LLM Providers

Magnitudeminds is an
OpenAI Select Partner.

OpenAI Select Partner badge

We are an official member of the OpenAI Partner Network, OpenAI's program for organizations that help businesses build, deploy, and scale AI solutions. For clients, it means the team implementing your AI systems has been vetted and enabled by the provider behind them.

It does not change how we choose technology. We remain model-agnostic: we implement on OpenAI, Anthropic, Google, Meta, Mistral, and self-hosted open-weight models, based on your requirements, region, and where your data is allowed to live.

What it means for clients

Vetted by the provider

Select Partner status is granted after completing OpenAI's partner onboarding and training: use-case identification, workflow design, deployment planning, and taking API integrations to production.

Direct technical enablement

We work with OpenAI partner resources and enablement channels, which keeps our teams current on new models and API capabilities as they ship.

Enterprise-grade defaults

Deployments follow the OpenAI platform enterprise posture: business data sent via the API is not used for model training by default, the platform is SOC 2 Type 2 audited, and data residency options cover Europe and Asia.

All major providers

We implement all major LLM providers.

The partnership with OpenAI does not narrow our recommendations. These are the providers we implement in production today.

OpenAI

Select Partner

GPT model family via the OpenAI API and Azure OpenAI. Our Select Partner track record lives here.

Anthropic

Claude models via the Anthropic API, AWS Bedrock, and Google Vertex AI.

Google

Gemini models via Vertex AI, with Google Cloud grounding and tooling.

Meta Llama

Open-weight Llama models for self-hosted and cost-sensitive workloads.

Mistral

European provider with open-weight and hosted options, often chosen for EU requirements.

Open-weight & local

Qwen, DeepSeek, and other open models served with vLLM or Ollama where data cannot leave your infrastructure.

Managed, cloud, or self-hosted

Deployed where your constraints allow.

Managed provider APIs

Fastest path to production. Direct APIs from OpenAI, Anthropic, or Google, with enterprise data-use terms and no infrastructure to run.

Cloud-hosted models

Models inside your existing cloud contract and compliance boundary: Azure OpenAI, AWS Bedrock, or Google Vertex AI, deployed in your preferred region.

Self-hosted & on-premise

Open-weight models on your own GPUs or private cloud when data residency, air-gapping, or regulation requires it. We size, serve, and monitor the stack.

Hybrid routing

Many systems we build route between models: a frontier API for hard reasoning, a smaller or local model for volume work. One system, the right model per task.

How we choose

Five questions decide the model, in this order.

01Requirements

Task complexity, quality bar, latency, and cost per call decide the model class before any brand does.

02Region & residency

Where your data may live and be processed narrows the provider and hosting options first.

03Compliance

Industry rules (finance, health, public sector) often decide managed vs. self-hosted before anything else.

04Existing stack

If you are committed to Azure, AWS, or GCP, we deploy models inside that boundary.

05Portability

We build against provider-agnostic interfaces, so switching or adding models later is a config change, not a rewrite.

Unsure which model or hosting setup fits your case?

Bring us the requirements and constraints. We will recommend a provider and deployment model, and show you comparable systems we have already shipped.