awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
Hsword avatar

Hsword/SpotServe

0
View on GitHub↗
134 stars·15 forks·Apache-2.0·7 views

SpotServe

SpotServe: Serving Generative Large Language Models on Preemptible Instances

Features

  • Inference Serving Engines - Serving generative models on preemptible cloud instances.

Star history

Star history chart for hsword/spotserveStar history chart for hsword/spotserve

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Open-source alternatives to SpotServe

Similar open-source projects, ranked by how many features they share with SpotServe.
  • intelligent-machine-learning/glakeintelligent-machine-learning avatar

    intelligent-machine-learning/glake

    502View on GitHub↗

    GLake: optimizing GPU memory management and IO transmission.

    Python
    View on GitHub↗502
  • microsoft/vattentionmicrosoft avatar

    microsoft/vattention

    495View on GitHub↗

    Dynamic Memory Management for Serving LLMs without PagedAttention

    C
    View on GitHub↗495
  • nvidia/tensorrt-llmNVIDIA avatar

    NVIDIA/TensorRT-LLM

    12,913View on GitHub↗

    TensorRT-LLM is a platform and toolkit designed for compiling, optimizing, and serving transformer-based models on accelerated hardware. It functions as a framework that transforms machine learning models into efficient execution graphs, providing an engine to refine these models for specific hardware to maximize throughput and minimize latency during text generation. The project distinguishes itself through advanced execution strategies that manage the entire inference pipeline. It utilizes kernel-level fusion and static graph execution to optimize mathematical operations and computational f

    Pythonblackwellcudallm-serving
    View on GitHub↗12,913
  • rulinshao/lightseqRulinShao avatar

    RulinShao/LightSeq

    223View on GitHub↗

    Official repository for DistFlashAttn: Distributed Memory-efficient Attention for Long-context LLMs Training

    Python
    View on GitHub↗223

Frequently asked questions

What does hsword/spotserve do?

SpotServe: Serving Generative Large Language Models on Preemptible Instances

What are the main features of hsword/spotserve?

The main features of hsword/spotserve are: Inference Serving Engines.

What are some open-source alternatives to hsword/spotserve?

Open-source alternatives to hsword/spotserve include: intelligent-machine-learning/glake — GLake: optimizing GPU memory management and IO transmission. microsoft/vattention — Dynamic Memory Management for Serving LLMs without PagedAttention. nvidia/tensorrt-llm — TensorRT-LLM is a platform and toolkit designed for compiling, optimizing, and serving transformer-based models on… rulinshao/lightseq — Official repository for DistFlashAttn: Distributed Memory-efficient Attention for Long-context LLMs Training.