Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Llama 4 Scout vs NVIDIA: Nemotron 3.5 Content Safety (free) benchmark

Name: Llama 4 Scout vs NVIDIA: Nemotron 3.5 Content Safety (free) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Llama 4 Scout (Meta) and NVIDIA: Nemotron 3.5 Content Safety (free) (nvidia) using the latest snapshots we have as of Aug 17, 2026. NVIDIA: Nemotron 3.5 Content Safety (free) wins on output price at $0/1M. Llama 4 Scout has the larger context window (1.3M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Llama 4 Scout (8)vsNVIDIA: Nemotron 3.5 Content Safety (free) (2)

Llama 4 Scout: 8W (80%)Overall: Llama 4 ScoutNVIDIA: Nemotron 3.5 Content Safety (free): 2W (20%)

← Llama 4 ScoutNVIDIA: Nemotron 3.5 Content Safety (free) →

Llama 4 Scout (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,412vs—

Coding Elo

1,398vs—

SWE-bench

52.4%vs—

LiveBench

59.6%vs—

GPQA Diamond

71.2%vs—

Llama 4 Scout: 5WNVIDIA: Nemotron 3.5 Content Safety (free): 0W

Llama 4 Scout (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

155 tok/svs—

Time to first token

130 msvs—

Llama 4 Scout: 2WNVIDIA: Nemotron 3.5 Content Safety (free): 0W

NVIDIA: Nemotron 3.5 Content Safety (free) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.3/1Mvs$0/1M

Input price

$0.1/1Mvs$0/1M

Context window

1.3Mvs128k

Llama 4 Scout: 1WNVIDIA: Nemotron 3.5 Content Safety (free): 2W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageLlama 4 Scout 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

NVIDIA: Nemotron 3.5 Content Safety (free)

$0.30/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,412

EloHigh is better

—

Code Elo

High is better

1,398

Code EloHigh is better

—

LiveBench

High is better

59.6%

LiveBenchHigh is better

—

SWE-bench

High is better

52.4%

SWE-benchHigh is better

—

GPQA

High is better

71.2%

GPQAHigh is better

—

TTFT

Low is better

130 ms

TTFTLow is better

—

Speed

High is better

155 tok/s

SpeedHigh is better

—

In $

Low is better

$0.1/1M

In $Low is better

$0/1M

Out $

Low is better

$0.3/1M

Out $Low is better

$0/1M

Context

High is better

+924%1.3M

ContextHigh is better

128k

Key Selection Recommendations

1
NVIDIA: Nemotron 3.5 Content Safety (free):Pick NVIDIA: Nemotron 3.5 Content Safety (free) when you are optimizing output cost.
2
Llama 4 Scout:Pick Llama 4 Scout for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatNVIDIA: Nemotron 3.5 Content Safety (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGLlama 4 Scout

Larger window (1.3M).

Screenshots / visionLlama 4 Scout

Llama 4 Scout is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	NVIDIA: Nemotron 3.5 Content Safety (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Llama 4 Scout	Larger window (1.3M).
Screenshots / vision	Llama 4 Scout	Llama 4 Scout is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

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Haiku 4.5 vs Llama 4 Scout: cheap Claude versus cheap open Llama

$1/$5 hosted Claude vs a cheap long-context open sibling. The alternative-to-Sonnet pair that is honest.

launchApr 8, 2026

Llama 4 Scout: long-context open sibling of Maverick

Huge window, cheap hosted lists. The Haiku alternative that is actually open-weight.

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LIVE

Llama 4 Scout

Elo 1,412

LiveBench59.6%

SWE-bench52.4%

Speed155 tok/s

Output cost$0.3/1M

nvidia

NVIDIA: Nemotron 3.5 Content Safety (free)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0/1M

Frequently Asked Questions

Which is better overall, Llama 4 Scout or NVIDIA: Nemotron 3.5 Content Safety (free)?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Llama 4 Scout or NVIDIA: Nemotron 3.5 Content Safety (free)?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: NVIDIA: Nemotron 3.5 Content Safety (free) output tokens are $0/1M versus $0.3/1M. Input prices and retry rates still move the real bill.
Which is faster, Llama 4 Scout or NVIDIA: Nemotron 3.5 Content Safety (free)?: We do not have TTFT for both models.
Which has the larger context window?: Llama 4 Scout accepts 1.3M tokens versus 128k.
Can I self-host either model?: Llama 4 Scout is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Llama 4 Scout and NVIDIA: Nemotron 3.5 Content Safety (free) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Llama 4 Scout matchups →|All NVIDIA: Nemotron 3.5 Content Safety (free) matchups →

Llama 4 Scout vs Llama 4 Maverick (previous llama)Llama 3.1 405B vs Llama 4 Scout Mistral Large 3 vs Llama 4 Scout Llama 3.3 70B vs Llama 4 Scout Doubao Pro 1.5 vs Llama 4 Scout Yi-Lightning vs Llama 4 Scout

Llama 4 Scout vs NVIDIA: Nemotron 3.5 Content Safety (free) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Llama 4 Scout (8)vsNVIDIA: Nemotron 3.5 Content Safety (free) (2)

Llama 4 Scout: 8W (80%)Overall: Llama 4 ScoutNVIDIA: Nemotron 3.5 Content Safety (free): 2W (20%)

← Llama 4 ScoutNVIDIA: Nemotron 3.5 Content Safety (free) →

Llama 4 Scout (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,412vs—

Coding Elo

1,398vs—

SWE-bench

52.4%vs—

LiveBench

59.6%vs—

GPQA Diamond

71.2%vs—

Llama 4 Scout: 5WNVIDIA: Nemotron 3.5 Content Safety (free): 0W

Llama 4 Scout (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

155 tok/svs—

Time to first token

130 msvs—

Llama 4 Scout: 2WNVIDIA: Nemotron 3.5 Content Safety (free): 0W

NVIDIA: Nemotron 3.5 Content Safety (free) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.3/1Mvs$0/1M

Input price

$0.1/1Mvs$0/1M

Context window

1.3Mvs128k

Llama 4 Scout: 1WNVIDIA: Nemotron 3.5 Content Safety (free): 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatNVIDIA: Nemotron 3.5 Content Safety (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGLlama 4 Scout

Larger window (1.3M).

Screenshots / visionLlama 4 Scout

Llama 4 Scout is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	NVIDIA: Nemotron 3.5 Content Safety (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Llama 4 Scout	Larger window (1.3M).
Screenshots / vision	Llama 4 Scout	Llama 4 Scout is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Llama 4 Scout or NVIDIA: Nemotron 3.5 Content Safety (free)?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Llama 4 Scout or NVIDIA: Nemotron 3.5 Content Safety (free)?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

NVIDIA: Nemotron 3.5 Content Safety (free) output tokens are $0/1M versus $0.3/1M. Input prices and retry rates still move the real bill.

Which is faster, Llama 4 Scout or NVIDIA: Nemotron 3.5 Content Safety (free)?

We do not have TTFT for both models.

Which has the larger context window?

Llama 4 Scout accepts 1.3M tokens versus 128k.

Can I self-host either model?

Llama 4 Scout is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Llama 4 Scout and NVIDIA: Nemotron 3.5 Content Safety (free) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

NVIDIA: Nemotron 3.5 Content Safety (free)

Full Benchmark Score Matrix

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Haiku 4.5 vs Llama 4 Scout: cheap Claude versus cheap open Llama

Llama 4 Scout: long-context open sibling of Maverick

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Llama 4 Scout

NVIDIA: Nemotron 3.5 Content Safety (free)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

NVIDIA: Nemotron 3.5 Content Safety (free)

Full Benchmark Score Matrix

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Haiku 4.5 vs Llama 4 Scout: cheap Claude versus cheap open Llama

Llama 4 Scout: long-context open sibling of Maverick

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Llama 4 Scout

NVIDIA: Nemotron 3.5 Content Safety (free)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons