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Reference · AI Workstations

Quad RTX 4090 AI Workstation (reference profile): Local AI & Business Fit

A serious local AI workstation: four RTX 4090s pool to 96GB, enough to serve flagship 70B models and run many concurrent agents privately.

Here’s what the Quad RTX 4090 AI Workstation (reference profile) means for a business that wants to run private AI on hardware it controls: which open LLMs fit, which agents it can power, the AI Business OS tier it suits, and whether to run local, cloud or hybrid.

75/100· Strong

Specs at a glance

Memory
96 GB
Memory type
GDDR6X (4× 24GB)
Bandwidth
1,008 GB/s
Approx FP16
1,320 TFLOPS
Architecture
Ada Lovelace
Process
TSMC 4N
Power
1,800 W
Launch year
2023

Specs are approximate figures. Representative profile. 96GB aggregate VRAM hosts flagship open models at 4-bit and high concurrency, but draws heavy power and needs careful cooling and a workstation/threadripper-class platform. A strong Business Command Center base.

AI compatibility scores

Transparent 0–100 heuristics blending usable memory, bandwidth and compute — relative guidance, not benchmarks.

Local AI (overall)75/100
Document RAG75/100
Coding agents80/100
Multi-agent67/100
Business automation72/100

Compatible LLMs

Open-weight chat, coding and reasoning models from our catalog graded for the Quad RTX 4090 AI Workstation (reference profile), best fit first.

  • Qwen2.5 72B
    Qwen · 72B · Qwen License

    Fits at Q8_0 (~78GB) with ~6.5GB headroom — about 1 concurrent instance.

    Q8_0 · ~78GBRuns well
  • Llama 3.1 70B
    Llama · 70B · Llama Community License

    Fits at Q8_0 (~75GB) with ~9.5GB headroom — about 1 concurrent instance.

    Q8_0 · ~75GBRuns well
  • Llama 3.3 70B
    Llama · 70B · Llama Community License

    Fits at Q8_0 (~75GB) with ~9.5GB headroom — about 1 concurrent instance.

    Q8_0 · ~75GBRuns well
  • DeepSeek-R1 Distill Llama 70B
    DeepSeek · 70B · MIT

    Fits at Q8_0 (~75GB) with ~9.5GB headroom — about 1 concurrent instance.

    Q8_0 · ~75GBRuns well
  • Mixtral 8x7B (MoE)
    Mistral · 47B · Apache-2.0

    Fits at Q8_0 (~50GB) with ~34.5GB headroom — about 1 concurrent instance.

    Q8_0 · ~50GBRuns well
  • CodeLlama 34B
    CodeLlama · 34B · Llama Community License

    Fits at FP16 (~68GB) with ~16.5GB headroom — about 1 concurrent instance.

    FP16 · ~68GBRuns well
  • Qwen2.5 32B
    Qwen · 32B · Apache-2.0

    Fits at FP16 (~64GB) with ~20.5GB headroom — about 1 concurrent instance.

    FP16 · ~64GBRuns well
  • Qwen3 32B
    Qwen · 32B · Apache-2.0

    Fits at FP16 (~64GB) with ~20.5GB headroom — about 1 concurrent instance.

    FP16 · ~64GBRuns well

See the full model catalog →

Best models by business workload

Best for coding agents

Code completion, review and refactoring on private source.

Best for RAG / search

Answering over your documents with citations.

Best for business automation

Document extraction and back-office workflows.

Good for a private AI Business OS?

✓

Yes — this is a viable private AI Business OS host for a department-scale deployment, running models like Qwen2.5 72B on hardware you control.

Headline model it can host: Qwen2.5 72B.

Where it falls short

  • ▸Requires datacenter-class power, cooling and physical space.

Business agents that make sense

How this machine fits the core AI Business OS agent archetypes:

  • Customer Support Agent

    Answers customers over your docs, drafts replies, triages tickets.

    Strong fit
  • Document / RAG Agent

    Reads contracts, reports and wikis and answers with citations.

    Strong fit
  • Legal Evidence Agent (DocMatch-style)

    Searches case files and exhibits to surface and link evidence.

    Strong fit
  • Hotel / Hospitality Agent

    Handles guest messaging, bookings and front-desk automation.

    Strong fit
  • Accounting / Odoo Agent

    Extracts invoices, reconciles data and drives ERP workflows.

    Strong fit
  • Coding / Product Engineering Agent

    Local code completion, review and refactoring on private source.

    Strong fit
  • Founder Ops / Business Command Center

    A fleet of cooperating agents running the whole business privately.

    Capable

“Cloud-assist” means run it locally for light loads and burst to the cloud for heavier jobs. See business use cases for how each agent maps to hardware.

Frequently asked questions

Is the Quad RTX 4090 AI Workstation (reference profile) good for running local AI?+

It scores 75/100 on our Local AI Score (Strong tier), based on its 96GB of memory and available bandwidth/compute. That makes it suited to the Business AI Business OS tier.

Which LLMs can the Quad RTX 4090 AI Workstation (reference profile) run?+

Comfortably: Qwen2.5 72B (Q8_0), Llama 3.1 70B (Q8_0), Llama 3.3 70B (Q8_0). Larger models may run with heavier quantization or by splitting across devices.

Should I run AI locally or in the cloud on the Quad RTX 4090 AI Workstation (reference profile)?+

Local-first is recommended. Enough capability to host real agents locally for privacy and predictable cost; use cloud only to burst beyond peak demand.

Can I turn the Quad RTX 4090 AI Workstation (reference profile) into a private AI Business OS?+

Yes. AI Business OS can run on this machine at the Business tier, giving you private agents on your own hardware. See the call-to-action above to get started.

Turn the Quad RTX 4090 AI Workstation (reference profile) into a private AI Business OS

Run your own AI agents on hardware you control — private by design, no per-seat data leaving your premises. BrainOutput helps you pick the right machine and turn it into a working AI Business OS.

Get started

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