REPOGEO REPORT · LITE
casper-hansen/AutoAWQ
Default branch main · commit 88e4c76b · scanned 5/21/2026, 5:41:58 PM
GitHub: 2,337 stars · 301 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface casper-hansen/AutoAWQ, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- mediumabout#1Refine the repository description for clarity and keywords
Why:
CURRENTAutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:
COPY-PASTE FIXAutoAWQ implements the AWQ algorithm for 4-bit quantization, providing a 2x speedup for large language model (LLM) inference by reducing memory consumption.
- lowreadme#2Add a concise summary of AutoAWQ's original purpose to the README
Why:
CURRENTThe current README starts with "News: The vLLM project has fully adopted AutoAWQ" after the H1.
COPY-PASTE FIXAdd the following sentence directly after the `# AutoAWQ` heading and before the "News" section: 'AutoAWQ was an efficient library for 4-bit Activation-aware Weight Quantization (AWQ) to achieve 2x speedup for large language model (LLM) inference.'
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- bitsandbytes · recommended 1×
- AutoGPTQ · recommended 1×
- AWQ · recommended 1×
- llama.cpp · recommended 1×
- NVIDIA TensorRT-LLM · recommended 1×
- CATEGORY QUERYHow to achieve faster inference for large language models through 4-bit quantization?you: not recommendedAI recommended (in order):
- bitsandbytes
- AutoGPTQ
- AWQ
- llama.cpp
- NVIDIA TensorRT-LLM
- Intel OpenVINO
AI recommended 6 alternatives but never named casper-hansen/AutoAWQ. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat are the best libraries for 4-bit quantization to speed up LLM inference?you: not recommendedAI recommended (in order):
- bitsandbytes (TimDettmers/bitsandbytes)
- AWQ (Activation-aware Weight Quantization)
- GPTQ (Generative Pre-trained Transformer Quantization)
- AutoGPTQ (PanQiWei/AutoGPTQ)
- Optimum (Hugging Face) (huggingface/optimum)
- llama.cpp (ggerganov/llama.cpp)
AI recommended 6 alternatives but never named casper-hansen/AutoAWQ. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of casper-hansen/AutoAWQ?passAI named casper-hansen/AutoAWQ explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts casper-hansen/AutoAWQ in production, what risks or prerequisites should they evaluate first?passAI named casper-hansen/AutoAWQ explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo casper-hansen/AutoAWQ solve, and who is the primary audience?passAI named casper-hansen/AutoAWQ explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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casper-hansen/AutoAWQ — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite