RTX 5080VSNVIDIA H100
AI Benchmark Battle 2026
RTX 5080
Blackwell16GB
$999-1100
Konsumen
High-End
NVIDIA H100
Hopper80GB
$25,000-30000
Enterprise
Data Center
Level Concurrency Berbeda
NVIDIA H100 diuji pada 128 concurrent requests (beban datacenter), sementara RTX 5080 diuji pada 16 concurrent requests (beban workstation). Concurrency tinggi menunjukkan kapasitas throughput tetapi mungkin tidak mencerminkan latensi pengguna tunggal.
LLM Inference
| Model | RTX 5080 | NVIDIA H100 | Pemenang |
|---|---|---|---|
Typhoon2.5-Qwen3-4BLebih tinggi lebih baik | 1,013tok/s | 9,931tok/s | NVIDIA H100 |
GPT-OSS-20BLebih tinggi lebih baik | Tidak Dapat Dijalankan | 8,553tok/s | NVIDIA H100 |
Qwen3-4B-Instruct-FP8Lebih tinggi lebih baik | N/A | N/A | N/A |
Vision-Language
| Model | RTX 5080 | NVIDIA H100 | Pemenang |
|---|---|---|---|
Qwen3-VL-4BLebih tinggi lebih baik | 895tok/s | 7,790tok/s | NVIDIA H100 |
Qwen3-VL-8BLebih tinggi lebih baik | 403tok/s | 7,035tok/s | NVIDIA H100 |
Typhoon-OCR-3BLebih tinggi lebih baik | 394tok/s | 14,019tok/s | NVIDIA H100 |
Image Generation
| Model | RTX 5080 | NVIDIA H100 | Pemenang |
|---|---|---|---|
Qwen-ImageLebih rendah lebih baik | 106.00sec | 28.00sec | NVIDIA H100 |
Qwen-Image-EditLebih rendah lebih baik | 114.00sec | 29.00sec | NVIDIA H100 |
Video Generation
| Model | RTX 5080 | NVIDIA H100 | Pemenang |
|---|---|---|---|
Wan2.2-5BLebih rendah lebih baik | 712.00sec | 180.00sec | NVIDIA H100 |
Wan2.2-14BLebih rendah lebih baik | 2067.00sec | 404.00sec | NVIDIA H100 |
Speech-to-Text
| Model | RTX 5080 | NVIDIA H100 | Pemenang |
|---|---|---|---|
Typhoon-ASRLebih tinggi lebih baik | 0.344xx realtime | 0.392xx realtime | NVIDIA H100 |
Analisis Pemenang
Analisis mendalam mengapa setiap GPU berkinerja berbeda berdasarkan spesifikasi teknis
Ringkasan Analisis Teknis
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.
Perbedaan Utama
- RTX 5080 uses Blackwell architecture while NVIDIA H100 uses Hopper
- NVIDIA H100's HBM3 memory provides exceptional bandwidth for AI workloads
- RTX 5080 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 960GB/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.
Spesifikasi Teknis
RTX 5080
NVIDIA H100
Pemenang Keseluruhan
NVIDIA H100
10 menang dari 10 benchmarks
0
RTX 5080
10
NVIDIA H100
RTX 5080 Keunggulan
- Significantly lower cost
- Easier availability
NVIDIA H100 Keunggulan
- More VRAM (80GB vs 16GB)
- Strong in LLM Inference
- Dominates in Vision-Language
- Dominates in Image Generation
Frequently Asked Questions
NVIDIA H100 outperforms RTX 5080 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 5080 has 16GB of GDDR7 memory with 960 GB/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 5080's 960 GB/s.
RTX 5080 has a TDP of 360W while NVIDIA H100 has a TDP of 700W. RTX 5080 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 5080 is priced around $999-1100 (consumer market), while NVIDIA H100 costs approximately $25,000-30000 (enterprise/datacenter). Note that RTX 5080 is a consumer GPU while NVIDIA H100 is an enterprise solution with different support and warranty terms.