DeepSeek V3 vs Gemini 2.5 Pro
Pricing, benchmarks, and use case comparison
Quick take
- •DeepSeek V3 is meaningfully stronger at cost efficiency (92 vs 70 on our capability index).
- •Gemini 2.5 Pro is meaningfully stronger at multimodal (85 vs 10).
- •DeepSeek V3 is open-weights (free to self-host); Gemini 2.5 Pro is paid API only.
- •DeepSeek V3 has a 128K tokens context window vs 1,048,576 tokens (1M) input; up to 65K output - better for whole-repo or long-document work.
Specs comparison
| DeepSeek V3 | Gemini 2.5 Pro | |
|---|---|---|
| Provider | DeepSeek | Google DeepMind |
| Type | Open source | Closed source |
| Context window | ✓128K tokens | 1,048,576 tokens (1M) input; up to 65K output |
| Input / 1M tokens | ✓Free (self-host) | $1.25 |
| Output / 1M tokens | Free (self-host) | $10.00 |
| Release date | 2024-12 | 2025-06 |
Benchmarks
| Benchmark | DeepSeek V3 | Gemini 2.5 Pro |
|---|---|---|
| Pre-training scale | ~15T tokens | - |
| Context window | - | 1M tokens |
| Pricing tier break | - | 200K tokens |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose DeepSeek V3 if...
- →You want a proven, stable open model with broad ecosystem support
- →You need to self-host or fine-tune without licensing friction
- →Cost is critical and you don't need V4's 1M context or top scores
- →You want reproducible open-weight behavior pinned to a known version
Choose Gemini 2.5 Pro if...
- →Complex reasoning, analysis, or STEM tasks that benefit from a thinking model
- →Processing very long inputs (long documents, large repos)
- →Multimodal tasks needing high quality