Gemini 1.5 Flash vs GPT-3.5 Turbo
Gemini 1.5 Flash leads the LLM Stats Score 6.2 to -9.2. Gemini 1.5 Flash is 2.9x cheaper per token.
Google · OpenAI · Updated for 2026
Which is better?
Gemini 1.5 Flash leads the overall LLM Stats Score 6.2 to -9.2, ranking #277 overall.
In the 7 individual benchmarks reported for both models, Gemini 1.5 Flash wins 7; this is a narrower head-to-head signal than the composite indexes.
On price, Gemini 1.5 Flash is roughly 2.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Flash 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 1.5 Flash
- overall performance matters — it scores 6.2 and ranks #277 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 7 of 7 exact shared results
- cost matters — it's about 2.9x 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 May 2024
Choose GPT-3.5 Turbo
- you want predictable pricing at $0.50/M input and $1.50/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for Gemini 1.5 Flash · 8 for GPT-3.5 Turbo
Gemini 1.5 Flash outperforms in 7 benchmarks (GPQA, HumanEval, MATH, MathVista, MGSM, MMLU, MMMU), while GPT-3.5 Turbo is better at 0 benchmarks.
Gemini 1.5 Flash 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 1.5 Flash ($0.15/1M tokens) is 3.3x cheaper than GPT-3.5 Turbo ($0.50/1M tokens).
For output processing, Gemini 1.5 Flash ($0.60/1M tokens) is 2.5x cheaper than GPT-3.5 Turbo ($1.50/1M tokens).
In conclusion, GPT-3.5 Turbo is more expensive than Gemini 1.5 Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.5 Flash accepts 1,048,576 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. Gemini 1.5 Flash can generate longer responses up to 8,192 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 1.5 Flash supports multimodal inputs, whereas GPT-3.5 Turbo does not.
Gemini 1.5 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 1.5 Flash
GPT-3.5 Turbo
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 1.5 Flash was released on 2024-05-01, while GPT-3.5 Turbo was released on 2023-03-21.
Gemini 1.5 Flash is 14 months newer than GPT-3.5 Turbo.
May 1, 2024
2.3 years ago
1.1yr newerMar 21, 2023
3.4 years ago
Knowledge Cutoff
When training data ends
Gemini 1.5 Flash has a knowledge cutoff of 2023-11-01, while GPT-3.5 Turbo has a cutoff of 2021-09-30.
Gemini 1.5 Flash has more recent training data (up to 2023-11-01), making it potentially better informed about events through that date compared to GPT-3.5 Turbo (2021-09-30).
Nov 2023
2.2 yr newerSep 2021
Provider Availability
Gemini 1.5 Flash is available from Google. GPT-3.5 Turbo is available from Azure, OpenAI.
Gemini 1.5 Flash
GPT-3.5 Turbo
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Flash and GPT-3.5 Turbo side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Flash vs GPT-3.5 Turbo.