$ diff embeddinggemma-2 mimo-v2-6-pro
EmbeddingGemma 2 vs MiMo-V2.6-Pro
Values come from EmbeddingGemma 2 and MiMo-V2.6-Pro, 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
- $0.435
- $/M out
- $0.87
What actually differs
- Context window
- MiMo-V2.6-Pro takes 1M against 8K — 125× more room in a single request.
- Weights
- Both publish weights — EmbeddingGemma 2 under Apache 2.0, MiMo-V2.6-Pro under MIT (open weights). Check the licences rather than assuming they permit the same commercial use.
- Recency
- EmbeddingGemma 2 shipped 14 days after MiMo-V2.6-Pro (2026-10-06 vs 2026-09-22).
Full spec
| Attribute | EmbeddingGemma 2 | MiMo-V2.6-Pro |
|---|---|---|
| Developer | Google DeepMind | Xiaomi |
| Released | 2026-10-06 | 2026-09-22 |
| Context window | 8K tokens | 1M tokens |
| Pricing | not recorded | no vendor list price — weights are MIT and self-hostable; routed providers reported at $0.435/M input · $0.87/M output |
| License | Apache 2.0 | MIT (open weights) |
| Availability | Weights on Hugging Face and Kaggle; local inference | Hugging Face as `XiaomiMiMo/MiMo-V2.6-Pro-RL`; hosted via third-party routers |