Price Per TokenPrice Per Token
Google
Google
vs
Nvidia
Nvidia

Google vs Nvidia

Compare all Google and Nvidia models — pricing, benchmarks, and capabilities

108 out of our 483 tracked models have had a price change in March.

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Overview

Google

Models
34
Cheapest Input
$0.02
Max Context
1.0M
Top Intelligence
48.4

Nvidia

Models
7
Cheapest Input
$0.04
Max Context
262K
Top Intelligence
14.6

Flagship Model Comparison

Gemini 3 Pro PreviewvsLlama 3.3 Nemotron Super 49B V1.5
MetricGemini 3 Pro PreviewLlama 3.3 Nemotron Super 49B V1.5
Input $/1M tokens$2.00$0.10
Output $/1M tokens$12.00$0.40
Context Window1.0M131K
Intelligence48.414.6
Coding46.510.5
Math95.78.0
Full comparison →

All Models Pricing

Google Models

ModelInput/1MOutput/1MContext
Gemini 3 Pro Preview $2.00 $12.001.0M
Gemma 2 27B $0.65 $0.658K
Gemini 3 Flash Preview $0.50 $3.001.0M
Gemini 2.5 Pro $1.00 $10.001.0M
Gemma 2 9B $0.03 $0.088K
Gemini 2.5 Pro Preview 06-05 $1.25 $10.001.0M
Gemini 2.5 Pro Preview 05-06 $1.25 $10.001.0M
Gemini 2.5 Flash Preview 09-2025 $0.30 $2.501.0M
Gemini 2.5 Flash $0.30 $2.501.0M
Gemini 2.5 Flash Lite Preview 09-2025 $0.10 $0.401.0M
Gemini 2.0 Flash $0.10 $0.401.0M
Gemini 2.0 Flash Experimental $0.10 $0.401.0M
Gemini 2.0 Flash Lite $0.07 $0.301.0M
Gemini 1.5 Flash $0.35 $1.051.0M
Gemini 2.5 Flash Lite $0.10 $0.401.0M
Gemma 3 27B $0.03 $0.11128K
Gemma 3 12B $0.04 $0.13131K
Gemini 1.0 Pro $0.13 $0.3833K
Gemma 3n 4B $0.02 $0.0433K
Gemma 3 4B $0.04 $0.08131K
Gemma 7B Instruct $0.07 $0.078K
CodeGemma 2B $0.10 $0.108K
Gemma 2B $0.10 $0.108K
Gemma 2B $0.10 $0.108K
Gemma 3 1B $0.10 $0.10128K
CodeGemma 7B $0.20 $0.20128K
Gemma 7B $0.20 $0.208K
Gemini 3.1 Flash Lite Preview $0.25 $1.501.0M
Gemini 2.5 Flash Image (Nano Banana) $0.30 $2.5033K
Gemini 2.5 Flash Image Preview (Nano Banana) $0.30 $2.501.0M
MedGemma 27B $0.90 $0.908K
Gemini 3.1 Pro Preview $2.00 $12.001.0M
Nano Banana Pro (Gemini 3 Pro Image Preview) $2.00 $12.0066K
Gemini 3.1 Pro Preview Custom Tools $2.00 $12.001.0M

Nvidia Models

ModelInput/1MOutput/1MContext
Llama 3.3 Nemotron Super 49B V1.5 $0.10 $0.40131K
Llama 3.1 Nemotron 70B Instruct $0.90 $0.90131K
Nemotron Nano 9B V2 $0.04 $0.16131K
Nemotron 3 Nano 30B A3B $0.05 $0.20262K
Nemotron Nano 12B 2 VL $0.20 $0.20131K
Nemotron Nano 12B V2 $0.20 $0.20128K
Llama 3.1 Nemotron Ultra 253B v1 $0.00 $0.00128K

Benchmark Comparison

Best Scores by Provider

BenchmarkGoogleNvidia
Intelligence
48.4
Gemini 3 Pro Preview
14.6
Llama 3.3 Nemotron Super 49B V1.5
Coding
46.7
Gemini 2.5 Pro Preview 06-05
15.8
Nemotron 3 Nano 30B A3B
Math
95.7
Gemini 3 Pro Preview
62.3
Nemotron Nano 9B V2
MMLU Pro
89.8
Gemini 3 Pro Preview
73.9
Nemotron Nano 9B V2
GPQA
90.8
Gemini 3 Pro Preview
55.7
Nemotron Nano 9B V2
LiveCodeBench
91.7
Gemini 3 Pro Preview
70.1
Nemotron Nano 9B V2
Aider
83.1
Gemini 2.5 Pro Preview 06-05
54.9
Llama 3.1 Nemotron 70B Instruct
AIME
88.7
Gemini 2.5 Pro
24.7
Llama 3.1 Nemotron 70B Instruct
BBH
49.3
Gemma 2 27B
N/A

Capabilities

CapabilityGoogleNvidia
Vision✓ (25 models)✓
Tool Calls✓ (26 models)✓ (7 models)
Reasoning✓ (10 models)✓ (5 models)
Audio Input✓ (13 models)—
Audio Output——
PDF Input✓ (13 models)—
Web Search——
Prompt Caching✓ (15 models)—
Open Source Models✓ (14 models)✓ (5 models)

Model-Level Comparisons

Compare specific models head-to-head:

Gemini 3 Pro PreviewvsLlama 3.3 Nemotron Super 49B V1.5
Gemini 3 Pro PreviewvsLlama 3.1 Nemotron 70B Instruct
Gemini 3 Pro PreviewvsNemotron Nano 9B V2
Gemma 2 27BvsLlama 3.3 Nemotron Super 49B V1.5
Gemma 2 27BvsLlama 3.1 Nemotron 70B Instruct
Gemma 2 27BvsNemotron Nano 9B V2
Gemini 3 Flash PreviewvsLlama 3.3 Nemotron Super 49B V1.5
Gemini 3 Flash PreviewvsLlama 3.1 Nemotron 70B Instruct
Gemini 3 Flash PreviewvsNemotron Nano 9B V2

Frequently Asked Questions

Google has 34 models while Nvidia has 7 models available through API providers.
Google's cheapest model starts at $0.02/M input tokens, while Nvidia's cheapest starts at $0.04/M input tokens.
It depends on your needs. Compare specific models from each provider using the head-to-head comparisons above. Consider factors like pricing, benchmark performance, context window size, and supported capabilities.

Built by @aellman

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