Designed for on-premise LLM workloads in Malaysia-controlled infrastructure. Pricing, performance, and residency depend on the approved deployment configuration. Planned integrations include task segmentation, smart routing, and parser adapters.
Direct Answer
A Private LLM is a model deployment designed to keep inference, access and data handling under organisational control. It can run locally or behind a private network, depending on the architecture and operational requirements.
Access to world-class open-source models, optimised for local deployment
Alibaba Cloud. Multimodal model (text+image) with 128K context window.
Meta. Instruction-tuned for complex tasks and reasoning.
DeepSeek AI. Deep reasoning & strategic analysis.
Moonshot AI. Long-context champion for documents.
Tsinghua AI Lab. Coding & system generation.
Google DeepMind. Fast classification & tagging.
Mistral AI. Translation & rewriting.
Auto-cycling through AINNA LLM Hub models each scored across 6 weighted dimensions
Illustrative pilot packages. Final pricing, token limits, support, and service levels are confirmed in the customer agreement.
| Feature | AINNA LLM | OpenAI |
|---|---|---|
| Data Location | MY Only | Global |
| Cost per 1M tokens | Pilot estimate | Varies by model |
| Latency | Deployment target | Varies by model |
| Bahasa Malaysia | Optimized | Limited |
| Support | MY Team | Global |
Explore a controlled local pilot with deployment-specific pricing, performance validation, and data-residency controls.
Research evidence: Research Hub Β· Private AI Architecture
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