Model Comparison
GPT-3.5 Turbo vs Gemini 2.0 FlashWhich is better in 2026?
Gemini 2.0 Flash significantly outperforms across most benchmarks. Gemini 2.0 Flash is 4.3x cheaper per token.
Verdict: GPT-3.5 Turbo vs Gemini 2.0 Flash — which is better?
GPT-3.5 Turbo (by OpenAI) and Gemini 2.0 Flash (by Google) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GPT-3.5 Turbo outperforms in 0 benchmarks, while Gemini 2.0 Flash is better at 3 benchmarks (GPQA, MATH, MMMU). Gemini 2.0 Flash significantly outperforms across most benchmarks.
On price, Gemini 2.0 Flash is roughly 4.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 2.0 Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-3.5 Turbo if…
- you want predictable pricing at $0.50/M input and $1.50/M output
Choose Gemini 2.0 Flash if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- cost matters — it's about 4.3x 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 Dec 2024
Performance Benchmarks
Comparative analysis across standard metrics
GPT-3.5 Turbo outperforms in 0 benchmarks, while Gemini 2.0 Flash is better at 3 benchmarks (GPQA, MATH, MMMU).
Gemini 2.0 Flash significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-3.5 Turbo ($0.50/1M tokens) is 5.0x more expensive than Gemini 2.0 Flash ($0.10/1M tokens).
For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 3.8x more expensive than Gemini 2.0 Flash ($0.40/1M tokens).
In conclusion, GPT-3.5 Turbo is more expensive than Gemini 2.0 Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 2.0 Flash accepts 1,048,576 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. Gemini 2.0 Flash can generate longer responses up to 8,192 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
Input Capabilities
Supported data types and modalities
Gemini 2.0 Flash supports multimodal inputs, whereas GPT-3.5 Turbo does not.
Gemini 2.0 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-3.5 Turbo
Gemini 2.0 Flash
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
GPT-3.5 Turbo was released on 2023-03-21, while Gemini 2.0 Flash was released on 2024-12-01.
Gemini 2.0 Flash is 21 months newer than GPT-3.5 Turbo.
Mar 21, 2023
3.2 years ago
Dec 1, 2024
1.5 years ago
1.7yr newerKnowledge Cutoff
When training data ends
GPT-3.5 Turbo has a knowledge cutoff of 2021-09-30, while Gemini 2.0 Flash has a cutoff of 2024-08-01.
Gemini 2.0 Flash has more recent training data (up to 2024-08-01), making it potentially better informed about events through that date compared to GPT-3.5 Turbo (2021-09-30).
Sep 2021
Aug 2024
2.9 yr newerProvider Availability
GPT-3.5 Turbo is available from Azure, OpenAI. Gemini 2.0 Flash is available from Google.
GPT-3.5 Turbo
Gemini 2.0 Flash
Outputs Comparison
Key Takeaways
No standout differentiators in the data we have for this pair.
Detailed Comparison
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FAQ
Common questions about GPT-3.5 Turbo vs Gemini 2.0 Flash.