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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. Nemotron 3.5 Super VL (Free)NVIDIARemove
  2. Nemotron 3.5 LightningNVIDIARemove
  3. Gemini 3.5 TranscribeGoogleRemove
nemotron-3.5-super-vl:free vs nemotron-3.5-lightning vs gemini-3.5-transcribe
AttributeNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeNemotron 3.5 Lightningnemotron-3.5-lightningGemini 3.5 Transcribegemini-3.5-transcribe
Pricing
Input$0 / 1M— Not priced per input token— Not priced per input token
Output$0 / 1M— Not priced per output token— Not priced per output token
Cache Write$0 / 1M——
Cache Read$0 / 1M$0.00 / 1MNot applicable
Cache Write (5m)—$0.00 / 1MNot applicable
Cache Write (1h)—$0.00 / 1MNot applicable
Web Search—$0 / 1M$0 / 1M
Context
Max context1M1M98.3K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderNVIDIANVIDIAGoogle
Categorychatchatvoice
Charge typeFreePay As You GoPay As You Go
Released——2026-09-25
Description
SummaryNVIDIA 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.NVIDIA Nemotron 3.5 Lightning is an open Mixture-of-Experts (MoE) model with 30B total parameters and 3B active per token, optimized for high-throughput agentic workloads and efficient inference. Its lightweight active compute and open design make it well suited for specialized agents, domain-specific customization, and scalable production deployments where speed, cost efficiency, and adaptability are key.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.