Model overview
MLX conversion of Google EmbeddingGemma 2 in **BF16** format, retaining text, image, audio, and video encoders. The model produces normalized 768-dimensional embeddings. See the original model card for intended use, training information, evaluation, and limitations. Weight storage: 1.489 GB (decimal). Source revision: `914f7f89142e33e77833254d9c9b90c3cef7303b`. Converted with MLX-VLM revision `3d87e884`, from branch `pc/embeddinggemma-2`, and MLX 0.32.3. Apply the appropriate task prefixes from `config_sentence_transformers.json`. Queries and documents must use the same embedding dimension. Keep non-quantized weights and activations in BF16; do not cast this model to float16.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。