Know more about Nvidia RTX5090

🚀 What is the NVIDIA RTX 5090?

Launched in January 2025, the GeForce RTX 5090 is part of NVIDIA’s Blackwell architecture, a successor to Ada Lovelace. Designed originally for ultra-performance gaming, RTX 5090 is now drawing attention from the AI and ML community thanks to its incredible memory bandwidth, compute throughput, and AI-optimized tensor cores.

🚀 What is the main difference between NVIDIA RTX4090 and RTX 5090?

The main difference between the NVIDIA RTX 4090 and RTX 5090 lies in their architecture, performance, memory, and AI capabilities — with the RTX 5090 offering substantial upgrades across the board.

🧠 Architecture

Feature	RTX 4090	RTX 5090
Architecture	Ada Lovelace (2022)	Blackwell (2025)
Process Node	TSMC 4N	TSMC 4N (optimized, denser)
Tensor Cores	4th Gen	5th Gen (FP8 capable)
RT Cores	3rd Gen	4th Gen (faster, improved path tracing)

⚙️ Performance & Hardware Specs

Spec	RTX 4090	RTX 5090
CUDA Cores	16,384	~24,576 (≈50% more)
VRAM	24GB GDDR6X	32GB GDDR7
Memory Bandwidth	1,008 GB/s	1,532 GB/s (50% increase)
Bus Width	384-bit	512-bit
Boost Clock	~2.52 GHz	~2.9–3.0 GHz
TDP	450W	~450–520W

🔬 AI & LLM Capabilities

Feature	RTX 4090	RTX 5090
FP8 support	❌ No	✅ Yes (critical for LLMs)
FP16 / BF16 performance	~82 TFLOPS	~190 TFLOPS (est.)
LLM training (e.g. 7B)	Possible (with tuning)	Faster, more stable
LLM inference (e.g. 13B)	OK (with quantization)	Handles smoothly with more VRAM

🏁 Summary: Key Upgrades in RTX 5090

✅ +50% more CUDA cores

✅ +33% more VRAM (32GB vs 24GB)

✅ FP8 support for faster LLM/AI inference

✅ Much faster memory (GDDR7 vs GDDR6X)

✅ Improved RT + DLSS 4 for next-gen games

✅ Better suited for AI training + deployment