NVIDIA RTX 4090

Consumer GPU N DevOps & Hardware

Basic Information

Product Description

The NVIDIA GeForce RTX 4090 is a flagship consumer-grade graphics card based on the Ada Lovelace architecture, featuring 24GB of GDDR6X memory and 16,384 CUDA cores. As of 2025, it remains the most popular consumer GPU choice for local LLM inference, benefiting from over two years of driver optimizations and community tool development. Its mature ecosystem and excellent cost-performance ratio make it the preferred choice for developers running local LLMs to provide inference services for OpenClaw.

Core Features/Characteristics

  • 16,384 CUDA cores + 512 Tensor Cores
  • 24GB GDDR6X memory (384-bit bus)
  • Approximately 1 TB/s memory bandwidth
  • 82.6 TFLOPS FP32 compute power
  • Ada Lovelace architecture
  • Supports full AI inference stack including CUDA, TensorRT, etc.
  • 450W TDP

Price

  • New retail price: $1,500-$1,800
  • Used/refurbished price: $1,100-$1,400

LLM Inference Performance

  • 8B parameter model: 128 tokens/s
  • Smoothly runs 7B-13B parameter models
  • Can run some 30B+ models with quantization
  • Over two years of driver and inference library optimizations, with mature quantization strategies on the Ada Lovelace architecture

Target Users

  • Individual developers for local LLM inference
  • OpenClaw deployments requiring GPU acceleration
  • Small teams for AI prototype development
  • Multi-purpose users for both gaming and AI development

Competitive Advantages

  • Most mature AI inference ecosystem among consumer GPUs
  • Two years of community accumulation, with extremely rich tutorials and tools
  • Better cost-performance ratio compared to RTX 5090 (considering actual purchase price)
  • 24GB memory sufficient for most development and prototyping scenarios
  • Wide range of third-party board options

Relationship with OpenClaw Ecosystem

The RTX 4090 is the most popular consumer GPU for building local LLM inference engines for OpenClaw. Paired with inference frameworks like Ollama and vLLM, it can provide fast model inference services locally for OpenClaw. The 24GB memory allows running 7B-13B parameter open-source LLMs, enabling fully localized OpenClaw deployments to ensure privacy and security.

Sources

External References

Learn more from these authoritative sources: