$ diff embeddinggemma-2 deepseek-v4-1-flash
EmbeddingGemma 2 vs DeepSeek V4.1-Flash
Values come from EmbeddingGemma 2 and DeepSeek V4.1-Flash, where each is cited to its source. This page states no benchmark result and ranks neither model — it puts two published specifications next to each other. Where a lab has not published a figure, the row says so rather than guessing.
Google DeepMindEmbeddingGemma 2
- context
- 8K
- weights
- open
- $/M in
- —
- $/M out
- —
- context
- 1M
- weights
- open
- $/M in
- $0.15
- $/M out
- $0.6
What actually differs
- Context window
- DeepSeek V4.1-Flash takes 1M against 8K — 125× more room in a single request.
- Weights
- Both publish weights — EmbeddingGemma 2 under Apache 2.0, DeepSeek V4.1-Flash under MIT (open-weight). Check the licences rather than assuming they permit the same commercial use.
- Recency
- EmbeddingGemma 2 shipped 26 days after DeepSeek V4.1-Flash (2026-10-06 vs 2026-09-10).
Full spec
| Attribute | EmbeddingGemma 2 | DeepSeek V4.1-Flash |
|---|---|---|
| Developer | Google DeepMind | DeepSeek |
| Released | 2026-10-06 | 2026-09-10 |
| Context window | 8K tokens | 1,000,000 |
| Pricing | not recorded | $0.15/M input (cache miss) · $0.003/M input (cache hit) · $0.60/M output, off-peak; peak rates double — see Pricing |
| License | Apache 2.0 | MIT (open-weight) |
| Availability | Weights on Hugging Face and Kaggle; local inference | DeepSeek API, Hugging Face (`deepseek-ai/DeepSeek-V4.1-Flash`) |