Blackwell-tuned AI workstations,
validated for sustained runs.
Helmstone Systems builds pre-configured rigs around RTX 5090, RTX Pro 6000, and B200 accelerators — burned in for 48 hours against the workload you actually bought it for, shipped with a per-unit benchmark, and covered by on-site service.
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- Street price, RTX 5090
- $1,999 – $2,599
- Street price, RTX Pro 6000
- $8,500 – $10,500
- Helmstone integrator premium
- 25 – 35% over DIY parts cost
Unit datasheet / HS-5090-W1
- Accelerator
- 1× NVIDIA RTX 5090 · 32 GB GDDR7
- Host memory
- 256 GB DDR5-6400
- Storage
- 4 TB NVMe
- Validation
- Workload-specific 48-hour burn-in
- Commercial path
- From $6,400 · hosted card checkout
- Service tier
- On-site · 5-business-day swap
Burn-in window
48 hours
Workload coverage
Per-SKU
Service metros
5 priority regions
Per-unit benchmark
Published, signed
HW-01 / Catalog
Four systems, with the buying path made explicit.
W1 is the only published fixed-price card path. W2, W4, and RS remain approval and quote workflows while their final commercial details are pending.
HW-02 / Validation
The 48-hour burn-in is engineering, not theater.
Every unit runs the workload it was sold for — not a synthetic stress test — for two full days, with thermography and per-GPU telemetry sampled throughout. The result is a benchmark sheet that ships with the hardware and lives in our service portal for the life of the unit.
Spec review
Pre-sales engineer locks the SKU to the actual workload — model class, batch shape, expected duration.
Burn-in loop
Workload-specific driver + model stress runs for 48 hours at target utilization. Tail-latency, clocks, and VRAM thermals logged per minute.
Thermography
Infrared sweep at peak load. Hot-spot map attached to the unit datasheet; chassis airflow tuned if delta exceeds spec.
Sign-off
Engineer signs the per-unit benchmark. Unit is sealed, logged, and routed to regional service depot for delivery.
Validation record · SKU-specific output
- Workload
- Buyer-specific model and run profile
- Throughput
- Measured across the full validation window
- Tail latency
- Logged under sustained target utilization
- GPU thermals
- Per-accelerator telemetry recorded
- VRAM utilization
- Recorded against the configured workload
- Power envelope
- Measured against the final chassis
- Verified by
- Helmstone pre-sales engineering
Thermography · 30-minute mean
- Record
- Per SKU
- Window
- 48 hours
- Output
- Signed
HW-03 / Workload coverage
What the burn-in is actually exercising.
The metric we publish on each datasheet is one a real customer cares about — not a peak number that a five-minute stress run can hit. We pick the metric that decides whether the next day of work makes progress.
p99 tokens/sec
Multi-day LLM inference
Sustained token throughput on 70B–120B models, with KV cache pressure and tail latency measured across the burn-in window.
tokens/day · gradient stability
Frontier fine-tuning
LoRA, full-parameter, and continued pretraining runs sustained through checkpointing and optimizer state shuffle.
frames/sec · MFLOPS sustained
Video + scientific sim
Diffusion workloads and CFD/EM solvers held at target utilization, with thermal headroom verified against job profile.
HW-04 / Why Helmstone
The integrator premium
is the product.
The 25–35% uplift over DIY parts cost is what a researcher or an IT lead chooses to pay in a constrained 2026 market, in exchange for engineering time, supply allocation, and named accountability. We are not a retailer, and the margin does not fund one.
Per-sale margins of $1,000–$5,000+ fund a small bench of pre-sales engineers and field technicians. The moat is configurator depth, sustained-load thermal validation, and on-site coverage in priority metros — not SKU breadth.
Supply access
Dedicated channels in a market where TSMC 4NP allocation favors hyperscalers. We do not rely on the same retail channels you do.
Workload-locked SKU
A pre-sales engineer picks the configuration that wins for your job. Configurator depth, not configurator breadth.
48-hour burn-in
Per-unit, workload-specific, with a signed benchmark. Not a five-minute stress test that any retail unit could pass.
On-site service
Five priority metros today: Bay Area, Boston, Research Triangle, Austin, Seattle. Pickup within 24 hours, depot validation, return or swap in five business days.
HW-05 / Frequently asked
The questions pre-sales
actually hear.
If the answer you need is not below, talk to an engineer. The longer list lives at /faq.
HS-CS-00 / Latest case study
What buyers actually deployed,
paraphrased inside the published envelope.
The published case studies walk through buyer profile, configuration purchased, validation evidence with linked proof, and what the deployment looked like — every quantitative claim traced back to the canonical 48-hour burn-in.
HS-CS · University AI research lab
- Workload
- LoRA + full-parameter fine-tunes · 7B–13B base models
- Tier SKU
- HS-5090-W1
- Run duration
- ~72–96 hours / fine-tune · weekly cadence
- Throughput envelope
- Inside published worst-hour tok/s
- Junction temperature
- Max 79 °C · 30-min mean ≤ 72 °C
- Wall-meter watts
- ≤ 612 W · clean PD envelope
HS-06 / Engage
Spec a build, or read the burn-in
that proves it.
Every order begins with a pre-sales engineer. If your team is buying a single workstation or equipping a research lab, write to us with the workload — model class, expected duration, batch shape — and we will return a configuration, a benchmark target, and a quote.
What to include
- 01.Model class and size (parameters, tokenizer, context length)
- 02.Expected job duration per run, and runs per week
- 03.Site location and preferred service metro
- 04.Procurement vehicle (PO, grant, capital)
Reply within one business day, signed by an engineer with a configuration and a benchmark target.