Models
LLMs and efficient models (LFMs) solve different jobs
Model-agnostic by design
We select and optimize models based on accuracy, latency, cost, privacy, hardware, and workload — including customer-hosted and open-weight options.
LLMs stay the enterprise flagship
Complex agents, grounded RAG, and deep reasoning still need large models. Efficient models extend Digicane beyond the cloud — they do not replace that layer.
Multi-model AI
Side-by-side: LLM · SLM · Efficient / LFM
Digicane is model-agnostic. We combine LLMs, SLMs, and efficient foundation models (LFMs) — we do not claim LFM replaces LLM.
Deep reasoning
Large Language Models (LLMs)
- Complex agents
- Enterprise RAG
- Analytics & synthesis
- Multi-step copilots
- · Maximum reasoning quality
- · Cloud or private VPC
- · Higher compute cost
- · Best for hard problems
Private / local
Small Language Models (SLMs)
- On-prem copilots
- Regulated automation
- Local assistants
- Cost-sensitive chat
- · Strong enough for many workflows
- · Easier private hosting
- · Lower latency at scale
- · Good mid-tier fit
Edge / offline
Efficient models / LFMs
- On-device AI
- Mobile & IoT
- Offline intelligence
- Camera / field inference
- · Low latency
- · Lower inference cost
- · Privacy at the device
- · Constrained compute
Want the full comparison? LLM vs LFM · Hybrid AI · Edge AI
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Related capabilities
FAQs
Does Digicane replace LLMs with LFMs?+
No. Digicane is model-agnostic. LLMs remain the primary layer for complex enterprise agents and RAG. Efficient models and LFMs are used where edge, offline, latency, or cost constraints dominate.
Do you sell a proprietary Digicane LFM?+
No. We select and optimize foundation models — including efficient/edge models — based on accuracy, latency, cost, privacy, hardware, and workload. We do not claim a Digicane-owned LFM.
When should we use an efficient or edge model?+
When the workload must run on-device or offline, needs very low latency, or must stay local for privacy or bandwidth — for example cameras, mobile apps, vehicles, or remote industrial sites.
Map the right model mix for your workload
Bring residency, latency, and cost constraints — Digicane will recommend a practical stack.