Mixedbread AI
mxbai Embed Large
当前
4.8M下载量805点赞Mar 2024发布日期1K tokens上下文Apache 2.0许可证80 优秀质量
mxbai Embed Large (0.33500000834465027B parameters) requires approximately 4.0 GB of VRAM with F16 quantization. For the best balance of quality and speed, we recommend hardware with at least 5 GB of VRAM.
快速开始
— 复制粘贴即可本地运行Copy-paste commands to run mxbai Embed Large on your machine.
Run
ollama run mxbai-embed-largeQuick specs
Parameters0.34B
Architecturedense
Context1K tokens
Modalityembedding
Min RAM0.1 GB
Rec. RAM0.7 GB (F16)
LicenseApache 2.0
Familymxbai
✓ RAG
About this model
快速推荐
最佳硬件
mxbai Embed Large 的最佳选择
运行此模型
量化选项
各量化级别的 VRAM 估算
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.1 GB | Low | — |
Q3_K_S | 3 | 0.2 GB | Low | — |
NVFP4 | 4 | 0.2 GB | Medium | — |
Q4_K_M | 4 | 0.2 GB | Medium | — |
Q5_K_M | 5 | 0.2 GB | High | — |
Q6_K | 6 | 0.3 GB | High | — |
Q8_0 | 8 | 0.4 GB | Very High | — |
F16 | 16 | 0.7 GB | Maximum | — |
硬件兼容性
全部硬件的适配估算
Computing compatibility...
内存详细分析
Reference: RTX 2060 6GB
Weights0.7 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
常见问题
FAQ — mxbai Embed Large
另请参阅