DeepSeek V3 vs Gemma 4 12B
Pricing, benchmarks, and use case comparison
Quick take
- •DeepSeek V3 is meaningfully stronger at math (78 vs 65 on our capability index).
- •Gemma 4 12B is meaningfully stronger at multimodal (78 vs 10).
- •Gemma 4 12B has a 256K tokens context window vs 128K tokens - better for whole-repo or long-document work.
Specs comparison
| DeepSeek V3 | Gemma 4 12B | |
|---|---|---|
| Provider | DeepSeek | |
| Type | Open source | Open source |
| Context window | 128K tokens | ✓256K tokens |
| Input / 1M tokens | Free (self-host) | Free (self-host) |
| Output / 1M tokens | Free (self-host) | Free (self-host) |
| Release date | 2024-12 | 2026-06 |
Benchmarks
| Benchmark | DeepSeek V3 | Gemma 4 12B |
|---|---|---|
| Pre-training scale | ~15T tokens | - |
| Total parameters | - | ~11.95B |
| Context window | - | 256K 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 Gemma 4 12B if...
- →You need an open, self-hostable multimodal model
- →Running on a single consumer GPU or a laptop
- →Data-privacy or on-prem requirements
- →You want a permissive license (Apache 2.0) for commercial use