REPOGEO REPORT · LITE
go-skynet/go-llama.cpp
Default branch master · commit 6a8041ef · scanned 6/4/2026, 10:03:18 PM
GitHub: 905 stars · 113 forks
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 go-skynet/go-llama.cpp, 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
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- hightopics#1Add relevant topics to the repository
Why:
COPY-PASTE FIXgo, golang, llama.cpp, llm, large-language-models, ai, inference, bindings, cgo, gguf
- highreadme#2Strengthen the README's opening sentence to highlight core value
Why:
CURRENTLLama.cpp golang bindings.
COPY-PASTE FIXgo-llama.cpp provides high-level Go language bindings for the highly optimized llama.cpp library, enabling Go developers to efficiently run large language models (LLMs) locally with a simple, performant Go-native interface.
- mediumhomepage#3Add a homepage URL to the repository
Why:
COPY-PASTE FIXhttps://pkg.go.dev/github.com/go-skynet/go-llama.cpp
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.
- llama.cpp · recommended 2×
- Ollama · recommended 2×
- ggerganov/ggml · recommended 1×
- ONNX Runtime · recommended 1×
- microsoft/onnxruntime-go · recommended 1×
- CATEGORY QUERYWhat are the best Go libraries for running open-source LLMs on local hardware?you: #2AI recommended (in order):
- llama.cpp
- go-llama.cpp ← you
- Ollama
- GGML (ggerganov/ggml)
- ONNX Runtime
- microsoft/onnxruntime-go (microsoft/onnxruntime-go)
- gorgonia/onnx (gorgonia/onnx)
- TensorFlow Lite (tensorflow/tensorflow/lite/go)
- PyTorch
- gorgonia/gorgonia (gorgonia/gorgonia)
- gorgonia/cuda (gorgonia/cuda)
Show full AI answer
- CATEGORY QUERYLooking for performant Go bindings to run local large language models efficiently.you: #1AI recommended (in order):
- go-llama.cpp ← you
- llama.cpp
- ollama-go
- Ollama
- go-gpt4all
- gpt4all
- LocalAI
- go-transformers
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 go-skynet/go-llama.cpp?passAI did not name go-skynet/go-llama.cpp — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts go-skynet/go-llama.cpp in production, what risks or prerequisites should they evaluate first?passAI named go-skynet/go-llama.cpp 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 go-skynet/go-llama.cpp solve, and who is the primary audience?passAI named go-skynet/go-llama.cpp explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of go-skynet/go-llama.cpp. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
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go-skynet/go-llama.cpp — 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