Deploy, manage, and secure frontier open-source language models in your private cloud or your own physical hardware. No shared-queue rate limits. No external data harvesting. Absolute sovereignty.
Deploy in your own cloud or on private local hardware. Keep control over data, access, and uptime decisions.
You are the product. Proprietary context can train external provider advantage.
Cloud-hosted private runtime or fully private on-prem stack. Your data boundary, your policy.
Frontier H100/H200/B200 systems are quote-only and allocation-dependent. For most customers, the practical path starts with workstation-class pro GPUs, previous-generation datacenter cards, or a cloud bridge while local hardware is sourced.
Fastest realistic start for local private AI pilots, demos, RAG, coding agents, and quantized 7B-70B models.
Private inference server for heavier workloads, multiple users, and stronger uptime requirements.
Large enterprise deployment, high concurrency, or advanced model hosting where budget and procurement cycles are ready.
Hardware sizing, procurement support, OS and driver setup, model runtime, private API, chat UI, retrieval, access controls, monitoring, backups, and maintenance.
Pricing references checked 2026-05-26. Final quotes depend on live channel availability, warranty, taxes, shipping, power, cooling, and support terms.
Current model portfolio with expanded benchmark dimensions for planning and routing decisions.
| Benchmark / Model | DeepSeek V4 Flash | DeepSeek V4 Pro | Qwen 3.6 | Kimi K2.6 | Gemma 4 | GLM 5.1 | Meta Llama 4 Scout | GPT 5.5 (reference) | Claude Opus 4.7 (reference) |
|---|---|---|---|---|---|---|---|---|---|
| Provider | DeepSeek | DeepSeek | Qwen | Moonshot AI | Zhipu | Meta | OpenAI | Anthropic | |
| Parameters | 236B (MoE, ~21B active) | 671B (MoE, ~37B active) | 235B (MoE, ~22B active) | 1T (MoE, ~32B active) | 27B dense | 355B (MoE, ~35B active) | 400B (MoE) | Undisclosed | Undisclosed |
| Context | 256K | 1M | 256K | 256K | 128K | 200K | 10M | Provider-defined | Provider-defined |
| MMLU-Pro (%) | 78.1 | 84.4 | 79.6 | 85.8 | 72.9 | 81.7 | 83.8 | 88.9 | 87.4 |
| SWE-bench (%) | 52.4 | 64.8 | 56.1 | 67.7 | 34.8 | 58.6 | 61.4 | 73.6 | 70.9 |
| HumanEval+ (%) | 83.2 | 91.3 | 86.9 | 92.4 | 71.2 | 87.1 | 89.6 | 95.1 | 94.2 |
| GPQA (%) | 61.2 | 68.6 | 63.8 | 70.3 | 54.9 | 65.4 | 70.1 | 75.9 | 73.8 |
| GSM8K (%) | 91.4 | 95.8 | 92.5 | 96.2 | 87.1 | 93.4 | 95.2 | 97.8 | 97.1 |
| ARC-Challenge (%) | 88.7 | 92.9 | 89.6 | 93.7 | 81.4 | 90.8 | 92.6 | 95.2 | 94.3 |
| IFEval (%) | 72.1 | 79.4 | 74.8 | 81.2 | 66.2 | 76.6 | 79.3 | 85.7 | 84.5 |
| MT-Bench (10 max) | 7.9 | 8.6 | 8.1 | 8.8 | 7.1 | 8.3 | 8.5 | 9.2 | 9 |
| Role | Supported | Supported | Supported | Supported | Supported | Supported | Supported | Reference | Reference |
Same assistant interface, very different operating reality. Sovereign removes these failure modes with private cloud or on-prem deployment.
Rate Limit Hit Mid Workflow
Typical Big Tech Session
How Sovereign Fixes It
Toggle core capabilities to see how the private AI system changes.
Cloud-hosted private runtime or fully private on-prem hardware.
Updating exchange rates... using fallback rates until the live check completes.
Checking live Azure H100 prices...
Pricing shown here is an estimate; we will provide a final quote after reviewing your requirements.
For advanced AI-native products, we run bespoke engineering programs beyond the standard deployment path.
