DeepSeek V4 Flash vs Gemma 3
Pricing, benchmarks, and use case comparison
Quick take
- •DeepSeek V4 Flash is meaningfully stronger at math (86 vs 62 on our capability index).
- •Gemma 3 is meaningfully stronger at multimodal (70 vs 10).
- •DeepSeek V4 Flash has a 1M tokens context window vs 128K tokens (32K for the 1B variant) - better for whole-repo or long-document work.
Specs comparison
| DeepSeek V4 Flash | Gemma 3 | |
|---|---|---|
| Provider | DeepSeek | Google DeepMind |
| Type | Open source | Open source |
| Context window | ✓1M tokens | 128K tokens (32K for the 1B variant) |
| Input / 1M tokens | Free (self-host) | Free (self-host) |
| Output / 1M tokens | Free (self-host) | Free (self-host) |
| Release date | 2026-04 | 2025-03 |
Benchmarks
| Benchmark | DeepSeek V4 Flash | Gemma 3 |
|---|---|---|
| Reasoning (vs V4 Pro) | Closely approaches V4 Pro | - |
| MATH (27B) | - | 89% |
| MMMU (27B, multimodal) | - | 64.9% |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose DeepSeek V4 Flash if...
- →You want most of V4 Pro's capability at a lower price and higher throughput
- →You need long context but on a tighter compute or cost budget
- →You are serving high request volumes where per-token cost dominates
- →You want an open model small enough to self-host on modest multi-GPU setups
Choose Gemma 3 if...
- →You need an open, self-hostable model with a size to match your hardware
- →Multilingual or multimodal tasks on-prem
- →Privacy-sensitive or offline deployments
- →Fine-tuning on your own data