Best LLM Inference Tools
Compare 5 top-rated llm inference tools. Find features, pricing, pros, cons, and alternatives.
🏆 Top Tools in This Category
AirLLM
🔴DeveloperLayer-by-layer LLM inference library that lets a 70B model run on a 4 GB GPU, or a 405B model on 8 GB.
GroqCloud
🔴DeveloperFast, low-cost LLM inference API powered by Groq's LPU chip, serving open-source models like Llama, Kimi K2, and Qwen at low latency.
KTransformers
🔴DeveloperHigh-performance framework from Tsinghua's KVCache.ai for running massive MoE models like DeepSeek-V3 and Kimi K2 on a single workstation.
SGLang
🔴DeveloperHigh-performance open-source serving framework for LLMs and multimodal models, optimized for structured generation and complex agent workloads.
vLLM
🔴DeveloperHigh-throughput, memory-efficient open-source inference and serving engine for LLMs, used as the default backend at many AI companies.
LLM Inference tools
AirLLM
🔴DeveloperLayer-by-layer LLM inference library that lets a 70B model run on a 4 GB GPU, or a 405B model on 8 GB.
Key Features:
Custom
GroqCloud
🔴DeveloperFast, low-cost LLM inference API powered by Groq's LPU chip, serving open-source models like Llama, Kimi K2, and Qwen at low latency.
Key Features:
Custom
KTransformers
🔴DeveloperHigh-performance framework from Tsinghua's KVCache.ai for running massive MoE models like DeepSeek-V3 and Kimi K2 on a single workstation.
Key Features:
Custom
SGLang
🔴DeveloperHigh-performance open-source serving framework for LLMs and multimodal models, optimized for structured generation and complex agent workloads.
Key Features:
Custom
vLLM
🔴DeveloperHigh-throughput, memory-efficient open-source inference and serving engine for LLMs, used as the default backend at many AI companies.
Key Features:
Custom
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