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

o1-preview

OpenAI

o1-preview is a language model developed by OpenAI. It achieves strong performance with an average score of 64.8% across 8 benchmarks. It excels particularly in MGSM (90.8%), MMLU (90.8%), MATH (85.5%). The model shows particular specialization in math tasks with an average performance of 88.1%. It supports a 161K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents OpenAI's latest advancement in AI technology.

OpenAI

o1-preview

OpenAI

2024-09-12

Google

Gemini 2.0 Flash-Lite

Google

2025-02-05

4 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.0 Flash-Lite

$74.63 cheaper
Input:$0.07
Output:$0.30
OpenAI

o1-preview

Input:$15.00
Output:$60.00

Performance Metrics

Context window and performance specifications

Google

Gemini 2.0 Flash-Lite

Larger context
Max Context:1.1M
OpenAI

o1-preview

Max Context:160.8K

Average performance across 3 common benchmarks

Google

Gemini 2.0 Flash-Lite

Average Score:53.3%
OpenAI

o1-preview

+13.7%
Average Score:67.1%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash-Lite

math
71.0%
general
55.5%
OpenAI

o1-preview

math
+17.1%
88.1%
general
+2.5%
58.0%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

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

o1-preview

2 providers

Azure

Throughput: 16 tok/s
Latency: 0.54ms

OpenAI

Throughput: 66 tok/s
Latency: 16.2ms
Google

Gemini 2.0 Flash-Lite

Avg Score:53.3%
Providers:1
OpenAI

o1-preview

+13.7%
Avg Score:67.1%
Providers:2