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

  1. Veo 3GoogleRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
  3. Gemini 3.1 Flash Lite Image (Google Vertex AI)GoogleRemove
veo3 vs nemotron-3.5-super-vl:free vs gemini-3.1-flash-lite-image-vertex
AttributeVeo 3veo3Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeGemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertex
Pricing
Request$1.26 / request—$0.0336 / request
BillingPay Per Request—Pay Per Request
Cache Write (5m)Not applicable—Not applicable
Cache Write (1h)Not applicable—Not applicable
Cache ReadNot applicable$0 / 1MNot applicable
Input—$0 / 1M—
Output—$0 / 1M—
Cache Write—$0 / 1M—
Context
Max contextN/A1MN/A
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesNo
JSON ModeNoYesNo
StreamingNoYesNo
Catalogue
ProviderGoogleNVIDIAGoogle
Categoryvideochatimage
Charge typePay Per RequestFreePay Per Request
Released———
Description
Summary—NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications.Gemini 3.1 Flash Lite Image served from Google Vertex AI. Billed per image at US$0.0336. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 1K. A request for a larger size returns a 1K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size.