Gemini 2.0 Flash-Lite vs GPT-5 nano
GPT-5 nano leads the LLM Stats Score 19.5 to 12.4. Gemini 2.0 Flash-Lite is 1.1x cheaper per token.
Google · OpenAI · Updated for 2026
Which is better?
GPT-5 nano leads the overall LLM Stats Score 19.5 to 12.4, ranking #203 overall.
In the 1 individual benchmarks reported for both models, GPT-5 nano wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Gemini 2.0 Flash-Lite is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 2.0 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 2.0 Flash-Lite
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
Choose GPT-5 nano
- overall performance matters — it scores 19.5 and ranks #203 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Aug 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Gemini 2.0 Flash-Lite · 5 for GPT-5 nano
Gemini 2.0 Flash-Lite outperforms in 0 benchmarks, while GPT-5 nano is better at 1 benchmark (GPQA).
GPT-5 nano significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 2.0 Flash-Lite ($0.07/1M tokens) is 1.4x more expensive than GPT-5 nano ($0.05/1M tokens).
For output processing, Gemini 2.0 Flash-Lite ($0.30/1M tokens) is 1.3x cheaper than GPT-5 nano ($0.40/1M tokens).
In conclusion, GPT-5 nano is more expensive than Gemini 2.0 Flash-Lite.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 2.0 Flash-Lite accepts 1,048,576 input tokens compared to GPT-5 nano's 400,000 tokens. GPT-5 nano can generate longer responses up to 128,000 tokens, while Gemini 2.0 Flash-Lite is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 2.0 Flash-Lite and GPT-5 nano support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 2.0 Flash-Lite
GPT-5 nano
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Gemini 2.0 Flash-Lite was released on 2025-02-05, while GPT-5 nano was released on 2025-08-07.
GPT-5 nano is 6 months newer than Gemini 2.0 Flash-Lite.
Feb 5, 2025
1.6 years ago
Aug 7, 2025
1.1 years ago
6mo newerKnowledge Cutoff
When training data ends
Gemini 2.0 Flash-Lite has a knowledge cutoff of 2024-06-01, while GPT-5 nano has a cutoff of 2024-05-30.
Gemini 2.0 Flash-Lite has more recent training data (up to 2024-06-01), making it potentially better informed about events through that date compared to GPT-5 nano (2024-05-30).
Jun 2024
1 mo newerMay 2024
Provider Availability
Gemini 2.0 Flash-Lite is available from Google. GPT-5 nano is available from OpenAI.
Gemini 2.0 Flash-Lite
GPT-5 nano
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 2.0 Flash-Lite and GPT-5 nano side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 2.0 Flash-Lite vs GPT-5 nano.