Gemini 2.0 Flash-Lite vs o1-mini
Gemini 2.0 Flash-Lite and o1-mini are closely matched at 12.4 and 10.0 on the LLM Stats Score. Gemini 2.0 Flash-Lite is 41.2x cheaper per token.
Google · OpenAI · Updated for 2026
Which is better?
Gemini 2.0 Flash-Lite and o1-mini are closely matched on the overall LLM Stats Score at 12.4 and 10.0.
In the 1 individual benchmarks reported for both models, o1-mini wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Gemini 2.0 Flash-Lite is roughly 41.2x 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 41.2x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Feb 2025
Choose o1-mini
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
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 · 6 for o1-mini
Gemini 2.0 Flash-Lite outperforms in 0 benchmarks, while o1-mini is better at 1 benchmark (GPQA).
o1-mini 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 42.9x cheaper than o1-mini ($3.00/1M tokens).
For output processing, Gemini 2.0 Flash-Lite ($0.30/1M tokens) is 40.0x cheaper than o1-mini ($12.00/1M tokens).
In conclusion, o1-mini 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 o1-mini's 128,000 tokens. o1-mini can generate longer responses up to 65,536 tokens, while Gemini 2.0 Flash-Lite is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 2.0 Flash-Lite supports multimodal inputs, whereas o1-mini does not.
Gemini 2.0 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 2.0 Flash-Lite
o1-mini
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 o1-mini was released on 2024-09-12.
Gemini 2.0 Flash-Lite is 5 months newer than o1-mini.
Feb 5, 2025
1.6 years ago
4mo newerSep 12, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Gemini 2.0 Flash-Lite has a documented knowledge cutoff of 2024-06-01, while o1-mini's cutoff date is not specified.
We can confirm Gemini 2.0 Flash-Lite's training data extends to 2024-06-01, but cannot make a direct comparison without o1-mini's cutoff date.
Jun 2024
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Provider Availability
Gemini 2.0 Flash-Lite is available from Google. o1-mini is available from OpenAI, Azure.
Gemini 2.0 Flash-Lite
o1-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 2.0 Flash-Lite and o1-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 2.0 Flash-Lite vs o1-mini.