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Nemotron 3.5 Super VL

by NVIDIA · Released Oct 2026

Multimodal1M Context
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Context
1.0M tokens (~524 books)
Input $/1M
$0.15
Output $/1M
$0.50
Type
multimodal
License
Proprietary
Benchmarks
6 tested
Data as of
About

NVIDIA Nemotron 3.5 Super VL is an open vision-language model with 120B total and 12B active parameters, a Mamba-2 and Transformer hybrid MoE with a C-RADIO vision encoder, built for long-running agents, tool use, document and video understanding. Up to 1M tokens of context. OpenMDW-1.1.

Tested on 6 benchmarks. Top scores: Artificial Analysis · Long Context Reasoning (69.0%), Artificial Analysis · SciCode (47.8%), Artificial Analysis · GDPval (33.1%).

Capabilities
speed
36.3
#76 globally
Benchmark Scores
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Tested on 6 benchmarks · Ranked across 1 categories
Score Distribution (all 319 models)
0255075100
Excellent (85+) Good (70-85) Average (50-70) Below (<50)
Links
Documentation
Community
BenchGecko API
nemotron-3-5-super-vl
Specifications
  • Typemultimodal
  • Context1.0M tokens (~524 books)
  • ReleasedOct 2026
  • LicenseProprietary
  • StatusActive
  • Cost / Message~$0.001
Available On
NVIDIA logoNVIDIA$0.15
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Nemotron 3.5 Super VL is a proprietary multimodal AI model by NVIDIA, released in October 2026. Context window: 1M tokens.

Key facts · as of 2026-10-16

  • Nemotron 3.5 Super VL by NVIDIA. Not enough public benchmark scores to rank yet.
  • List price $0.15 input · $0.50 output per 1M tokens (as of 2026-10-16).
  • Sold by 5 providers (as of 2026-10-16): Crusoe (bf16) $0.10 in / $0.40 out · CoreWeave (nvfp4) $0.15 in / $0.75 out · Together $0.15 in / $0.50 out · DeepInfra (fp4) $0.20 in / $1.00 out · Venice (fp4) $0.25 in / $1.25 out. Every provider

How to cite · data as of 2026-10-16

Nemotron 3.5 Super VL · benchmarks, pricing and providers. BenchGecko, data as of 2026-10-16. https://benchgecko.ai/model/nemotron-3-5-super-vl

Credit "Source: BenchGecko" with a link. Prices per provider and Gecko Tests are BenchGecko data (CC BY 4.0); benchmark scores keep their original source, listed in the JSON. JSON · llms.txt · MCP