LinkT&B Editorial Department
A local LLM runs a language model on infrastructure you control. This can help define where confidential documents are processed, but evaluation, permissions, updates and backups still need an owner.
Contents
- Comparing cloud and local deployment
- Check where company information will be processed
- Compare operational responsibility as well as location
- Choose a model using your own questions
- Hardware price alone does not establish a payback period
- Test the operating process with a limited use case
- Discuss your project
Comparing cloud and local deployment
| Item | What to check | How to assess it |
|---|---|---|
| Quality | Task-specific questions and expected answers | Do not rely only on general benchmarks |
| Data controls | Retention, permissions and external traffic | Training exclusion is not zero retention |
| Cost | Hardware, electricity, fees and maintenance | Compare the same users and workload |
Check where company information will be processed
Before submitting contracts or design documents to AI, decide which information may be processed where. For cloud services, check the contract, retention, administrative settings, training use and subprocessors. “Not used for training” does not mean “not transmitted” or “never stored”.
A local LLM runs in an environment you control, such as a company workstation or server. But local inference does not keep the entire workflow local if OCR, speech recognition, search or logging sends data elsewhere.
Compare operational responsibility as well as location
Cloud providers maintain much of the infrastructure, while customers still need to manage permissions, contracts and service changes. Local deployments require updates, monitoring, backups and incident handling by an internal or contracted team. An on-premises location alone is not a security control for every risk.
Consider who will operate the system and how quickly it must recover. A single trial machine is not automatically suitable for a company-wide production service.
Choose a model using your own questions
Public benchmarks help shortlist models, but do not establish whether a model retrieves the right company document and supports its answer. Evaluate realistic questions, source accuracy, refusal when evidence is missing, and response time.
Memory requirements depend on model size, quantisation, context length and concurrency. Downloadable weights also do not imply unrestricted commercial use; check the licence for the exact release.
Hardware price alone does not establish a payback period
Dividing server cost by a cloud subscription ignores differences in capability and ongoing work. Include energy, hardware refresh, model updates, document preparation, operations and support. Cloud costs may include seats, tokens, retrieval and storage.
| Cost or benefit to assess | What to include |
|---|---|
| Initial setup | Hardware, installation, model evaluation, document ingestion and authentication integration |
| Ongoing operation | Electricity, service fees, monitoring, updates, backups and user support |
| Effect on the work | Changes in task time, checking and correction time, and actual usage |
| Exit or change | Data migration, deletion, hardware replacement and handover |
Measure the time saved after including human checking and correction. Define expected use and maintenance costs before claiming a financial return.
Test the operating process with a limited use case
A scoped internal FAQ needs document owners, permissions, citations and a support route. Confirm who will own the service before the trial ends. Different data classifications can justify different local and cloud arrangements.
AI evaluation must also address inaccurate answers and malicious instructions in retrieved content. NIST’s Generative AI Profile offers a useful risk-management reference. LinkT&B supports requirements, deployment, document integration and operations planning.
Discuss your project
We help select an AI architecture, evaluation process and operating model for your workflows and information requirements.