Hardware Configuration Matrix
GPU specifications, complete build examples, and constraint-based selection guidance
> GPU_COMPARISON_MATRIX
Key specifications for LLM inference workloads
| GPU MODEL | VRAM | TDP | PRICE RANGE | MAX MODEL (Q4) | INFERENCE SPEED | SCENARIO FIT |
|---|---|---|---|---|---|---|
| RTX 5090 (Blackwell) | 32 GB GDDR7 | 575W | $2,000-$2,500 (est.) | 70B Q8 | ~60-70 tok/s (13B) | Next-gen workstation, High-throughput inference |
| RTX 5080 (Blackwell) | 16 GB GDDR7 | 360W | $1,000-$1,200 (est.) | 34B | ~45-50 tok/s (13B) | Performance/Efficiency balance, Enterprise IT |
| RTX 5070 (Blackwell) | 12 GB GDDR7 | 250W | $600-$750 (est.) | 13B | ~35-40 tok/s (7B) | Budget next-gen, Developer workstations |
| RTX 4090 | 24 GB | 450W | $1,600-$2,000 | 70B | ~40 tok/s (13B) | Enterprise IT, Pharma (validated) |
| RTX 4080 SUPER | 16 GB | 320W | $1,000-$1,200 | 34B | ~35 tok/s (13B) | Enterprise IT, Edge (power constrained) |
| RTX 4070 Ti SUPER | 16 GB | 285W | $800-$900 | 34B | ~30 tok/s (13B) | Budget Enterprise, Edge deployment |
| RTX 4070 | 12 GB | 200W | $550-$650 | 13B | ~25 tok/s (7B) | Entry-level, Developer workstations |
| NVIDIA A6000 | 48 GB | 300W | $4,500-$5,000 | 180B (Q4) | ~30 tok/s (70B) | Manufacturing (A&D), Pharma, Enterprise |
| NVIDIA L40S | 48 GB | 350W | $7,000-$8,000 | 180B (Q4) | ~35 tok/s (70B) | Data center, High-throughput inference |
| NVIDIA H100 PCIe | 80 GB | 350W | $25,000-$30,000 | 405B (Q4) | ~60 tok/s (70B) | Enterprise scale, Multi-model serving |
| NVIDIA Spark | 64 GB HBM3e | 300W | $10,000-$15,000 (est.) | 405B (Q4) | ~45 tok/s (70B) | Workstation AI, Large model inference |
| AMD RX 7900 XTX | 24 GB | 355W | $900-$1,000 | 70B (Q4) | ~25 tok/s (13B)* | Budget alternative (ROCm 6.0+) |
| AMD RX 7900 XT | 20 GB | 315W | $700-$800 | 34B (Q4) | ~22 tok/s (13B)* | Mid-range alternative, Developer workstations |
| AMD RX 7800 XT | 16 GB | 263W | $500-$600 | 34B (Q4) | ~18 tok/s (13B)* | Budget entry, Testing/development |
| AMD RX 6900 XT | 16 GB | 300W | $400-$600 | 34B (Q4) | ~15 tok/s (13B)* | Previous gen, Cost-effective testing |
| AMD MI210 | 64 GB HBM2e | 300W | $5,000-$6,000 | 240B (Q4) | ~28 tok/s (70B)* | Professional workloads, ROCm mature |
| AMD MI250X | 128 GB HBM2e | 560W | $10,000-$12,000 | 405B+ (Q4) | ~40 tok/s (70B)* | Data center, Multi-GPU alternative |
| AMD MI300X | 192 GB HBM3 | 750W | $15,000-$18,000 | 405B+ (Q8) | ~70 tok/s (70B)* | H100 competitor, Massive memory bandwidth |
* AMD performance estimates with ROCm 6.0+. Software compatibility may vary by framework.
> MINI_PC_CPU_INFERENCE
High-RAM mini PCs for edge deployment and CPU-only workloads
| MINI PC MODEL | CPU | MAX RAM | TDP | PRICE RANGE | MAX MODEL (CPU) | INFERENCE SPEED | SCENARIO FIT |
|---|---|---|---|---|---|---|---|
| GMKtec EVO-X2 AI | Ryzen AI Max+ 395 + RX 8060S (40 CU RDNA 3.5) | 128 GB LPDDR5X-8000 | ~80W | $1,800-$2,600 | 70B Q8 | ~20-30 tok/s (13B) | High-performance edge, iGPU inference, 8K displays |
| GMKtec EvoX2 | Ryzen 9 7940HS | 128 GB DDR5 | 65W | $800-$1,200 | 70B Q4 | ~8-12 tok/s (13B) | Edge deployment, Silent operation |
| Minisforum MS-01 | Intel i9-13900H | 96 GB DDR5 | 65W | $700-$1,000 | 34B Q4 | ~6-10 tok/s (13B) | Small office, Homelab |
| Beelink GTR7 Pro | Ryzen 9 7940HS | 64 GB DDR5 | 54W | $600-$800 | 13B Q4 | ~5-8 tok/s (7B) | Budget edge, IoT gateway |
| Intel NUC 13 Extreme | i9-13900K | 64 GB DDR5 + GPU Slot | 125W base | $1,400-$1,800 | 70B Q4 (with GPU) | Varies (GPU-dependent) | Compact + GPU option (RTX 4070 max) |
| Mac Mini M2 Pro | M2 Pro (12-core) | 32 GB Unified | ~50W | $1,300-$1,600 | 13B Q4 | ~15-20 tok/s (7B) | Apple ecosystem, Efficient inference |
| Mac Studio M2 Ultra | M2 Ultra (24-core) | 192 GB Unified | ~100W | $4,000-$5,000 | 70B Q8 | ~25-30 tok/s (13B) | Professional macOS, Silent operation |
| Olares (Upcoming) | TBD (ARM/x86) | Up to 128 GB | ~80W (est.) | TBD | 70B Q4 (est.) | TBD | Personal cloud, Self-hosted AI |
| Framework Mainboard | Intel Ultra 7 / Ryzen 7 | Up to 96 GB DDR5 | ~60W | $500-$1,500 | 34B Q4 | ~8-12 tok/s (13B) | Modular/repairable, Portable AI dev |
CPU inference speeds are 3-6× slower than GPU but viable for latency-tolerant use cases. Apple Silicon unified memory architecture provides better performance than x86 CPU-only. Note: Olares specs are estimates pending official release.
> COMPLETE_BUILD_EXAMPLES
Full system specifications across 5 budget tiers
Component List (High-End)
- System: GMKtec EVO-X2 AI
- CPU: AMD Ryzen AI Max+ 395 (up to 5.1GHz)
- GPU: Radeon RX 8060S iGPU (40 CU, RDNA 3.5, ~RTX 4060-4070 mobile)
- RAM: 128GB LPDDR5X-8000MHz (shared with GPU)
- Storage: 1TB NVMe PCIe 4.0
- Power: ~80W
- I/O: WiFi 7, USB4, 8K display (4 screens), SD 4.0
Budget Option: GMKtec EvoX2 (Ryzen 9 7940HS, $800-$1,200)
Performance & Constraints
Max Model: 70B Q8 (iGPU-accelerated, good throughput for edge)
Use Cases: Edge inference with GPU acceleration, ROCm support, silent operation, 8K visual output
Constraints: Unified memory (GPU shares RAM), single user, lower throughput than discrete GPU
→ Best for: Factory floor, retail POS, remote sites with GPU needs, fanless deployments, space-constrained environments, multi-display setups
Component List
- GPU: RTX 4070 (12GB) or RTX 5070 Blackwell (12GB GDDR7)
- CPU: AMD Ryzen 7 7700X
- RAM: 32GB DDR5-5600
- Storage: 1TB NVMe Gen4
- PSU: 750W 80+ Gold
- Cooling: Air (stock or tower)
AMD Alternative: RX 7800 XT (16GB, ROCm 6.0+, $500-$600)
Performance & Constraints
Max Model: 13B Q4 comfortably
Use Cases: Development, prototyping, small deployments
Constraints: Cannot run 70B models, limited multi-user capacity
→ Best for: Developer workstations, PoC projects, small teams
Component List
- GPU: RTX 4090 (24GB) or RTX 5090 Blackwell (32GB GDDR7)
- CPU: AMD Ryzen 9 7950X
- RAM: 64GB DDR5-6000
- Storage: 2TB NVMe Gen4 + 4TB SATA SSD
- PSU: 1000W 80+ Platinum (1200W for 5090)
- Cooling: AIO 280mm or better
AMD Alternative: RX 7900 XTX (24GB, ROCm 6.0+, $900-$1,000)
Performance & Constraints
Max Model: 70B Q4 (single user)
Use Cases: Small team production, validated environments
Constraints: Limited concurrent users (2-3), no multi-GPU scaling
→ Best for: Enterprise IT pilot, Pharma validation (single workstation)
Component List
- GPU: 2× RTX 4090 (48GB total) OR 1× A6000 (48GB)
- CPU: AMD Threadripper 7960X (24-core)
- RAM: 128GB DDR5-5200 ECC
- Storage: 4TB NVMe Gen4 (RAID 1) + 8TB SATA
- PSU: 1600W 80+ Titanium (dual GPU) or 1000W (A6000)
- Cooling: Custom loop or AIO 360mm
Performance & Constraints
Max Model: 180B Q4 (A6000) or 70B Q8 (dual 4090)
Use Cases: Multi-user production, GxP environments
Constraints: Single server (no redundancy), 5-10 concurrent users max
→ Best for: Manufacturing (A&D), Pharma production, Small enterprise deployment
Component List
- GPU: 2× A6000 (96GB total) OR 4× L40S (192GB)
- CPU: Dual Intel Xeon Gold 6458Q (64-core total)
- RAM: 512GB DDR5 ECC Registered
- Storage: 8TB NVMe Gen4 (RAID 10) + 20TB SATA RAID
- PSU: Redundant 2000W 80+ Titanium
- Chassis: 4U rackmount with redundant cooling
Performance & Constraints
Max Model: 405B Q4 OR multiple 70B instances
Use Cases: Department-scale production, multi-model serving
Constraints: Single rack unit (no geo-redundancy), cooling requirements
→ Best for: Mid-size enterprise, Multi-department deployment, High-availability needs
Component List
- GPU: 4× H100 PCIe (320GB) OR 8× L40S (384GB) OR 5× Spark (320GB) OR 2× MI300X (384GB)
- CPU: Dual AMD EPYC 9554 (128-core total)
- RAM: 1.5TB DDR5 ECC Registered
- Storage: 20TB NVMe Gen5 (RAID 10) + 100TB object storage
- Networking: Dual 100GbE RDMA
- Infrastructure: Redundant PSU, hot-swap components, KVM
Note: NVIDIA Spark and AMD MI300X offer competitive price/performance to H100 tier
Performance & Constraints
Max Model: Multiple 405B instances, tensor parallelism capable
Use Cases: Organization-wide production, multi-tenant
Constraints: Requires data center facilities, cooling (15-20kW), ops team
→ Best for: Large enterprise, Multi-site deployment, Regulated industries with scale
Constraint-based selection guidance: Not recommendations, but constraint implications.
Budget Constraint
If budget < $1.5K: Mini PC tier (Framework, GMKtec, Beelink). CPU-only inference (slow). Edge deployments only.
If budget < $3K: Entry tier GPU build (RTX 4070/5070, RX 7800 XT). Cannot run 70B models. Multi-user not viable.
If budget $3K-$10K: Mid-range viable (RTX 4090/5090, RX 7900 XTX). Single 70B possible. Limited concurrency (2-5 users).
If budget $10K-$40K: Professional tier (A6000, L40S, Spark, MI210/250X). Multi-GPU or pro cards. Production-ready (5-15 users).
If budget > $40K: Enterprise/Data Center (H100, MI300X, multi-GPU). Scaling, redundancy, multi-model serving feasible.
Deployment Environment Constraint
If edge/remote site: Mini PC preferred (GMKtec EVO-X2 AI, Olares, Framework). Low power (60-80W), fanless, compact.
If factory floor/POS: Mini PC or ruggedized workstation. Noise/dust concerns. Consider Intel NUC with GPU slot for hybrid needs.
If office/lab: GPU workstation viable (Blackwell/RDNA 3 generation). Cooling and power available.
If data center: Rack-mount enterprise tier (H100, Spark, MI300X). Redundancy and cooling infrastructure present.
If mobile/vehicle: Mini PC only (Framework for modularity). Power and thermal constraints critical.
Model Size Constraint
If 7B-13B models sufficient: Entry tier viable (12GB VRAM min).
If 34B-70B required: Mid-range minimum (24GB VRAM), Professional preferred.
If 70B+ Q8 or 180B+ Q4: Professional tier minimum (48GB+ VRAM).
If 405B models: Enterprise tier (80GB+ VRAM per GPU, multi-GPU likely).
Concurrency Constraint
If 1-2 concurrent users: Entry tier sufficient.
If 3-5 concurrent users: Mid-range minimum. Queue management required.
If 5-15 concurrent users: Professional tier. Multiple model instances or larger VRAM.
If 15+ concurrent users: Enterprise tier. Load balancing, multi-server likely needed.
Validation/Regulatory Constraint
If FDA 21 CFR Part 11 required: Professional tier minimum. ECC RAM required. Redundancy preferred.
If ITAR/EAR/CUI: Professional or Enterprise. Air-gap capability. Audit logging critical.
If general enterprise (non-regulated): Any tier based on other constraints.
If development/testing only: Entry tier acceptable. Validation not required.