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