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Synapse Frontier AI Workstation
Synapse Frontier AI Workstation
Built for one thing.
Production AI models. At a scale that doesn't ask you to compromise.
Frontier is centred around the RTX Pro 6000 Blackwell - 96GB of ECC GDDR7 memory and 1.8 TB/s of bandwidth. That's enough to full fine-tune a 70B parameter model, and headroom to run 120B MoE models that most local hardware simply can't load.
Pair that with a 96-core Threadripper PRO and 256GB of ECC system memory, and you have a machine that handles production training workloads without negotiating with its own spec.
Production inference
The models that push the boundary of what's openly available. Running 19 tok/s, 71 tok/s across 4 concurrent on 70B model
Fine-tuning at scale
Full fine-tune on 70B. Distributed-ready. The kind of training work that usually requires a cloud contract.
Private by default
Running on hardware that belongs to you means no usage limits, no data leaving your network, and no bill at the end of the month.
Our support service helps you get up and running, from hardware to your first models
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Built for your workload
At its heart is the RTX PRO 6000 Max-Q Workstation Edition — 96 gigabytes of ECC GDDR7 memory at 1.79 TB/s of bandwidth, in a 300-watt power envelope deliberately tuned to live in an office, not a server room. Every byte of the VRAM, every byte of the bandwidth, none of the noise.
A deliberate decision. Not a compromise.
The Max-Q variant of the RTX PRO 6000 Blackwell is the same silicon as the 600-watt full-fat card — same 96GB ECC VRAM, same 1.79 TB/s bandwidth, same fifth-generation Tensor Cores. It runs at 300W instead of 600W. That decision shapes what Frontier is.
Identical memory. Identical bandwidth.
Where it matters for LLMs — the things that decide whether a 70B model fits and how fast it runs — the Max-Q is the full card. 96GB ECC GDDR7. 1.79 TB/s bandwidth. None of that changes.
Real-world inference loss: 15–20%.
The lower TDP costs you on sustained peak compute — but LLM inference is bandwidth-bound, not compute-bound. Real-world Llama 70B throughput is within fifteen to twenty percent of the 600W card, in a chassis you can actually live with.
Deskside thermals.
At 300W, Frontier runs in a standard tower chassis with conventional cooling. No 1600W datacentre PSU, no rack, no liquid cooling loop. It sits where your team sits.
Quieter. Cooler. Lower power bill.
Three hundred watts of GPU plus a Threadripper is still a serious load, but it's a load that runs at office-noise levels and pulls within a single 13-amp socket's headroom. The Frontier is a workstation. Not a server pretending to be one.
Scale with speed
Your whole team, running simultaneously, getting instant responses.
On a 14 billion parameter model, Chillblast Synapse Frontier delivers 790 tokens per second across 32 concurrent requests. Aggregate throughput scales with every user you add.
What it runs
Inference
| Model | Precision | VRAM | Tokens / sec | Concurrent users |
|---|---|---|---|---|
| Llama 3 8B Drafting, agents | FP16 | ~16 GB | ~240 | 128 |
| Qwen 2.5 14B | FP16 | ~28 GB | ~180 | 48 |
| Llama 3 32B Production reasoning | Q8 | ~34 GB | ~110 | 32 |
| Llama 3.3 70B | Q4 | ~40 GB | ~90–110 | 12 |
| Llama 3.3 70B | FP8 | ~70 GB | ~60 | 6 |
| Llama 3.3 70B Full fidelity · the sweet spot | FP16 | ~140 GB | ~32 (partial offload) | 1–2 |
| Mixtral 8×22B MoE — fast at scale | Q4 | ~80 GB | ~70 | 8 |
| Llama 3.1 405B Frontier open model | Q4 | ~230 GB | ~8–12 (CPU offload) | 1 |
Fine-tuning
| Task | Method | Time / Requirement |
|---|---|---|
| 70B LoRA fine-tune | QLoRA | ~10 hours |
| 30B full fine-tune | Native | Comfortable |
| 70B full fine-tune | Native | Multi-GPU or 2× Frontier |
Image generation
A model that knows your business
Foundation models know almost nothing about you. For good reason.
Every prompt leaves the building, and every experiment has a cost attached. Synapse Frontier is built for the point where that stops making sense.
Your models run locally, privately, on hardware you own. No dependency on a service that can change its pricing tomorrow.
Data sovereignity
Every inference call, every training run, every fine-tune checkpoint processed and stored on hardware inside your network perimeter.
Your model weights don't touch a third-party GPU. Your training data doesn't transit a cloud region. Your prompts aren't logged by a provider whose retention policy you don't control.
No data processor agreements. No third-party sub-processors. No exposure.
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Data agents
Production-grade data intelligence at scale: complex pipelines, real-time insight, and automated reporting running on hardware you own.
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Employee agents
A 120B model trained on everything your organisation knows, serving your entire team in parallel, at quality that replaces the frontier APIs you're currently paying for.
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Security agents
A production model running end-to-end threat detection, response, and resilience monitoring, entirely air-gapped, entirely in your control.
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Customer agents
A production inference endpoint handling customer requests at scale, surfacing trends in real time, with no external API in your critical path.
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Development agents
A fully fine-tuned 70B model that knows your entire stack, your conventions, and your standards — generation, review, and documentation at production speed.
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Creative agents
A production creative pipeline — text, image, and multimodal generation, running entirely on your infrastructure, at the scale and speed your team demands.
When AI is in your product. It changes the unit economics.
Frontier is the workstation that moves AI from operating expense to capital asset. For teams shipping AI features inside a product, the difference compounds with every customer.
|
Typical Frontier operator
A small AI product team, or an in-house ML platform group, serving inference into a product, fine-tuning models, running R&D. Currently renting cloud GPUs and paying API spend on top.
|
|
|---|---|
| Production inference on cloud 2x H100-equivalent, 24/7 | 32,900 / year |
| API spend for non-production work Team usage of Claude / GPT | £24,000 / year |
| Cloud GPU for fine-tuning runs ~400 hours / month | £9,100 / year |
| Total annual spend Frontier displaces | £66,000 / year |
Frontier payback in this scenario: ~7 months.
For teams running heavy 24/7 production inference, payback can be as short as 5 months. After that, the cost of every inference call your product makes drops to electricity — and you own the infrastructure outright.
Yours alone
Most AI work happens on borrowed infrastructure. Every prompt leaves the building, and every experiment has a cost attached.
Frontier is built for the point where that stops making sense.
Your models run locally, privately, on hardware you own. No dependency on a service that can change its pricing tomorrow.
Deliberate throughout
The NVIDIA RTX PRO 6000 Blackwell Max-Q delivers a massive 1.79 TB/s of memory bandwidth to the GPU. But a bottleneck anywhere else in the system costs you inference performance just as surely—CPU memory bandwidth starving the data pipeline, NVMe throughput limiting model load times, or system RAM constraining batch size.
Every component in Frontier was specified against the same workload: sustained, concurrent, 70B-class inference. From the 64-core Threadripper 9980X and 256GB of ECC RDIMM to the PCIe 5.0 throughput of the Samsung 9100 PRO drives, nothing in the system is the weak link.
Graphics card RTX Pro 6000 Blackwell
Speed 1.8 TB/s of memory bandwidth
Memory 256GB of DDR5-6400 ECC
Processor Threadripper PRO 9995WX
Storage Dual model and OS drives
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Errors caught before they reach your model
Error-correcting memory built for model training that can't afford to fail.
Silent memory errors aren't caught by consumer hardware, and can invalidate a result without warning. You won't know until it's too late.
Error-correcting memory detects and corrects single-bit errors in real time. Every byte that passes through is checked, and every error is fixed. Automatically. In real time.
Space reserved for your models
Your models and your system each get a dedicated drive. Fast storage where it matters, headroom where you need it, and nothing competing for bandwidth.
OS drive
Keeps the system fast. The Samsung 9100 Pro 2TB means applications load instantly and pipelines initialise without delay — nothing stealing bandwidth from your models.
Model drive
A dedicated RAID-0 array across two Samsung 9100 Pro 8TB drives for your models, datasets, and checkpoints. A 70B model at full precision occupies around 140GB. Room for a production library, with headroom to grow.
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Supporting your configuration
Choosing the right AI infrastructure is a technical decision. Our team understands the workloads, the models, and the tradeoffs, and can help you get from first question to running inference, without the guesswork.
There when you need it
When hardware is part of your production stack, downtime has a number attached to it.
Hand-built and manually tested
Every Frontier is burned in and benchmarked by our engineers before it leaves us. It arrives ready to get to work.
Not sure where to start?
Speak to us before you configure. No obligation - just a conversation about whether the Frontier is the right tool for what you're building.
Configuration support service
Getting a workstation running is one thing. Getting it running the right models, configured for your team's workflows, with inference serving that's ready for production is another.
Our setup service covers the full stack. You tell us what you need to run. We make sure it runs.
?Hardware commissioning
Software environment
Model selection
Model deployment
Testing and benchmarking
Find the right machine for your team
Three machines, one architecture. Node for the individual operator who needs serious local inference. Nexus for the team that needs shared infrastructure at scale. Frontier for the team shipping AI into production.
The right one depends on the models you need to run, the concurrency you need to support, and the workloads you can't afford to send to the cloud.
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£8,499.99
From £215.69 per month
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£20,999.99
From £382.28 per month
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Synapse Frontier AI Workstation
£39,999.99
Specifications
Chillblast Synapse Frontier AI Workstation
Processor (CPU)
- AMD Ryzen Threadripper PRO 9995WX
- 96 Cores | 192 Threads
- Base Frequency: 2.5 GHz
- Boost Frequency: 5.4 GHz
CPU Cooler
- 360mm AIO Liquid Cooler
- Silverstone XE360-TR5
- 3 x 120mm Fan(s)
Motherboard
- AMD WRX90 Chipset
Network
- Ethernet Up to 10Gbps
Graphics
- NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
- 96GB VRAM
Memory (RAM)
- 256GB DDR5 5600MT/s
- 16 x 16GB Modules
Case
- Fractal Define 7 XL
- Black
- Solid Side Panel
Physical Dimensions
- Width: 240mm
- Height: 604mm
- Depth: 566mm
Front Ports
- 1 x USB 3.1 Type-C
- 2 x USB 3.0
- 2 x USB 2.0
- 1 x 3.5mm Jack - Headphone
- 1 x 3.5mm Jack - Microphone
Operating System
- Microsoft Windows 11 Home
Power Supply
- Seasonic PRIME PX ATX 3.1
- 2200W
- 80 Plus Platinum
Warranty
- 5 Years Includes:
- 3 Years On Site
- 2 Years Labour
- UK Mainland*
Storage
- 18TB Samsung 9100 PRO
- PCIe 5.0 x4 NVMe
- Solid State Drive (SSD)
Rear Ports
- 2 x USB-C 4
- 6 x USB 3.1
- 1 x USB 2.0
- 1 x 3.5mm Jack - Line Out
- 3 x RJ-45 Ethernet
Solid State Storage (SSD)
- 2x Samsung 9100 PRO
- PCIe 5.0 x4 NVMe + PCIe 5.0 x4 NVMe
Stock Code
- CB-AI-003
Industry-leading 5 year warranty
We’re proud of how much customers love and trust us, and that’s why your PC is protected by an industry-leading 5 year warranty. So just in-case anything goes wrong, we’ve got you covered.
The first 3 years warranty covers parts and labour – we’ll collect your system, repair it and replace any parts as necessary, and return it to you free of charge. The final 2 years covers labour costs on a return to base basis.
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