Llama 4 (Meta), DeepSeek V3 and Mistral Large compete with GPT-4o on most benchmarks. Self-hosted inference costs are 5-10x lower. But the ease of use and ecosystem of proprietary models remain real advantages.
• Fast start essential (<1 week)
• No internal MLOps team
• Best reasoning needed (Claude Opus 4.6)
• Advanced multimodal (GPT-4o)
• Ecosystem integration (Azure OpenAI, Google Workspace)
• Sensitive data / regulated sector
• High volume (API costs prohibitive)
• Fine-tuning on proprietary data needed
• Data sovereignty required
• Air-gapped deployment required
Free commercial licence. Variants 8B to 405B. Llama 4 Scout (17B MoE) on a single A100. De facto standard for on-premise deployments in Europe.
Best open-weights on GPQA Diamond (85%+). 128K context. MIT licence. Performance close to GPT-4o at 1/10th the API cost.
French model (Paris). Excellent in French and Dutch. Apache 2.0. Deployable on OVHcloud for European sovereignty.
72B parameters. Apache 2.0. Excellent multilingual (Chinese, English, French). Strong on structured analytical tasks.
GPT-4o (OpenAI SaaS): ~$5,000/month
Claude Sonnet 4.6 (Anthropic SaaS): ~$3,000/month
Llama 4 (self-hosted, 2x A100): ~$400-600/month all-in
DeepSeek V3.2 (self-hosted): ~$350-500/month
Self-hosting breaks even at ~200,000 requests/month depending on prompt complexity.
Molderez Consult SRL analyses your volumes, GDPR constraints and needs to recommend the best proprietary/open-source architecture.
AI architecture audit