Dell PowerEdge XE9680: Local AI & Business Fit
Dell's flagship 8-GPU AI server, configurable with H100 or H200 — a rack-scale building block for AI clusters.
Here’s what the Dell PowerEdge XE9680 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.
Specs at a glance
- Memory
- 640 GB
- Memory type
- 8x 80GB HBM3 (aggregate, H100 config)
- Bandwidth
- 3,350 GB/s
- Approx FP16
- 7,920 TFLOPS
- Architecture
- NVIDIA HGX (8-GPU), H100/H200 options
- Process
- TSMC 4N
- Power
- 10,000 W
- Launch year
- 2023
Specs are approximate figures. memoryGB reflects an 8x H100 configuration; an H200 build raises this substantially. Per-GPU bandwidth shown. Datacenter power and cooling required.
AI compatibility scores
Transparent 0–100 heuristics blending usable memory, bandwidth and compute — relative guidance, not benchmarks.
Compatible LLMs
Open-weight chat, coding and reasoning models from our catalog graded for the Dell PowerEdge XE9680, best fit first.
- DeepSeek-R1 671B (MoE)DeepSeek · 671B · MIT
Fits at Q4_K_M (~400GB) with ~163.2GB headroom — about 1 concurrent instance.
Q4_K_M · ~400GBRuns well - Llama 3.1 405BLlama · 405B · Llama Community License
Fits at Q8_0 (~410GB) with ~153.2GB headroom — about 1 concurrent instance.
Q8_0 · ~410GBRuns well - Qwen3 235B-A22B (MoE)Qwen · 235B · Apache-2.0
Fits at FP16 (~470GB) with ~93.2GB headroom — about 1 concurrent instance.
FP16 · ~470GBRuns well - Qwen2.5 72BQwen · 72B · Qwen License
Fits at FP16 (~145GB) with ~418.2GB headroom — about 3 concurrent instances.
FP16 · ~145GBRuns well - Llama 3.1 70BLlama · 70B · Llama Community License
Fits at FP16 (~140GB) with ~423.2GB headroom — about 4 concurrent instances.
FP16 · ~140GBRuns well - Llama 3.3 70BLlama · 70B · Llama Community License
Fits at FP16 (~140GB) with ~423.2GB headroom — about 4 concurrent instances.
FP16 · ~140GBRuns well - DeepSeek-R1 Distill Llama 70BDeepSeek · 70B · MIT
Fits at FP16 (~140GB) with ~423.2GB headroom — about 4 concurrent instances.
FP16 · ~140GBRuns well - Mixtral 8x7B (MoE)Mistral · 47B · Apache-2.0
Fits at FP16 (~90GB) with ~473.2GB headroom — about 6 concurrent instances.
FP16 · ~90GBRuns well
Best models by business workload
Best for coding agents
Code completion, review and refactoring on private source.
- Qwen3 235B-A22B (MoE)Runs well
- Qwen2.5 72BRuns well
- Llama 3.3 70BRuns well
Best for RAG / search
Answering over your documents with citations.
- Qwen2.5 72BRuns well
- Llama 3.1 70BRuns well
- Llama 3.3 70BRuns well
Best for business automation
Document extraction and back-office workflows.
- Llama 3.1 70BRuns well
- Gemma 2 27BRuns well
- Gemma 3 27BRuns well
Good for a private AI Business OS?
Yes — this is a viable private AI Business OS host for an org-wide, multi-agent deployment, running models like DeepSeek-R1 671B (MoE) on hardware you control.
Headline model it can host: DeepSeek-R1 671B (MoE).
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:
- Strong fitCustomer Support Agent
Answers customers over your docs, drafts replies, triages tickets.
- Strong fitDocument / RAG Agent
Reads contracts, reports and wikis and answers with citations.
- Strong fitLegal Evidence Agent (DocMatch-style)
Searches case files and exhibits to surface and link evidence.
- Strong fitHotel / Hospitality Agent
Handles guest messaging, bookings and front-desk automation.
- Strong fitAccounting / Odoo Agent
Extracts invoices, reconciles data and drives ERP workflows.
- Strong fitCoding / Product Engineering Agent
Local code completion, review and refactoring on private source.
- Strong fitFounder Ops / Business Command Center
A fleet of cooperating agents running the whole business privately.
“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 Dell PowerEdge XE9680 good for running local AI?+
It scores 100/100 on our Local AI Score (Elite tier), based on its 640GB of memory and available bandwidth/compute. That makes it suited to the Enterprise AI Business OS tier.
Which LLMs can the Dell PowerEdge XE9680 run?+
Comfortably: DeepSeek-R1 671B (MoE) (Q4_K_M), Llama 3.1 405B (Q8_0), Qwen3 235B-A22B (MoE) (FP16). Larger models may run with heavier quantization or by splitting across devices.
Should I run AI locally or in the cloud on the Dell PowerEdge XE9680?+
Local-first is recommended. Datacenter-class capacity is best run on-prem (or in colocation) for sustained, high-volume private workloads, with cloud as overflow.
Can I turn the Dell PowerEdge XE9680 into a private AI Business OS?+
Yes. AI Business OS can run on this machine at the Enterprise tier, giving you private agents on your own hardware. See the call-to-action above to get started.
Turn the Dell PowerEdge XE9680 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.
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