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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. Nemotron 3.5 Super VL (Free)NVIDIARemove
  3. Qwen3 Reranker 8BRerankerRemove
nemotron-3.5-super-vl vs nemotron-3.5-super-vl:free vs Qwen/Qwen3-Reranker-8B
AttributeNemotron 3.5 Super VLnemotron-3.5-super-vlNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeQwen3 Reranker 8BQwen/Qwen3-Reranker-8B
Pricing
Input$0.10 / 1M$0 / 1M$0.56 / 1M
Output$0.40 / 1M$0 / 1M$0.56 / 1M
Cache Write (5m)$0.10 / 1M—Not applicable
Cache Write (1h)$0.10 / 1M—Not applicable
Cache Read$0.10 / 1M$0 / 1MNot applicable
Web Search$0 / 1M—$0 / 1M
Cache Write—$0 / 1M—
Context
Max context1M1M8.2K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderNVIDIANVIDIAReranker
Categorychatchatchat
Charge typePay As You GoFreePay 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.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.—