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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. Gemma 4 26B A4BGoogleRemove
nemotron-3.5-super-vl vs gemma-4-26b-a4b-it
AttributeNemotron 3.5 Super VLnemotron-3.5-super-vlGemma 4 26B A4Bgemma-4-26b-a4b-it
Pricing
Input$0.10 / 1M$0.13 / 1M
Output$0.40 / 1M$0.40 / 1M
Cache Write (5m)$0.10 / 1M$0.13 / 1M
Cache Write (1h)$0.10 / 1M$0.13 / 1M
Cache Read$0.10 / 1M$0.13 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M262.1K
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderNVIDIAGoogle
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
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.Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind, featuring 25.2B total parameters with only 3.8B activated per token—delivering near 31B-class quality at a fraction of the compute cost. It supports multimodal inputs including text, images, and video (up to 60s at 1fps). The model includes a 256K token context window, native function calling, configurable thinking/reasoning modes, and structured output support. Released under the Apache 2.0 license, it is well suited for efficient, production-ready multimodal and agentic applications.