Model vs model
Llama 4 Scout vs NVIDIA Nemotron 3.5 Super VL
NVIDIA Nemotron 3.5 Super VL costs $0.28 per 1M tokens blended, against $0.29 for Llama 4 Scout, so price barely separates them. The score gap does justify the choice: an Intelligence Index of 26.5 against 6.5, and higher results on three of four shared benchmarks. Its 1.05M context window is also far larger than Llama 4 Scout's 128K.
At a glance
Longer bar means the bigger number.
Blended price · per 1M tokens, lower is better
Intelligence Index · Artificial Analysis, higher is better
Context window · tokens it can read at once
Where they sit among all 44 models
Llama 4 Scout ranks 43rd of the 43 models with an Intelligence Index, NVIDIA Nemotron 3.5 Super VL 25th. Up and to the left is smarter for less money. Hover or tap a dot for its numbers, then click it to compare that model with Llama 4 Scout.
Which one to pick
Pick NVIDIA Nemotron 3.5 Super VL if
- you want the lower bill ($0.28 vs $0.29 per 1M tokens blended)
- you want the higher overall score (26.5 vs 6.5)
- you care about AA-LCR (long documents): 69 vs 27.7
- you care about Humanity's Last Exam (hard reasoning): 30.7 vs 3.8
How smart is each one?
Of the 10 scores both models have, NVIDIA Nemotron 3.5 Super VL is ahead on 9, and one is within a point.
Every intelligence score we have
Out of 100, higher is better. Llama 4 Scout NVIDIA Nemotron 3.5 Super VL
Overall
Intelligence Index
6.526.5
By area
Coding
8.2NVIDIA Nemotron 3.5 Super VL: not scored yet
Math
14NVIDIA Nemotron 3.5 Super VL: not scored yet
Agentic work
0.5NVIDIA Nemotron 3.5 Super VL: not scored yet
By field of work
Finance & accounting
6.627.2Legal
8.128.1Healthcare & medicine
25.5Llama 4 Scout: not scored yet
Economics
10.538.5Engineering
9.530.1Strategy & operations
4.922.6
Benchmarks
Hard reasoning · Humanity's Last Exam
3.830.7Science · GPQA Diamond
58.7NVIDIA Nemotron 3.5 Super VL: not scored yet
Knowledge · MMLU-Pro
75.2NVIDIA Nemotron 3.5 Super VL: not scored yet
Competitive coding · LiveCodeBench
29.9NVIDIA Nemotron 3.5 Super VL: not scored yet
Scientific coding · SciCode
21.347.8Terminal tasks · Terminal-Bench 4.0
0 eachTool use · τ-Bench Banking
3.3NVIDIA Nemotron 3.5 Super VL: not scored yet
Instruction following · IFBench
39.5NVIDIA Nemotron 3.5 Super VL: not scored yet
Long documents · AA-LCR
27.769Competition math · AIME 2025
14NVIDIA Nemotron 3.5 Super VL: not scored yet
Competition math · AIME 2024
28.3NVIDIA Nemotron 3.5 Super VL: not scored yet
Math · MATH-500
84.4NVIDIA Nemotron 3.5 Super VL: not scored yet
The specs
| Spec | Llama 4 Scout | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Input price | $0.17 per 1M | $0.20 per 1M |
| Output price | $0.66 per 1M | $0.50 per 1M |
| Cost per test task | Not tested | Not tested |
| Context window | 128K | 1.05M |
| Max output | 8K | 1.05M |
| Accepts | Text, Image | Text, Image |
| Open weights | Yes | Yes |
| Lab | Meta | NVIDIA |
| Released | Apr 2025 | Oct 2026 |
| Knowledge cutoff | Aug 2024 | Not published |
Blended price weighs 3 parts input to 1 part output. List prices from models.dev.
Questions
Is Llama 4 Scout or NVIDIA Nemotron 3.5 Super VL cheaper?
NVIDIA Nemotron 3.5 Super VL is cheaper. It charges $0.20 per 1M input tokens and $0.50 per 1M output tokens, against $0.17 and $0.66 for Llama 4 Scout. Blended 3 parts input to 1 part output, that is $0.28 against $0.29 per 1M tokens.
Which is smarter, Llama 4 Scout or NVIDIA Nemotron 3.5 Super VL?
NVIDIA Nemotron 3.5 Super VL scores higher on the Artificial Analysis Intelligence Index, 26.5 against 6.5 for Llama 4 Scout. The biggest differences are on AA-LCR (27.7 vs 69) and Humanity's Last Exam (3.8 vs 30.7).
Which has the longer context window?
NVIDIA Nemotron 3.5 Super VL accepts 1.05M tokens, against 128K for Llama 4 Scout.
Can I compare Llama 4 Scout and NVIDIA Nemotron 3.5 Super VL on my own prompt?
Yes. ModelCompare sends one prompt to both models at once and shows each answer side by side with what it cost. You can try it free without an account.
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Where the numbers come from
Intelligence Index and benchmark scores are from Artificial Analysis, at each model’s highest effort, except SimpleQA, which is from Epoch AI, and the Uncensored score, which is from the UGI Leaderboard. The hallucination test is ours: questions with one exact answer, fake evidence pushed against right answers and requests that tempt a model to name packages that don’t exist. Prices are list prices from models.dev. Example answers come from our own test runs. Updated October 25, 2026.