DeepSeek-V2.5 vs Gemini 1.0 Pro
DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is 4.3x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
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.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V2.5
- 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
- you process long inputs — it offers a 32,760 token context window
At a glance
The differences that matter most.
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
Playground indexes and blind preference scores
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
2.3 years ago
2mo newerFeb 15, 2024
2.5 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
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.
FAQ
Common questions about DeepSeek-V2.5 vs Gemini 1.0 Pro.