RTX 5090VSNVIDIA H100
AI Benchmark Battle 2026
RTX 5090
Blackwell32GB
$1,999-2200
Consumer
Flagship
NVIDIA H100
Hopper80GB
$25,000-30000
Enterprise
Data Center
Different Concurrency Levels
NVIDIA H100 was tested at 128 concurrent requests (datacenter workload), while RTX 5090 was tested at 16 concurrent requests (typical workstation load). Higher concurrency shows throughput capacity but may not reflect single-user latency.
LLM Inference
| Model | RTX 5090 | NVIDIA H100 | Winner |
|---|---|---|---|
Typhoon2.5-Qwen3-4BHigher is better | 1,446tok/s | 9,931tok/s | NVIDIA H100 |
GPT-OSS-20BHigher is better | 1,338tok/s | 8,553tok/s | NVIDIA H100 |
Qwen3-4B-Instruct-FP8Higher is better | N/A | N/A | N/A |
Vision-Language
| Model | RTX 5090 | NVIDIA H100 | Winner |
|---|---|---|---|
Qwen3-VL-4BHigher is better | 1,005tok/s | 7,790tok/s | NVIDIA H100 |
Qwen3-VL-8BHigher is better | 868tok/s | 7,035tok/s | NVIDIA H100 |
Typhoon-OCR-3BHigher is better | 1,577tok/s | 14,019tok/s | NVIDIA H100 |
Image Generation
| Model | RTX 5090 | NVIDIA H100 | Winner |
|---|---|---|---|
Qwen-ImageLower is better | 46.00sec | 28.00sec | NVIDIA H100 |
Qwen-Image-EditLower is better | 50.00sec | 29.00sec | NVIDIA H100 |
Video Generation
| Model | RTX 5090 | NVIDIA H100 | Winner |
|---|---|---|---|
Wan2.2-5BLower is better | 344.00sec | 180.00sec | NVIDIA H100 |
Wan2.2-14BLower is better | 903.00sec | 404.00sec | NVIDIA H100 |
Speech-to-Text
| Model | RTX 5090 | NVIDIA H100 | Winner |
|---|---|---|---|
Typhoon-ASRHigher is better | 0.324xx realtime | 0.392xx realtime | NVIDIA H100 |
Winner Analysis
Deep dive into why each GPU performs differently based on technical specifications
Technical Analysis Summary
NVIDIA H100 wins 10 out of 10 benchmarks, excelling in LLM Inference and Vision-Language. Its HBM3 memory bandwidth provides a decisive advantage for AI inference workloads.
Key Differentiators
- RTX 5090 uses Blackwell architecture while NVIDIA H100 uses Hopper
- NVIDIA H100's HBM3 memory provides exceptional bandwidth for AI workloads
- RTX 5090 offers consumer pricing vs NVIDIA H100's enterprise cost
- NVIDIA H100 has 80GB VRAM for larger models
LLM Inference
NVIDIA H100 wins in LLM inference because NVIDIA H100's superior memory bandwidth (3.4TB/s vs 1.8TB/s) enables faster token generation, and HBM3 memory provides exceptional bandwidth for memory-bound LLM operations.
Vision-Language
NVIDIA H100 excels at vision-language tasks due to higher memory bandwidth accelerates image token processing, and more VRAM (80GB) handles larger image batches efficiently.
Image Generation
NVIDIA H100 leads in image generation because faster memory enables quicker diffusion iterations, and Hopper architecture optimizations accelerate denoising operations.
Video Generation
NVIDIA H100 dominates video generation with significantly more VRAM (80GB) maintains temporal coherence across frames, and 3.4TB/s bandwidth handles high-throughput video data.
Speech-to-Text
NVIDIA H100 excels at speech-to-text because superior memory bandwidth enables faster audio feature processing, and 4th Gen Tensor Cores accelerate attention-based speech recognition.
Technical Specifications
RTX 5090
NVIDIA H100
Overall Winner
NVIDIA H100
10 wins out of 10 benchmarks
0
RTX 5090
10
NVIDIA H100
RTX 5090 Advantages
- Significantly lower cost
- Easier availability
NVIDIA H100 Advantages
- More VRAM (80GB vs 32GB)
- Strong in LLM Inference
- Dominates in Vision-Language
- Dominates in Image Generation
Frequently Asked Questions
NVIDIA H100 outperforms RTX 5090 in 10 out of 10 AI benchmarks. The NVIDIA H100's Hopper architecture features the Transformer Engine with FP8 precision, specifically designed for large language models and transformer-based AI workloads. With 3.4 TB/s memory bandwidth and 80GB HBM3 memory, it delivers superior throughput for AI inference workloads.
RTX 5090 has 32GB of GDDR7 memory with 1.8 TB/s bandwidth. NVIDIA H100 has 80GB of HBM3 memory with 3.4 TB/s bandwidth. NVIDIA H100's HBM3 memory provides exceptional bandwidth for memory-bound AI workloads like LLM inference.
NVIDIA H100 is faster for LLM inference. LLM performance is heavily dependent on memory bandwidth - NVIDIA H100's 3.4 TB/s HBM3 enables faster token generation compared to RTX 5090's 1.8 TB/s.
RTX 5090 has a TDP of 575W while NVIDIA H100 has a TDP of 700W. RTX 5090 is more power efficient, making it suitable for deployments with power constraints. For cloud deployments, consider Float16.cloud where you can access these GPUs without managing power infrastructure.
RTX 5090 is priced around $1,999-2200 (consumer market), while NVIDIA H100 costs approximately $25,000-30000 (enterprise/datacenter). Note that RTX 5090 is a consumer GPU while NVIDIA H100 is an enterprise solution with different support and warranty terms.