Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 2.0 Flash-Lite

Google

Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

OpenAI

GPT-5 nano

OpenAI

GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.

Google

Gemini 2.0 Flash-Lite

Google

2025-02-05

OpenAI

GPT-5 nano

OpenAI

2025-08-07

6 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.0 Flash-Lite

$0.08 cheaper
Input:$0.07
Output:$0.30
OpenAI

GPT-5 nano

Input:$0.05
Output:$0.40

Performance Metrics

Context window and performance specifications

Google

Gemini 2.0 Flash-Lite

Larger context
Max Context:1.1M
OpenAI

GPT-5 nano

Max Context:528.0K

Average performance across 1 common benchmarks

Google

Gemini 2.0 Flash-Lite

Average Score:51.5%
OpenAI

GPT-5 nano

+19.7%
Average Score:71.2%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash-Lite

math
+61.4%
71.0%
general
55.5%
OpenAI

GPT-5 nano

math
9.6%
general
+4.7%
60.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-5 nano

2024-05-30

Gemini 2.0 Flash-Lite

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.0 Flash-Lite

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
OpenAI

GPT-5 nano

2 providers

ZeroEval

Throughput: 500 tok/s
Latency: 0.3ms

OpenAI

Throughput: 500 tok/s
Latency: 0.3ms
Google

Gemini 2.0 Flash-Lite

Avg Score:51.5%
Providers:1
OpenAI

GPT-5 nano

+19.7%
Avg Score:71.2%
Providers:2