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parallax

Parallax is a distributed model serving framework that lets you build your own AI cluster anywhere

InfrastructureDeploy & ServeOrchestrationPython
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创建于 2025-09-22 · 更新于 2026-10-15 · 今日第 10462 名
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GradientHQ/parallax 排名第 10,462，有 1,397 个星标。

同类别比较

GradientHQ/parallax 排名第 10,462，此处有 8 个同类条目；doonny/PipeCNN 排名第 10,474。

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关键参数与规格
关键参数与规格
参数值
语言Python
类别Infrastructure
子类别Deploy & Serve,Orchestration
关键词Distributed
星标数1,397
分叉数150
贡献者26
创建日期2025-09-22
更新日期2026-10-15
1 天星标数0
7 天星标数0
排名10,462
上次排名10,457
排名变化-5
7 天星标排名12,632
上次 7 天星标排名12,664
7 天星标排名变化32
总星标排名8,577
上次总星标排名8,567
总星标排名变化-10
README 摘录

**Gradient** | **Blog** | **X/Twitter (Gradient)** | **X/Twitter (Parallax)** | **Discord** | **Arxiv** News [2026/02] 🦞 Parallax now supports OpenClaw integration! See Docs [2025/10] 🔥 Parallax won #1 Product of The Day on Product Hunt! About A fully decentralized inference engine developed by Gradient. Parallax lets you build your own AI cluster for model inference onto a set of distributed nodes despite their varying configuration and physical location. Its core features include: **Host local LLM on personal devices** **Cross-platform support** **Pipeline parallel

model sharding** **Paged KV cache management & continuous batching for Mac** **Dynamic request scheduling and routing for high performance** The backend architecture: P2P communication powered by Lattica GPU backend powered by SGLang and vLLM Mac backend powered by MLX LM User Guide Installation Getting Started Working with OpenClaw 🦞 Quick Install Contributing We warmly welcome contributions of all kinds! For guidelines on how to get involved, please refer to our Contributing Guide. 2 is built for stronger reasoning and agent workflows, adding

thinking-aware tool use while keeping both thinking and non-thinking tool-use modes available. 7 | MiniMax M3: Frontier Coding, 1M Context, Native Multimodality | MiniMax-M3 is a sparse-attention model for coding, agentic work, long-context tasks, and multimodal input, with MiniMax-M2. 2: Built for Long-Horizon Tasks | GLM-5. 2 is Z AI's latest flagship model for long-horizon coding agents, large-scale implementation, automated research, and performance optimization. | |Kimi-K2 | Moonshot AI | Kimi-K2-Thinking Kimi

-K2-Instruct-0905 | Kimi K2 Thinking | Kimi-K2-Thinking is the reasoning-focused Kimi-K2 variant for long-horizon agentic workflows, multi-step reasoning, and tool-heavy tasks. 6-35B-A3B: Agentic Coding Power, Now Open to All | Qwen3. 6-35B-A3B is an open-weight MoE model focused on stable, practical coding and agentic workflows, with Qwen3-Next and larger Qwen3 MoE variants also represented. | |gpt-oss | OpenAI | gpt-oss-120b gpt-oss-safeguard-120b | Introducing gpt-oss-safeguard

| gpt-oss-120b is OpenAI's open-weight GPT model; gpt-oss-safeguard-120b adds policy-driven reasoning classification for flexible moderation and safety workflows. 5-Flash is a sparse MoE foundation model for efficient reasoning and agentic workflows, activating a small subset of its total parameters per token.

常见问题

记录了多少星标和分叉？

GradientHQ/parallax 有 1,397 个星标和 150 个分叉。

仓库排名是多少？

GradientHQ/parallax 排名第 10,462。

记录的语言和类别是什么？

GradientHQ/parallax 有 1,397 个星标，语言为 Python，类别为 Infrastructure。

哪个仓库排名最接近？

GradientHQ/parallax 与 doonny/PipeCNN 比较，后者排名第 10,474，有 1,393 个星标。

README
 ![](docs/images/parallax.png)

Trusted by Partners

   ![SGLang](docs/images/sglang.png) 
   ![vLLM](docs/images/vllm.png) 
   ![Qwen](docs/images/qwen.avif) 
   ![DeepSeek](docs/images/deepseek.png) 
   ![Kimi](docs/images/kimi.png) 
   ![Minimax](docs/images/minimax.png) 
   ![ZAI](docs/images/zai.svg)

Gradient | Blog | X/Twitter (Gradient) | X/Twitter (Parallax) | Discord | Arxiv

News

  • [2026/02] 🦞 Parallax now supports OpenClaw integration! See Docs
  • [2025/10] 🔥 Parallax won #1 Product of The Day on Product Hunt!
  • [2025/10] 🔥 Parallax version 0.0.1 has been released!

About

A fully decentralized inference engine developed by Gradient. Parallax lets you build your own AI cluster for model inference onto a set of distributed nodes despite their varying configuration and physical location. Its core features include:

  • Host local LLM on personal devices
  • Cross-platform support
  • Pipeline parallel model sharding
  • Paged KV cache management & continuous batching for Mac
  • Dynamic request scheduling and routing for high performance

The backend architecture:

User Guide

Quick Install

git clone https://github.com/GradientHQ/parallax.git
cd parallax
./install.sh
source .venv/bin/activate
parallax serve -m Qwen/Qwen3.5-0.8B

Contributing

We warmly welcome contributions of all kinds! For guidelines on how to get involved, please refer to our Contributing Guide.

Supported Models

Provider HuggingFace Collection Blog Description
DeepSeek Deepseek DeepSeek-V3.2
DeepSeek-R1
DeepSeek-V3.2 Release DeepSeek-V3.2 is built for stronger reasoning and agent workflows, adding thinking-aware tool use while keeping both thinking and non-thinking tool-use modes available.
MiniMax MiniMax AI MiniMax-M3
MiniMax-M2.7 MiniMax M3: Frontier Coding, 1M Context, Native Multimodality MiniMax-M3 is a sparse-attention model for coding, agentic work, long-context tasks, and multimodal input, with MiniMax-M2.7 kept as a supported sibling model.
GLM Z AI GLM-5.2
GLM-5.1
GLM-4.7 GLM-5.2: Built for Long-Horizon Tasks GLM-5.2 is Z AI's latest flagship model for long-horizon coding agents, large-scale implementation, automated research, and performance optimization.
Kimi-K2 Moonshot AI Kimi-K2-Thinking
Kimi-K2-Instruct-0905 Kimi K2 Thinking Kimi-K2-Thinking is the reasoning-focused Kimi-K2 variant for long-horizon agentic workflows, multi-step reasoning, and tool-heavy tasks.
Qwen Qwen Qwen3.6-35B-A3B Qwen3.6-35B-A3B: Agentic Coding Power, Now Open to All Qwen3.6-35B-A3B is an open-weight MoE model focused on stable, practical coding and agentic workflows, with Qwen3-Next and larger Qwen3 MoE variants also represented.
gpt-oss OpenAI gpt-oss-120b
gpt-oss-safeguard-120b Introducing gpt-oss-safeguard gpt-oss-120b is OpenAI's open-weight GPT model; gpt-oss-safeguard-120b adds policy-driven reasoning classification for flexible moderation and safety workflows.
Step StepFun Step-3.5-Flash Step 3.5 Flash Step-3.5-Flash is a sparse MoE foundation model for efficient reasoning and agentic workflows, activating a small subset of its total parameters per token.
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