The Biggest Molecular Dynamics Hardware Comparison: 5090 vs Pro 6000 vs H100/H200
Last week, a lab manager from a major research institute contacted and he wanted to upgrade his lab's infrastructure. The team relied on a server from 2019 equipped with four Quadro RTX 5000 GPUs.
His question was: "We see the reports on the RTX 5090. Can a consumer card replace our enterprise server and deliver real performance gains?"
We decided to verify this with data by testing his specific workload, standard AMBER and GROMACS trajectories and benchmarked his existing setup against our new test bench.
The results, You will get to know in this blog.
This guide details those findings. It compares the latest RTX 5090, the workstation-class RTX Pro 6000, and the data center H100/H200, helping you identify the right tools for your lab.
GPU Resident Computing
Molecular Dynamics has now evolved. Modern software like NAMD 3.0, AMBER 24, and OpenMM now runs as "GPU-Resident" code.
The entire simulation lives on the graphics card. The GPU acts as the primary engine, while the CPU handles data coordination.
This shift highlights an important detail about hardware, that Clock speed drives performance.
Consumer cards like the NVIDIA RTX 5090 operate at high clock speeds (~2.9 GHz). Enterprise cards like the H100 prioritize massive parallelization and stability at lower clocks (~1.7 GHz). For standard biological systems (proteins, ligands, small membranes), the high clock speed of the 5090 delivers exceptional raw speed.
Real-World Performance
We tested these cards using AMBER 24 on the industry-standard STMV (Satellite Tobacco Mosaic Virus) benchmark (~1 million atoms).
1. Single GPU Performance (Raw Speed)
Metric: Speed in nanoseconds per day (ns/day), (Note- Your benchmarks may vary depending on Configuration and other factors).
| GPU Model | Architecture | Speed (ns/day) | Relative Performance |
|---|---|---|---|
| NVIDIA H200 | Hopper (Server) | 135.03 ns/day | 6.75x |
| RTX Pro 6000 | Blackwell (Pro) | 121.56 ns/day | 6.1x |
| NVIDIA RTX 5090 | Blackwell (Consumer) | 110.03 ns/day | 5.5x |
| NVIDIA H100 | Hopper (Server) | ~90 ns/day | 4.5x |
| RTX 6000 Ada | Ada Lovelace (Pro) | 71.50 ns/day | 3.5x |
| Quadro RTX 5000 | Turing (Old Lab Server) | ~20 ns/day | 1.0x |
The old RTX 5000 produced 20 nanoseconds a day. A single RTX 5090 delivers 110 ns/day. A single new card, performing the work of five previous-generation cards.
2. The Value Proposition of H200 vs. 4x RTX 5090
The market price of a single NVIDIA H200 card often exceeds the cost of a complete Pro Maestro GQ server equipped with FOUR RTX 5090s.
The Throughput Comparison (GROMACS/AMBER Ensemble):
- 1x H200 Server: 135.03 ns/day total throughput.
- 4x RTX 5090 Server: ~440 ns/day total throughput.
For labs focused on drug discovery or screening many independent candidates, the 4x 5090 system delivers over 3x the performance for the same (or lower) investment.
The Right Tool for your Workload
Each card serves a specific scientific purpose.
1. The Role of H100 and H200
These cards excel at "Big Science."
- Memory Capacity: Massive systems, such as viral capsids or whole-cell organelles (>10 million atoms), require vast memory. The H200 (141GB) and H100 (80GB) accommodate these datasets comfortably.
- Bandwidth: The H200 offers 4.8 TB/s of bandwidth, ensuring smooth data flow for large simulations.
- Scalability: For tasks requiring 8 GPUs working as a single unit (MPI), the H100/H200 utilizes NVLink for instant communication.
2. The Role of RTX 5090 and Pro 6000
These cards excel at "Fast Science."
- Standard Systems: For research on proteins and ligands (<1 million atoms), the RTX 5090 offers the most efficient performance.
- Ensemble Computing: Labs running hundreds of replicas to determine binding affinity benefit from a dense array of fast cards.
Hardware Recommendations from The ProX Lineup
We structured our machines to address specific lab requirements.
1. The Desk-Side PC / Workstation:
Best for: Individual Researchers & PhD Students
- Specs: Single RTX 5090 32GB / Pro6000 96GB | Core Ultra / Ryzen 9000.
- Advantage: This single tower outperforms older 4-GPU nodes. It sits quietly under a desk and provides students with immediate, 24/7 access to high-performance computing.
2. The High-Throughput Server:
Pro Maestro GQ (4x 5090) (4x Pro 6000 or H200)
Best for: Drug Discovery & Screening
- Specs: 4x RTX 5090 / H100 / Pro6000 / H200| Dual Xeon / EPYC
- Advantage: This system maximizes value. It delivers ~440 ns/day of aggregate throughput in a 4U rack mount, offering a powerful upgrade for aging clusters.
3. The Big Memory Station:
Pro Maestro GE (8x 5090 / Pro6000) 
Pro Maestro GD (10x Pro6000 / H100 / H200) 
Best for: Super Large Workloads.
- Advantage: This option bridges the gap between workstation and server. It offers a massive VRAM frame buffer, allowing for large simulations without the need for a full data center infrastructure.
Final Verdict
Consider the future for our Client. By upgrading his aging rack of RTX 5000s to a single Pro Maestro GQ (4x RTX 5090), he transforms the lab's operational density.
He consolidates his hardware footprint, reclaims valuable server rack space, and boosts the lab's simulation throughput by over 400%.
Validate Your Hardware Choice
Send us your specific workloads and we can recommend right solution for you.
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