# RTX 5090 Capabilities — Deep Dive Guides

> What you can do with the Razer Blade 18's RTX 5090 (24 GB GDDR7) that you can't (or can't do well) on the Mac.

Each guide covers: **what it is → how to use it → real-world use cases → benefits → skills you'll learn.**

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## Guides

| #                                       | Capability                        | Key Benefit                          | Skill Level  |
| --------------------------------------- | --------------------------------- | ------------------------------------ | ------------ |
| [01](01-gpu-inference-speed.md)         | **GPU Inference Speed**           | 2–4× faster LLM responses            | Beginner     |
| [02](02-whisper-batch-transcription.md) | **Whisper Batch Transcription**   | Hours of audio in minutes            | Beginner     |
| [03](03-tts-generation-at-scale.md)     | **TTS Generation at Scale**       | Faster-than-realtime voice synthesis | Beginner     |
| [04](04-fine-tuning-training.md)        | **Fine-Tuning / Training**        | Customize models on your own data    | Intermediate |
| [05](05-cuda-tensorrt-ml-research.md)   | **CUDA / TensorRT / ML Research** | Full NVIDIA ML toolchain             | Intermediate |
| [06](06-stable-diffusion-image-gen.md)  | **Stable Diffusion / Image Gen**  | 5–8s per image, unlimited free       | Beginner     |
| [07](07-multi-gpu-workloads.md)         | **Multi-GPU Workloads (Future)**  | Scaling path to production           | Advanced     |

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## Suggested Learning Order

```
Week 1:  01 (Inference) → 02 (Whisper) → 03 (TTS)
         Get familiar with the GPU, benchmark your models

Week 2:  06 (Stable Diffusion)
         Set up ComfyUI, generate app assets

Week 3:  04 (Fine-Tuning)
         QLoRA your first 7B model on your own code

Week 4:  05 (CUDA / TensorRT)
         Deeper GPU programming, profiling, optimization

Ongoing: 07 (Multi-GPU)
         Reference as you plan scaling
```

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## Prerequisites

All guides assume you've completed the [Windows setup](../setup-guide.md):

- NVIDIA drivers installed (Windows)
- Ollama installed and running (Windows)
- WSL2 Ubuntu 24.04 set up
- Repo cloned, `setup-tts.sh` completed
- Dashboard running at `http://localhost:3000`
