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NVIDIA: NVIDIA: Nemotron 3.5 Super VL

NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video...

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API record Report
InputT
OutputT
Input price$0.15/M
Output price$0.5/M
Context262.144K
Max output235.929K
Providers0
Inference availability

Providers

Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.

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Specification

Capabilities

Recorded from the source catalog and provider listings.

? Reasoning Unknown
? Tool calling Unknown
? Structured output Unknown
? Attachments Unknown
✓ Vision input Yes
? Open weights Unknown
Creator
NVIDIA
Model family
Not documented
Knowledge cutoff
Not documented
License
Not documented
Release date
Not documented
Model ID
nvidia/nemotron-3.5-super-vl
Published evaluations

Benchmarks

Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.

Benchmark registry
Benchmark profile
IntelligenceIntelligence Index Design Arena: w…Design Arena: website Design Arena: g…Design Arena: gamedev Design Arena: c…Design Arena: codecategories Design Arena: u…Design Arena: uicomponent Design Arena: 3dDesign Arena: 3d This model — Intelligence Index: 26.5 index (65.9th percentile) This model — Design Arena: website: 1172 elo (37.0th percentile) This model — Design Arena: gamedev: 1110 elo (27.7th percentile) This model — Design Arena: codecategories: 1155 elo (33.5th percentile) This model — Design Arena: uicomponent: 1153 elo (34.1th percentile) This model — Design Arena: 3d: 1126 elo (35.2th percentile)

Each axis is this model's percentile among the 6 benchmarks it has published results for, measured against every other model with a score on that same benchmark. Percentiles are used because benchmarks do not share a scale — a 60 on one is not a 60 on another. Hover any point for the raw score.

Intelligence Index index Source ↗
Intelligence Index #114 of 334
Design Arena: website elo Source ↗
Design Arena: website #126 of 200
Design Arena: gamedev elo Source ↗
Design Arena: gamedev #138 of 191
Design Arena: codecategories elo Source ↗
Design Arena: codecategories #125 of 188
Design Arena: uicomponent elo Source ↗
Design Arena: uicomponent #120 of 182
Design Arena: 3d elo Source ↗
Design Arena: 3d #114 of 176

Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.

Cost against capability

Price and performance

Listed input price plotted against Intelligence Index, the benchmark with the widest published coverage that this model appears in.

0 31 61 $0.01 $0.1 $1 $10 $100 Nova 2 Lite — $0.3/M, score 13.4 Nova Lite 1.0 — $0.059/M, score 6.7 Nova Micro 1.0 — $0.035/M, score 5.9 Amazon: Nova Premier 1.0 — $2.5/M, score 9.2 Nova Pro 1.0 — $0.799/M, score 7.0 Claude Fable 5 — $10/M, score 49.6 Anthropic: Claude Fable 5.1 — $10/M, score 53.4 Anthropic: Claude Fable 5.1 (batch) — $5/M, score 53.4 Anthropic: Claude Fable 5 (batch) — $5/M, score 49.6 Anthropic: Claude Haiku 4.5 — $1/M, score 16.9 Anthropic: Claude Haiku 4.5 (batch) — $0.5/M, score 16.9 Anthropic: Claude Haiku 5.5 — $0.1/M, score 43.4 Anthropic: Claude Haiku 5.5 (batch) — $0.05/M, score 43.4 Anthropic: Claude Opus 4.1 — $15/M, score 22.8 Anthropic: Claude Opus 4.1 (batch) — $7.5/M, score 22.8 Anthropic: Claude Opus 4.5 — $5/M, score 29.1 Anthropic: Claude Opus 4.5 (batch) — $2.5/M, score 29.1 Anthropic: Claude Opus 4.6 — $5/M, score 31.9 Anthropic: Claude Opus 4.6 (batch) — $2.5/M, score 31.9 Anthropic: Claude Opus 4.7 — $5/M, score 40.7 Anthropic: Claude Opus 4.7 (batch) — $2.5/M, score 40.7 Anthropic: Claude Opus 4.8 — $5/M, score 41.8 Anthropic: Claude Opus 4.8 (batch) — $2.5/M, score 41.8 Claude Opus 5 — $5/M, score 50.8 Anthropic: Claude Opus 5.5 — $4/M, score 57.6 Anthropic: Claude Opus 5.5 (batch) — $2/M, score 57.6 Anthropic: Claude Opus 5 (batch) — $2.5/M, score 50.8 Anthropic: Claude Sonnet 4 — $3/M, score 18.9 Anthropic: Claude Sonnet 4.5 — $3/M, score 20.7 Anthropic: Claude Sonnet 4.5 (batch) — $1.5/M, score 20.7 Anthropic: Claude Sonnet 4.6 — $3/M, score 30.1 Anthropic: Claude Sonnet 4.6 (batch) — $1.5/M, score 30.1 Claude Sonnet 5 — $2/M, score 38.2 Anthropic: Claude Sonnet 5.5 — $2/M, score 56.0 Anthropic: Claude Sonnet 5.5 (batch) — $1/M, score 56.0 Anthropic: Claude Sonnet 5 (batch) — $1/M, score 38.2 Trinity Large Thinking — $0.25/M, score 10.8 Command A — $2.5/M, score 13.1 DeepSeek V3 0324 — $0.2/M, score 9.7 DeepSeek V3.1 — $0.19/M, score 13.7 DeepSeek-R1 — $0.58/M, score 11.4 DeepSeek R1 0528 — $0.2/M, score 13.1 DeepSeek: DeepSeek V3.1 Terminus — $0.27/M, score 14.8 DeepSeek V3.2 — $0.209/M, score 21.5 DeepSeek: DeepSeek V3.2 Exp — $0.27/M, score 16.6 DeepSeek V4 Flash — $0.15/M, score 24.4 DeepSeek V4 Flash 0731 — $0.035/M, score 34.3 DeepSeek: DeepSeek V4 Flash 0731 (batch) — $0.11/M, score 34.3 DeepSeek V4 Flash Vision Exp — $0.15/M, score 34.8 DeepSeek V4 Pro — $0.66/M, score 30.4 DeepSeek V4 Pro 0813 — $0.132/M, score 36.0 DeepSeek: DeepSeek V4 Pro 0813 (batch) — $0.66/M, score 36.0 DeepSeek V4.1 Flash — $0.02/M, score 24.7 DeepSeek V4.1 Flash 1017 — $0.15/M, score 39.5 DeepSeek: DeepSeek V4.1 Flash (batch) — $0.05/M, score 24.7 Gemini 2.5 Flash — $0.3/M, score 15.5 Gemini 2.5 Flash-Lite — $0.1/M, score 10.4 Google: Gemini 2.5 Flash Lite (batch) — $0.05/M, score 10.4 Google: Gemini 2.5 Flash (batch) — $0.15/M, score 15.5 Gemini 2.5 Pro — $1.25/M, score 16.1 Google: Gemini 2.5 Pro (batch) — $0.625/M, score 16.1 Gemini 3 Flash Preview — $0.5/M, score 26.3 Google: Gemini 3 Flash Preview (batch) — $0.25/M, score 26.3 Gemini 3.1 Flash Lite Preview — $0.25/M, score 15.6 Gemini 3.1 Pro Preview — $2/M, score 29.7 Google: Gemini 3.1 Pro Preview (batch) — $1/M, score 29.7 Gemini 3.5 Flash — $1.5/M, score 33.6 Gemini 3.5 Flash Lite — $0.3/M, score 22.2 Google: Gemini 3.5 Flash Lite (batch) — $0.15/M, score 22.2 Google: Gemini 3.5 Flash (batch) — $0.75/M, score 33.6 Gemini 3.6 Flash — $0.75/M, score 34.0 Google: Gemini 3.6 Flash (batch) — $0.375/M, score 34.0 Gemini 3.7 Flash — $0.75/M, score 39.6 Google: Gemini 3.7 Flash (batch) — $0.375/M, score 39.6 Gemini 3.8 Flash — $0.75/M, score 40.9 Google: Gemini 3.8 Flash (batch) — $0.375/M, score 40.9 Gemini 4 Argon — $2/M, score 52.6 Google: Gemini 4 Argon (batch) — $1/M, score 52.6 Gemma 3 12B IT — $0.04/M, score 3.8 Gemma 3 27B IT — $0.08/M, score 4.9 Gemma 3 4B IT — $0.04/M, score 4.8 Gemma 4 26B A4B IT — $0.042/M, score 16.7 Gemma 4 31B IT — $0.1/M, score 14.7 Google: Gemma 4 31B (batch) — $0.39/M, score 15.4 IBM: Granite 4.0 Micro — $0.017/M, score 5.1 IBM: Granite 4.2 8B — $0.06/M, score 11.1 Mercury 2 — $0.25/M, score 10.8 Mercury 2.5 — $0.2/M, score 12.3 inclusionAI: Ling-2.6-flash — $0.01/M, score 14.2 Ling 3.0 Flash — $0.021/M, score 20.1 Ling 3.0 Flash Fin — $0.075/M, score 22.6 Ling 3.0 Flash VL — $0.06/M, score 24.6 Ling 3.1 Flash — $0.075/M, score 41.1 inclusionAI: Ring-2.6-1T — $0.075/M, score 31.1 Kwaipilot: KAT-Coder-Pro V2 — $0.3/M, score 33.7 LongCat-2.0 — $0.3/M, score 19.1 Meta: Llama 3.1 70B Instruct — $0.4/M, score 6.6 Meta: Llama 3.1 8B Instruct — $0.05/M, score 6.9 Meta: Llama 3.2 1B Instruct — $0.027/M, score 4.8 Meta: Llama 3.2 3B Instruct — $0.051/M, score 5.7 Meta: Llama 3.3 70B Instruct — $0.1/M, score 7.7 Meta: Llama 4 Maverick — $0.188/M, score 9.3 Meta: Llama 4 Scout — $0.1/M, score 6.5 Muse Glimmer 30B — $0.2/M, score 17.5 Muse Spark 1.1 — $1.25/M, score 33.7 Muse Spark 1.2 — $1.25/M, score 39.6 Muse Spark 1.3 — $1.25/M, score 48.1 Microsoft: Phi 4 — $0.07/M, score 5.9 MiniMax: MiniMax M1 — $0.55/M, score 11.7 MiniMax: MiniMax M2 — $0.255/M, score 18.6 MiniMax: MiniMax M2.1 — $0.3/M, score 20.9 MiniMax: MiniMax M2.5 — $0.3/M, score 22.8 MiniMax: MiniMax M2.7 — $0.3/M, score 22.8 MiniMax: MiniMax M3 — $0.3/M, score 29.2 MiniMax: MiniMax M3.1 Flash — $0.15/M, score 42.7 MiniMax: MiniMax M3 (batch) — $0.3/M, score 29.2 Mistral: Devstral 2 2512 — $0.4/M, score 8.6 Mistral: Ministral 3 14B 2512 — $0.2/M, score 6.0 Mistral: Ministral 3 3B 2512 — $0.1/M, score 4.8 Mistral: Ministral 3 8B 2512 — $0.15/M, score 5.5 Mistral: Ministral 3 8B 2512 (batch) — $0.075/M, score 5.5 Mistral Large — $2/M, score 5.8 Mistral Large 2407 — $2/M, score 7.6 Mistral: Mistral Large 3 2512 — $0.5/M, score 9.3 Mistral: Mistral Large 3 2512 (batch) — $0.25/M, score 9.3 Mistral: Mistral Large 4 — $1.36/M, score 38.4 Mistral: Mistral Medium 3 — $0.4/M, score 9.0 Mistral: Mistral Medium 3.5 — $1.5/M, score 14.2 Mistral: Mistral Medium 3.5 (batch) — $0.75/M, score 14.2 Mistral: Mistral Medium 3.1 — $0.4/M, score 9.2 Mistral: Mistral Medium 3.1 (batch) — $0.2/M, score 9.2 Mistral: Saba — $0.2/M, score 6.5 Mistral: Mistral Small 3 — $0.05/M, score 6.7 Mistral: Mistral Small 4 — $0.15/M, score 11.3 Mistral: Mistral Small 4 (batch) — $0.075/M, score 11.3 Mistral: Mixtral 8x22B Instruct — $2/M, score 5.7 Kimi K2 0711 — $0.4/M, score 12.7 Kimi K2 Instruct 0905 — $0.6/M, score 15.3 Kimi K2 Thinking — $0.4/M, score 22.0 Kimi K2.5 — $0.375/M, score 23.5 Kimi K2.6 — $0.95/M, score 27.0 Kimi K2.7 Code — $0.95/M, score 25.8 MoonshotAI: Kimi K2.7 Code (batch) — $0.475/M, score 43.0 Kimi K3 — $3/M, score 43.6 Kimi K3.1 Pro — $2/M, score 55.1 MoonshotAI: Kimi K3 (batch) — $2.28/M, score 43.6 Nex-N2-Pro — $0.5/M, score 41.7 Hermes 3 405B Instruct — $1/M, score 7.4 Hermes 3 70B Instruct — $0.7/M, score 6.7 Hermes 4 405B — $0.996/M, score 7.5 Nemotron 3 Nano 30B A3B — $0.05/M, score 8.9 Nemotron 3 Super 120B A12B — $0.05/M, score 12.8 Nemotron 3 Ultra 550B A55B — $0.1/M, score 22.9 NVIDIA: Nemotron 3 Ultra (batch) — $0.6/M, score 38.3 Nemotron 3.5 Lightning 30B A3B — $0.025/M, score 12.9 NVIDIA: Nemotron 3.5 Super VL — $0.15/M, score 26.5 GPT-3.5-turbo — $0.5/M, score 5.5 OpenAI: GPT-3.5 Turbo (batch) — $0.25/M, score 5.5 GPT-4 — $30/M, score 6.7 GPT-4 Turbo — $10/M, score 7.0 OpenAI: GPT-4 Turbo (batch) — $5/M, score 7.0 GPT-4.1 — $2/M, score 12.7 GPT-4.1 mini — $0.4/M, score 10.2 OpenAI: GPT-4.1 Mini (batch) — $0.2/M, score 10.2 GPT-4.1 nano — $0.1/M, score 7.8 OpenAI: GPT-4.1 Nano (batch) — $0.05/M, score 7.8 OpenAI: GPT-4.1 (batch) — $1/M, score 12.7 GPT-4o (2024-05-13) — $5/M, score 7.3 GPT-4o (2024-08-06) — $2.5/M, score 7.7 GPT-4o (2024-11-20) — $2.5/M, score 8.4 GPT-4o mini — $0.15/M, score 6.7 OpenAI: GPT-4o-mini (batch) — $0.075/M, score 6.7 GPT-5 — $1.25/M, score 23.0 GPT-5 Mini — $0.25/M, score 20.6 OpenAI: GPT-5 Mini (batch) — $0.125/M, score 20.6 GPT-5 Nano — $0.05/M, score 13.0 OpenAI: GPT-5 Nano (batch) — $0.025/M, score 13.0 GPT-5.1 — $1.25/M, score 24.7 GPT-5.1 Codex — $1.07/M, score 23.7 GPT-5.1 Codex mini — $0.22/M, score 20.4 OpenAI: GPT-5.1 (batch) — $0.625/M, score 24.7 GPT-5.2 — $1.75/M, score 30.4 GPT-5.2 Codex — $0.14/M, score 28.5 OpenAI: GPT-5.2 (batch) — $0.875/M, score 30.4 GPT-5.3 Codex — $1.75/M, score 32.5 GPT-5.4 — $2.5/M, score 39.0 GPT-5.4 mini — $0.75/M, score 24.1 OpenAI: GPT-5.4 Mini (batch) — $0.375/M, score 24.1 GPT-5.4 nano — $0.2/M, score 20.7 OpenAI: GPT-5.4 Nano (batch) — $0.1/M, score 20.7 OpenAI: GPT-5.4 (batch) — $1.25/M, score 39.0 GPT-5.5 — $5/M, score 38.4 OpenAI: GPT-5.5 (batch) — $2.5/M, score 38.4 GPT-5.6 Luna — $0.2/M, score 37.3 OpenAI: GPT-5.6 Luna (batch) — $0.1/M, score 37.3 GPT-5.6 Sol — $4/M, score 47.0 OpenAI: GPT-5.6 Sol (batch) — $2/M, score 47.0 GPT-5.6 Terra — $2/M, score 42.1 OpenAI: GPT-5.6 Terra (batch) — $1/M, score 42.1 OpenAI: GPT-5 (batch) — $0.625/M, score 23.0 GPT-6 Astra — $10/M, score 52.7 OpenAI: GPT-6 Astra (batch) — $5/M, score 52.7 GPT-6 Luna — $0.1/M, score 38.1 OpenAI: GPT-6 Luna (batch) — $0.05/M, score 38.1 GPT-6 Sol — $2/M, score 47.6 OpenAI: GPT-6 Sol (batch) — $1/M, score 47.6 GPT-6.1 Sol — $2/M, score 51.8 OpenAI: GPT-6.1 Sol (batch) — $1/M, score 51.8 GPT OSS 120B — $0.03/M, score 11.6 OpenAI: gpt-oss-120b (batch) — $0.03/M, score 11.6 GPT OSS 20B — $0.018/M, score 10.0 OpenAI: gpt-oss-20b (batch) — $0.024/M, score 10.0 o1 — $15/M, score 15.2 o1-pro — $150/M, score 12.4 o3 — $2/M, score 20.2 o3-mini — $1.1/M, score 12.5 OpenAI: o3 Mini High — $1.1/M, score 11.0 OpenAI: o3 Mini High (batch) — $0.55/M, score 15.7 OpenAI: o3 Mini (batch) — $0.55/M, score 12.5 o3-pro — $20/M, score 21.9 OpenAI: o3 (batch) — $1/M, score 20.2 o4-mini — $1.1/M, score 16.7 OpenAI: o4 Mini (batch) — $0.55/M, score 16.7 Sonar — $1/M, score 7.7 Sonar Pro — $3/M, score 7.6 Sonar Reasoning Pro — $2/M, score 11.8 Qwen2.5 72B Instruct — $0.36/M, score 7.7 Qwen2.5 Coder 32B Instruct — $0.66/M, score 6.7 Qwen: Qwen3 14B — $0.12/M, score 6.7 Qwen: Qwen3 235B A22B — $0.455/M, score 9.5 Qwen: Qwen3 235B A22B Instruct 2507 — $0.09/M, score 12.0 Qwen: Qwen3 235B A22B Thinking 2507 — $0.45/M, score 12.7 Qwen: Qwen3 30B A3B — $0.12/M, score 7.6 Qwen: Qwen3 30B A3B Instruct 2507 — $0.09/M, score 7.5 Qwen: Qwen3 30B A3B Thinking 2507 — $0.2/M, score 9.8 Qwen: Qwen3 32B — $0.08/M, score 7.3 Qwen: Qwen3 8B — $0.117/M, score 7.3 Qwen: Qwen3 Coder 480B A35B — $0.3/M, score 11.9 Qwen: Qwen3 Coder 30B A3B Instruct — $0.07/M, score 9.6 Qwen: Qwen3 Coder Next — $0.12/M, score 9.2 Qwen: Qwen3 Max — $0.78/M, score 15.6 Qwen: Qwen3 Max Thinking — $0.78/M, score 21.3 Qwen: Qwen3 Next 80B A3B Instruct — $0.09/M, score 9.6 Qwen: Qwen3 Next 80B A3B Thinking — $0.15/M, score 11.2 Qwen: Qwen3 VL 235B A22B Instruct — $0.21/M, score 9.9 Qwen: Qwen3 VL 235B A22B Thinking — $0.4/M, score 13.4 Qwen: Qwen3 VL 30B A3B Instruct — $0.15/M, score 7.9 Qwen: Qwen3 VL 30B A3B Thinking — $0.29/M, score 9.5 Qwen: Qwen3 VL 32B Instruct — $0.104/M, score 11.9 Qwen: Qwen3 VL 8B Instruct — $0.25/M, score 7.3 Qwen: Qwen3 VL 8B Thinking — $0.18/M, score 8.2 Qwen: Qwen3.5-122B-A10B — $0.4/M, score 17.7 Qwen: Qwen3.5-27B — $0.27/M, score 22.9 Qwen: Qwen3.5-35B-A3B — $0.14/M, score 19.3 Qwen: Qwen3.5 397B A17B — $0.5/M, score 21.4 Qwen: Qwen3.5-9B — $0.17/M, score 13.3 Qwen: Qwen3.5-9B (batch) — $0.17/M, score 21.8 Qwen: Qwen3.6 27B — $0.25/M, score 21.4 Qwen: Qwen3.6 35B A3B — $0.1/M, score 18.2 Qwen: Qwen3.6 Max Preview — $1.027/M, score 28.4 Qwen: Qwen3.6 Plus — $0.325/M, score 27.0 Qwen: Qwen3.7 Max — $1.475/M, score 29.5 Qwen: Qwen3.7 Plus — $0.32/M, score 25.2 Qwen: Qwen3.7 Plus (batch) — $0.23/M, score 25.2 Qwen: Qwen3.8 2.4T A95B — $2/M, score 39.9 Qwen: Qwen3.8 2.4T A95B (batch) — $2/M, score 39.9 Qwen: Qwen3.8 27B — $0.2/M, score 33.7 Qwen: Qwen3.8 Max — $2/M, score 53.4 Qwen: Qwen3.8 Max (0902) — $2/M, score 45.4 Reka Flash 3 — $0.1/M, score 6.4 Step 3.5 Flash — $0.105/M, score 17.0 Step 3.7 Flash — $0.202/M, score 19.5 Step 5 Preview — $1.046/M, score 43.7 Hy3 preview — $0.18/M, score 25.3 Inkling — $1/M, score 25.0 Inkling Small — $0.3/M, score 25.7 Thinking Machines: Inkling Small (batch) — $0.5/M, score 26.1 Thinking Machines: Inkling (batch) — $1/M, score 25.0 Solar Mini 4 — $0.1/M, score 24.1 Upstage: Solar Pro 3 — $0.15/M, score 7.8 Solar Pro 4 — $0.3/M, score 28.2 SpaceXAI: Grok 4.20 — $1.25/M, score 25.7 SpaceXAI: Grok 4.3 — $1.25/M, score 24.9 SpaceXAI: Grok 4.3 (batch) — $1/M, score 24.9 SpaceXAI: Grok 4.5 — $2/M, score 38.8 SpaceXAI: Grok 4.6 — $2/M, score 44.3 SpaceXAI: Grok 4.7 — $2/M, score 46.4 SpaceXAI: Grok Build 0.1 — $1/M, score 27.2 MiMo-V2.5 — $0.14/M, score 21.8 MiMo-V2.5-Pro — $0.435/M, score 26.0 MiMo-V2.6-Flash — $0.14/M, score 37.9 MiMo-V2.6-Pro — $0.435/M, score 46.3 Z.ai: GLM 4.5 — $0.6/M, score 12.8 Z.ai: GLM 4.5 Air — $0.13/M, score 11.1 Z.ai: GLM 4.5V — $0.6/M, score 7.6 Z.ai: GLM 4.6 — $0.55/M, score 18.5 Z.ai: GLM 4.6V — $0.3/M, score 11.2 Z.ai: GLM 4.7 — $0.54/M, score 22.2 Z.ai: GLM 4.7 Flash — $0.061/M, score 14.9 Z.ai: GLM 5 — $1/M, score 27.9 Z.ai: GLM 5 Turbo — $1.2/M, score 26.6 Z.ai: GLM 5.1 — $1.4/M, score 26.1 Z.ai: GLM 5.2 — $0.034/M, score 33.7 Z.ai: GLM 5.2 (batch) — $0.7/M, score 33.7 Z.ai: GLM 5.3 — $0.079/M, score 44.8 Z.ai: GLM 5.3 Flash — $0.15/M, score 41.8 Z.ai: GLM 5.3 Flash (batch) — $0.05/M, score 41.8 Z.ai: GLM 5.3 (batch) — $0.45/M, score 44.8 Z.ai: GLM 5V Turbo — $1.2/M, score 23.5 NVIDIA: Nemotron 3.5 Super VL Input price per million tokens (log scale) Index

The stepped line is the efficient frontier: at each price, the best score available for that money or less. A model sitting on it is not being beaten by anything cheaper. Price is log-scaled because listed rates span four orders of magnitude. Only models with both a listed price and a score on this benchmark can appear.

Catalog activity

Change log

Field-level changes detected between successful source imports.

Full change log
Price Completion0.39999999999999997 → 0.5
Price Prompt0.09999999999999999 → 0.15
Price Completion0.5 → 0.39999999999999997
Price Prompt0.15 → 0.09999999999999999
Price Completion0.39999999999999997 → 0.5
Price Prompt0.09999999999999999 → 0.15
Price Completion0.5 → 0.39999999999999997
Price Prompt0.15 → 0.09999999999999999
Public API

Use this record

Fetch the complete source-linked model record. No key, no account, no rate-limited tier.

API documentation
Endpoint
GET https://modelbench.lol/api/v1/models/nvidia/nemotron-3.5-super-vl
curl
curl "https://modelbench.lol/api/v1/models/nvidia/nemotron-3.5-super-vl"
Common questions

Frequently asked questions

Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.

What is NVIDIA: Nemotron 3.5 Super VL?

NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video. It is published by NVIDIA and catalogued here from OpenRouter.

What is the context length of NVIDIA: Nemotron 3.5 Super VL?

NVIDIA: Nemotron 3.5 Super VL accepts up to 262.144K tokens of context and returns up to 235.929K output tokens.

Does NVIDIA: Nemotron 3.5 Super VL support tool calling and structured output?

Provider catalogs list support for image input.

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