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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. Gemini 3.5 TranscribeGoogleRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. Nemotron 3.5 Super VL (Free)NVIDIARemove
gemini-3.5-transcribe vs gemini-3.8-flash vs nemotron-3.5-super-vl:free
AttributeGemini 3.5 Transcribegemini-3.5-transcribeGemini 3.8 Flashgemini-3.8-flashNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free
Pricing
Input— Not priced per input token$0.75 / 1M$0 / 1M
Output— Not priced per output token$3.75 / 1M$0 / 1M
Cache Write (5m)Not applicable$0.75 / 1M—
Cache Write (1h)Not applicable$0.75 / 1M—
Cache ReadNot applicable$0.75 / 1M$0 / 1M
Web Search$0 / 1M$0 / 1M—
Cache Write——$0 / 1M
Context
Max context98.3K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleGoogleNVIDIA
Categoryvoicechatchat
Charge typePay As You GoPay As You GoFree
Released2026-09-25——
Description
SummaryGoogle Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.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.