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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 VLNVIDIARemove
  2. Gemini 3.5 TranscribeGoogleRemove
  3. Nemotron 3.5 Super VL (Free)NVIDIARemove
nemotron-3.5-super-vl vs gemini-3.5-transcribe vs nemotron-3.5-super-vl:free
AttributeNemotron 3.5 Super VLnemotron-3.5-super-vlGemini 3.5 Transcribegemini-3.5-transcribeNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free
Pricing
Input$0.10 / 1M— Not priced per input token$0 / 1M
Output$0.40 / 1M— Not priced per output token$0 / 1M
Cache Write (5m)$0.10 / 1MNot applicable—
Cache Write (1h)$0.10 / 1MNot applicable—
Cache Read$0.10 / 1MNot applicable$0 / 1M
Web Search$0 / 1M$0 / 1M—
Cache Write——$0 / 1M
Context
Max context1M98.3K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderNVIDIAGoogleNVIDIA
Categorychatvoicechat
Charge typePay As You GoPay As You GoFree
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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.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.