"Strata" for GLM5.3 Flash is here for some! Project Maya
Summary
Project Maya 是一个开源工具,可在本地 GPU 上运行 321B 参数的 GLM-5.3-Flash 模型,通过分层存储(GPU/RAM/NVMe)和自动调优实现单卡 30+ tokens/s 的推理速度,并提供 OpenAI/Anthropic 兼容 API。
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@lxfater: Two old V100s can also run the 321 billion parameter GLM-5.3-Flash locally!! This open-source project is called Project…
开源项目 Project Maya 基于 Strata 引擎并适配 GLM,让两张 V100 32GB 显卡加约 32GB 内存和 NVMe SSD 即可本地运行 3210 亿参数的 GLM-5.3-Flash,生成速度可达 40 tokens/s,还内置 Web 聊天、图像理解和 OpenAI/Anthropic API 兼容。
@Gorden_Sun: Strata: Running a 100-billion-parameter model with just 12GB VRAM On a regular computer with 12GB VRAM, locally running…
Strata 项目实现在 12GB VRAM + 64GB RAM 的普通电脑上本地运行 125B 参数的 Qwen3.8-Flash-Next 模型,通过让常用专家模型常驻 GPU、全模型放入系统内存,并在 GPU、内存与 SSD 之间协同推理和投机采样来突破显存限制。
zai-org/GLM-5.3-Flash
GLM-5.3-Flash is the first natively multimodal model in the GLM-5 series, with 320B total parameters and 18B active parameters, outperforming previous versions and approaching Claude Opus 4.8 through a redesigned hybrid architecture for improved efficiency.
GLM-5.3-Flash
Release of GLM-5.3-Flash, an AI language model optimized for fast inference and performance updates.
@servasyy_ai: Strata 0.1.39 Multi-GPU Optimization is Here! No wonder—some folks' speeds have doubled!
Strata 0.1.39 has been released with multi-GPU optimization. According to user feedback, inference speeds in some scenarios have doubled — benchmarks on a 4090 48G running the hundred-billion-parameter Qwen3.8-Flash-Next showed a significant boost in tokens/s.