Open Source Models
Self-hosted AI with Llama, Mistral, and other open-source models
Overview
Open-source models like Llama, Mistral, Qwen, and DeepSeek have closed the gap with GPT-4 — and you can run them yourself. Full data sovereignty, predictable costs, no API rate limits, and no vendor lock-in. We deploy, fine-tune, and operate open-source models for teams that need control.
Capabilities
Model Selection & Benchmarking
We evaluate and benchmark models (Llama 3, Mistral, Qwen, DeepSeek, Phi) against your actual use cases.
Self-Hosted Deployment
Deploy on your own cloud, on-prem, or air-gapped environments with full data control.
Quantization & Optimization
Run large models on smaller hardware with GPTQ, AWQ, and GGUF quantization for 3–10x cost reduction.
Fine-Tuning on Your Data
LoRA and full fine-tuning on your proprietary data for task-specific accuracy gains.
Use Cases
- Data-sensitive applications (legal, medical, financial)
- Air-gapped or on-premise deployments
- High-volume inference with cost constraints
- Fine-tuned domain-specific models
- Edge AI deployments
- Offline and low-connectivity scenarios
Ideal For
- Privacy-conscious organizations
- Regulated industries with data residency needs
- Companies hitting API cost ceilings
- Teams wanting no vendor lock-in
Frequently Asked Questions
Are open-source models as good as GPT-4?
For many tasks, yes. Llama 3.1 405B and DeepSeek V3 match or beat GPT-4 on benchmarks. For frontier reasoning, closed models still lead.
What hardware do we need?
Depends on model size. Small models (7B–13B) run on a single GPU. Large models need multi-GPU setups. We right-size for your workload.
Ready to Deploy Open Source Models?
Book a free AI Deep Dive and we'll map Open Source Models to your business needs, team capabilities, and budget.
Book Your AI Deep Dive