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-4.1 nano

OpenAI

GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). 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 OpenAI's latest advancement in AI technology.

Google

Gemini 2.0 Flash-Lite

Google

2025-02-05

OpenAI

GPT-4.1 nano

OpenAI

2025-04-14

2 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.0 Flash-Lite

$0.13 cheaper
Input:$0.07
Output:$0.30
OpenAI

GPT-4.1 nano

Input:$0.10
Output:$0.40

Performance Metrics

Context window and performance specifications

Google

Gemini 2.0 Flash-Lite

Max Context:1.1M
OpenAI

GPT-4.1 nano

Larger context
Max Context:1.1M

Average performance across 2 common benchmarks

Google

Gemini 2.0 Flash-Lite

+6.9%
Average Score:59.8%
OpenAI

GPT-4.1 nano

Average Score:52.8%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash-Lite

code
28.9%
math
+14.8%
71.0%
vision
+12.6%
68.0%
general
+23.1%
55.5%
OpenAI

GPT-4.1 nano

code
+45.6%
74.5%
math
56.2%
vision
55.4%
general
32.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-4.1 nano

2024-05-31

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-4.1 nano

1 providers

OpenAI

Throughput: 200 tok/s
Latency: 2ms
Google

Gemini 2.0 Flash-Lite

+6.9%
Avg Score:59.8%
Providers:1
OpenAI

GPT-4.1 nano

Avg Score:52.8%
Providers:1