Model Comparison
DeepSeek-V3 0324 vs Gemini 1.5 FlashWhich is better in 2026?
DeepSeek-V3 0324 significantly outperforms across most benchmarks. Gemini 1.5 Flash is 1.9x cheaper per token.
Verdict: DeepSeek-V3 0324 vs Gemini 1.5 Flash — which is better?
DeepSeek-V3 0324 (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 0324 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemini 1.5 Flash is better at 0 benchmarks. DeepSeek-V3 0324 significantly outperforms across most benchmarks.
On price, Gemini 1.5 Flash is roughly 1.9x 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.
Choose DeepSeek-V3 0324 if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you want the most recent training data — it shipped Mar 2025
- you need open weights you can self-host or fine-tune
Choose Gemini 1.5 Flash if…
- cost matters — it's about 1.9x 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 0324 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemini 1.5 Flash is better at 0 benchmarks.
DeepSeek-V3 0324 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 0324 ($0.28/1M tokens) is 1.9x more expensive than Gemini 1.5 Flash ($0.15/1M tokens).
For output processing, DeepSeek-V3 0324 ($1.14/1M tokens) is 1.9x more expensive than Gemini 1.5 Flash ($0.60/1M tokens).
In conclusion, DeepSeek-V3 0324 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 0324's 163,840 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 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 0324 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 0324
Gemini 1.5 Flash
License
Usage and distribution terms
DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), 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 + Model License (Commercial use allowed)
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3 0324 was released on 2025-03-25, while Gemini 1.5 Flash was released on 2024-05-01.
DeepSeek-V3 0324 is 11 months newer than Gemini 1.5 Flash.
Mar 25, 2025
1.3 years ago
10mo 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 0324'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 0324's cutoff date.
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Nov 2023
Provider Availability
DeepSeek-V3 0324 is available from Novita. Gemini 1.5 Flash is available from Google.
DeepSeek-V3 0324
Gemini 1.5 Flash
Outputs Comparison
Key Takeaways
DeepSeek-V3 0324
View detailsDeepSeek
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 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 0324 vs Gemini 1.5 Flash.