Model Comparison
DeepSeek-V3.2-Exp vs Gemini 1.5 FlashWhich is better in 2026?
DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. Gemini 1.5 Flash is 1.2x cheaper per token.
Verdict: DeepSeek-V3.2-Exp vs Gemini 1.5 Flash — which is better?
DeepSeek-V3.2-Exp (by DeepSeek) and Gemini 1.5 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.
DeepSeek-V3.2-Exp outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemini 1.5 Flash is better at 0 benchmarks. DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.
On price, Gemini 1.5 Flash is roughly 1.2x 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.
Choose DeepSeek-V3.2-Exp if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Choose Gemini 1.5 Flash if…
- cost matters — it's about 1.2x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2-Exp outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemini 1.5 Flash is better at 0 benchmarks.
DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 1.8x more expensive than Gemini 1.5 Flash ($0.15/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 1.5x cheaper than Gemini 1.5 Flash ($0.60/1M tokens).
In conclusion, DeepSeek-V3.2-Exp 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 DeepSeek-V3.2-Exp's 163,840 tokens. DeepSeek-V3.2-Exp can generate longer responses up to 65,536 tokens, while Gemini 1.5 Flash is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Gemini 1.5 Flash supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
Gemini 1.5 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
Gemini 1.5 Flash
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while Gemini 1.5 Flash uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while Gemini 1.5 Flash was released on 2024-05-01.
DeepSeek-V3.2-Exp is 17 months newer than Gemini 1.5 Flash.
Sep 29, 2025
9 months ago
1.4yr newerMay 1, 2024
2.2 years ago
Knowledge Cutoff
When training data ends
Gemini 1.5 Flash has a documented knowledge cutoff of 2023-11-01, while DeepSeek-V3.2-Exp's cutoff date is not specified.
We can confirm Gemini 1.5 Flash's training data extends to 2023-11-01, but cannot make a direct comparison without DeepSeek-V3.2-Exp's cutoff date.
—
Nov 2023
Provider Availability
DeepSeek-V3.2-Exp is available from Novita. Gemini 1.5 Flash is available from Google.
DeepSeek-V3.2-Exp
Gemini 1.5 Flash
Outputs Comparison
Key Takeaways
DeepSeek-V3.2-Exp
View detailsDeepSeek
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and Gemini 1.5 Flash side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V3.2-Exp vs Gemini 1.5 Flash.