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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. Nemotron 3.5 Super VLNVIDIARemove
  3. Magistral Medium 2506 (Thinking)Mistral AIRemove
nemotron-3.5-super-vl:free vs nemotron-3.5-super-vl vs magistral-medium-2506:thinking
AttributeNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeNemotron 3.5 Super VLnemotron-3.5-super-vlMagistral Medium 2506 (Thinking)magistral-medium-2506:thinking
Pricing
Input$0 / 1M$0.10 / 1M$2.00 / 1M
Output$0 / 1M$0.40 / 1M$5.00 / 1M
Cache Write$0 / 1M——
Cache Read$0 / 1M$0.10 / 1M$2.00 / 1M
Cache Write (5m)—$0.10 / 1M$2.00 / 1M
Cache Write (1h)—$0.10 / 1M$2.00 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context1M1M41.0K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderNVIDIANVIDIAMistral AI
Categorychatchatchat
Charge typeFreePay 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.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.—