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

GPT-4 Turbo vs NVIDIA: Nemotron 3 Nano 30B A3B (free) benchmark

Name: GPT-4 Turbo vs NVIDIA: Nemotron 3 Nano 30B A3B (free) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-4 Turbo (OpenAI) and NVIDIA: Nemotron 3 Nano 30B A3B (free) (nvidia) using the latest snapshots we have as of Aug 17, 2026. NVIDIA: Nemotron 3 Nano 30B A3B (free) wins on output price at $0/1M. NVIDIA: Nemotron 3 Nano 30B A3B (free) has the larger context window (256k 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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OpenAI

GPT-4 Turbo

GPT-4 Turbo 128k. Historical flagship for gpt-4 turbo vs gpt-4o / gpt-5.

Elo 1,255$30/1M out

nvidia

NVIDIA: Nemotron 3 Nano 30B A3B (free)

Auto-discovered from OpenRouter (nvidia/nemotron-3-nano-30b-a3b:free). Preview until a second source matches.

$0/1M out

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Model A

Model B

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4 Turbo (6)vsNVIDIA: Nemotron 3 Nano 30B A3B (free) (3)

GPT-4 Turbo: 6W (67%)Overall: GPT-4 TurboNVIDIA: Nemotron 3 Nano 30B A3B (free): 3W (33%)

← GPT-4 TurboNVIDIA: Nemotron 3 Nano 30B A3B (free) →

GPT-4 Turbo (4/5)

Intelligence & Reasoning

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

Preference Elo

1,255vs—

Coding Elo

—vs—

SWE-bench

33.2%vs—

LiveBench

47%vs—

GPQA Diamond

48%vs—

GPT-4 Turbo: 4WNVIDIA: Nemotron 3 Nano 30B A3B (free): 0W

GPT-4 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

55 tok/svs—

Time to first token

350 msvs—

GPT-4 Turbo: 2WNVIDIA: Nemotron 3 Nano 30B A3B (free): 0W

NVIDIA: Nemotron 3 Nano 30B A3B (free) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$30/1Mvs$0/1M

Input price

$10/1Mvs$0/1M

Context window

128kvs256k

GPT-4 Turbo: 0WNVIDIA: Nemotron 3 Nano 30B A3B (free): 3W

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 AdvantageGPT-4 Turbo 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

NVIDIA: Nemotron 3 Nano 30B A3B (free)

$30.00/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,255

EloHigh is better

—

LiveBench

High is better

47%

LiveBenchHigh is better

—

SWE-bench

High is better

33.2%

SWE-benchHigh is better

—

GPQA

High is better

48%

GPQAHigh is better

—

TTFT

Low is better

350 ms

TTFTLow is better

—

Speed

High is better

55 tok/s

SpeedHigh is better

—

In $

Low is better

$10/1M

In $Low is better

$0/1M

Out $

Low is better

$30/1M

Out $Low is better

$0/1M

Context

High is better

128k

ContextHigh is better

256k+100%

Key Selection Recommendations

1
NVIDIA: Nemotron 3 Nano 30B A3B (free):Pick NVIDIA: Nemotron 3 Nano 30B A3B (free) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatNVIDIA: Nemotron 3 Nano 30B A3B (free)

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGNVIDIA: Nemotron 3 Nano 30B A3B (free)

Larger window (256k).

Screenshots / visionGPT-4 Turbo

GPT-4 Turbo 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 Nano 30B A3B (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	NVIDIA: Nemotron 3 Nano 30B A3B (free)	Larger window (256k).
Screenshots / vision	GPT-4 Turbo	GPT-4 Turbo is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

OpenAI

GPT-4 Turbo

Elo 1,255

LiveBench47%

SWE-bench33.2%

Speed55 tok/s

Output cost$30/1M

nvidia

NVIDIA: Nemotron 3 Nano 30B A3B (free)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0/1M

Frequently Asked Questions

Which is better overall, GPT-4 Turbo or NVIDIA: Nemotron 3 Nano 30B A3B (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, GPT-4 Turbo or NVIDIA: Nemotron 3 Nano 30B A3B (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 Nano 30B A3B (free) output tokens are $0/1M versus $30/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-4 Turbo or NVIDIA: Nemotron 3 Nano 30B A3B (free)?: We do not have TTFT for both models.
Which has the larger context window?: NVIDIA: Nemotron 3 Nano 30B A3B (free) accepts 256k tokens versus 128k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
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. GPT-4 Turbo and NVIDIA: Nemotron 3 Nano 30B A3B (free) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All GPT-4 Turbo matchups →|All NVIDIA: Nemotron 3 Nano 30B A3B (free) matchups →

GPT-4 Turbo vs GPT-4o (next gpt-flagship)GPT-5 vs GPT-4 Turbo GPT-4.5 Orion vs GPT-4 Turbo GPT-5.6 Sol vs GPT-4 Turbo GPT-5.6 Terra vs GPT-4 Turbo GPT-4o mini vs GPT-4 Turbo

GPT-4 Turbo vs NVIDIA: Nemotron 3 Nano 30B A3B (free) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4 Turbo (6)vsNVIDIA: Nemotron 3 Nano 30B A3B (free) (3)

GPT-4 Turbo: 6W (67%)Overall: GPT-4 TurboNVIDIA: Nemotron 3 Nano 30B A3B (free): 3W (33%)

← GPT-4 TurboNVIDIA: Nemotron 3 Nano 30B A3B (free) →

GPT-4 Turbo (4/5)

Intelligence & Reasoning

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

Preference Elo

1,255vs—

Coding Elo

—vs—

SWE-bench

33.2%vs—

LiveBench

47%vs—

GPQA Diamond

48%vs—

GPT-4 Turbo: 4WNVIDIA: Nemotron 3 Nano 30B A3B (free): 0W

GPT-4 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

55 tok/svs—

Time to first token

350 msvs—

GPT-4 Turbo: 2WNVIDIA: Nemotron 3 Nano 30B A3B (free): 0W

NVIDIA: Nemotron 3 Nano 30B A3B (free) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$30/1Mvs$0/1M

Input price

$10/1Mvs$0/1M

Context window

128kvs256k

GPT-4 Turbo: 0WNVIDIA: Nemotron 3 Nano 30B A3B (free): 3W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatNVIDIA: Nemotron 3 Nano 30B A3B (free)

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGNVIDIA: Nemotron 3 Nano 30B A3B (free)

Larger window (256k).

Screenshots / visionGPT-4 Turbo

GPT-4 Turbo 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 Nano 30B A3B (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	NVIDIA: Nemotron 3 Nano 30B A3B (free)	Larger window (256k).
Screenshots / vision	GPT-4 Turbo	GPT-4 Turbo is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, GPT-4 Turbo or NVIDIA: Nemotron 3 Nano 30B A3B (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, GPT-4 Turbo or NVIDIA: Nemotron 3 Nano 30B A3B (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 Nano 30B A3B (free) output tokens are $0/1M versus $30/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-4 Turbo or NVIDIA: Nemotron 3 Nano 30B A3B (free)?

We do not have TTFT for both models.

Which has the larger context window?

NVIDIA: Nemotron 3 Nano 30B A3B (free) accepts 256k tokens versus 128k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

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. GPT-4 Turbo and NVIDIA: Nemotron 3 Nano 30B A3B (free) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.