$ diff embeddinggemma-2 minimax-m3
EmbeddingGemma 2 vs MiniMax M3
Values come from EmbeddingGemma 2 and MiniMax M3, 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
- $0.3
- $/M out
- $1.2
What actually differs
- Context window
- MiniMax M3 takes 1M against 8K — 125× more room in a single request.
- Weights
- Both publish weights — EmbeddingGemma 2 under Apache 2.0, MiniMax M3 under Open-weight (HuggingFace). Check the licences rather than assuming they permit the same commercial use.
- Recency
- EmbeddingGemma 2 shipped 127 days after MiniMax M3 (2026-10-06 vs 2026-06-01).
Full spec
| Attribute | EmbeddingGemma 2 | MiniMax M3 |
|---|---|---|
| Developer | Google DeepMind | MiniMax |
| Released | 2026-10-06 | 2026-06-01 |
| Context window | 8K tokens | 1,000,000 tokens (1M); min. 512K guaranteed |
| Pricing | not recorded | $0.30/M input · $1.20/M output ($0.06/M cached input) — OpenRouter catalogue, read 2026-07-28 |
| License | Apache 2.0 | Open-weight (HuggingFace) |
| Availability | Weights on Hugging Face and Kaggle; local inference | API (global, including English) + open-weight on HuggingFace |