llm_counts

by harleyszhang · Agent Tool · ★ 114

About llm_counts

llm theoretical performance analysis tools and support params, flops, memory and latency analysis.

gpu-performancellamallmllm-inferenceprofilerpython3transformer

Quick Facts

Stars114
Forks10
LanguagePython
CategoryAgent Tool
Quality Score38.25/100
Open Issues1
Last Updated2025-07-11
Created2023-07-26
Platformspython
Est. Tokens~505k

Compatible Skills

These tools work well together with llm_counts for enhanced workflows:

  • vllm-cli — semantic(0.23)+complementary+rare_topics+same_lang+similar_pop+shared_platform (58%)
  • Noema-Declarative-AI — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (55%)
  • ai-agents-reality-check — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)
  • bzm-mcp — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • data-analysis-llm-agent — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)

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Frequently Asked Questions

What is llm_counts?

llm_counts is llm theoretical performance analysis tools and support params, flops, memory and latency analysis.. It is categorized as a Agent Tool with 114 GitHub stars.

What programming language is llm_counts written in?

llm_counts is primarily written in Python. It covers topics such as gpu-performance, llama, llm.

How do I install or use llm_counts?

You can find installation instructions and usage details in the llm_counts GitHub repository at github.com/harleyszhang/llm_counts. The project has 114 stars and 10 forks, indicating an active community.

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