M$0.075 / 1M
Output$0 / 1M$0.25 / 1M
Cache Write$0 / 1M—
Cache Read$0 / 1M$0.075 / 1M
Cache Write (5m)—$0.075 / 1M
Cache Write (1h)—$0.075 / 1M
Web Search—$0 / 1M
Context
Max context256K1M
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderNVIDIAZ.AI
Categorychatchat
Charge typeFreePay As You Go
Released——
Description
SummaryNVIDIA Nemotron 3 Nano Omni is an open 30B-A3B multimodal model designed as a perception and context sub-agent for enterprise agent systems. It supports text, image, video, and audio inputs with text output, enabling unified multimodal reasoning within a single inference loop. Built on a hybrid MoE Transformer–Mamba architecture with Conv3D video layers and Efficient Video Sampling (EVS), it delivers significantly improved efficiency for video reasoning—achieving ~2× higher throughput and 2.5× lower compute compared to separate pipelines. With up to 300K context length and extended thinking support, it is well suited for scalable, multimodal agent workflows.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.