Model Comparison
DeepSeek-V2.5 vs Gemini 1.0 ProWhich is better in 2026?
DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is 4.3x cheaper per token.
Verdict: DeepSeek-V2.5 vs Gemini 1.0 Pro — which is better?
DeepSeek-V2.5 (by DeepSeek) and Gemini 1.0 Pro (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-V2.5 outperforms in 2 benchmarks (MATH, MMLU), while Gemini 1.0 Pro is better at 0 benchmarks. DeepSeek-V2.5 significantly outperforms across most benchmarks.
On price, DeepSeek-V2.5 is roughly 4.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.0 Pro also accepts a larger context window (32,760 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V2.5 if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 4.3x cheaper per token
- you want the most recent training data — it shipped May 2024
- you need open weights you can self-host or fine-tune
Choose Gemini 1.0 Pro if…
- you process long inputs — it offers a 32,760 token context window
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 outperforms in 2 benchmarks (MATH, MMLU), while Gemini 1.0 Pro is better at 0 benchmarks.
DeepSeek-V2.5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 3.6x cheaper than Gemini 1.0 Pro ($0.50/1M tokens).
For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 5.4x cheaper than Gemini 1.0 Pro ($1.50/1M tokens).
In conclusion, Gemini 1.0 Pro is more expensive than DeepSeek-V2.5.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.0 Pro accepts 32,760 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Both models can generate responses up to 8,192 tokens.
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Gemini 1.0 Pro uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Gemini 1.0 Pro was released on 2024-02-15.
DeepSeek-V2.5 is 3 months newer than Gemini 1.0 Pro.
May 8, 2024
2.2 years ago
2mo newerFeb 15, 2024
2.4 years ago
Knowledge Cutoff
When training data ends
Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while DeepSeek-V2.5's cutoff date is not specified.
We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without DeepSeek-V2.5's cutoff date.
—
Feb 2024
Provider Availability
DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Gemini 1.0 Pro is available from Google.
DeepSeek-V2.5
Gemini 1.0 Pro
Outputs Comparison
Key Takeaways
DeepSeek-V2.5
View detailsDeepSeek
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V2.5 and Gemini 1.0 Pro side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about DeepSeek-V2.5 vs Gemini 1.0 Pro.