Square Codex and KoboldCpp: Bringing Fast LLaMA Model Inference to Your Local Infrastructure
KoboldCpp: Bringing Fast LLaMA
Running LLaMA models efficiently on standard CPUs used to be a challenge. But thanks to KoboldCpp, an advanced implementation built on top of llama.cpp, developers can now execute large language models quickly and smoothly without GPU acceleration. At Square Codex, we help companies adopt frameworks like KoboldCpp as part of their AI infrastructure, making local LLM deployments more accessible, cost-effective, and secure.
Our Costa Rica–based nearshore development teams have the technical expertise to integrate tools like KoboldCpp into real applications, helping North American businesses get the most out of their AI strategies while maintaining data control and low latency.
What Is KoboldCpp and How Does It Work
KoboldCpp is an optimized backend for running LLaMA-based models using CPU quantization techniques. It offers a web interface and chat-style user experience, supporting roleplay, memory, and long-form context better than many alternatives. Built to enhance llama.cpp, it uses techniques like GGUF support, multi-threading, and quantized models for speed and efficiency.
This tool is especially valuable for companies looking to run LLMs on local machines or in isolated environments where cloud usage is limited or undesirable. KoboldCpp runs models like LLaMA 2, Mistral, and custom fine-tunes with impressive performance.
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Advantages of Local Model Execution
Deploying models locally with KoboldCpp has major advantages. No external API calls means increased data privacy, instant response times, and no usage fees. At Square Codex, we guide clients in embedding these local models into customer support tools, documentation engines, or internal assistants.
With our help, companies can avoid vendor lock-in and maintain full control over their AI assets. Our developers know how to fine-tune the performance of KoboldCpp, configure memory management, and build custom interfaces to interact with the models seamlessly.
Seamless Integration from a Nearshore Team
Square Codex specializes in helping U.S. companies scale development with nearshore AI teams. Our developers work within your timezone, integrating directly into your workflows. We do not just provide staffing, we provide solutions.
When implementing KoboldCpp, our teams handle everything from model selection and quantization to deployment, interface design, and security. We ensure that your use of open-source LLM tools like KoboldCpp translates into real business value.
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Real Use Cases Across Industries
Whether you need document summarization, knowledge retrieval, AI chat assistants, or private data agents, KoboldCpp delivers efficient performance on standard hardware. This makes it perfect for sectors like healthcare, legal, finance, and education, where secure offline access is key.
At Square Codex, we have already deployed solutions using KoboldCpp that allow companies to process sensitive information securely, run models on internal networks, and interact with large datasets without sending data to the cloud.
Efficient Local AI with Square Codex
At Square Codex, we help businesses unlock the full potential of local AI deployment through platforms like KoboldCpp. Our nearshore development teams build custom applications that use CPU-friendly LLMs to reduce cost, increase control, and accelerate innovation. If you want to explore how local model inference can change the way your business uses AI, let our team help you bring that vision to life.
