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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. Jina Embeddings V2 Base ESJina AIRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
jina-embeddings-v2-base-es vs nemotron-3.5-super-vl:free
AttributeJina Embeddings V2 Base ESjina-embeddings-v2-base-esNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free
Pricing
Input$0.05 / 1M$0 / 1M
Output— Not priced per output token$0 / 1M
Cache Write (5m)$0.05 / 1M—
Cache Write (1h)$0.05 / 1M—
Cache Read$0.05 / 1M$0 / 1M
Cache Write—$0 / 1M
Context
Max context8.2K1M
Max outputN/AN/A
Capabilities
VisionNoYes
Function CallingNoYes
JSON ModeNoYes
StreamingNoYes
Catalogue
ProviderJina AINVIDIA
Categoryembeddingchat
Charge typePay As You GoFree
Released——
Description
Summary—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.