How Context Length Affect LLM Speed - Tested with GPT-OSS-20b - CPU & RTX 5060 Ti (16 GB VRAM) GPU

In this video, you will learn what context length means and why it is important in Local LLMs. I have explained how context length affects LLM speed and performance by testing it on the OpenAI GPT OSS 20B model in Hindi. You will see how different context lengths change response time, accuracy and memory load.

I have shown live examples using both CPU only and RTX 5060 Ti 16 GB VRAM GPU to compare the results. You will also understand how to adjust context length in LM Studio, how long prompts and file inputs impact generation speed, and what hardware gives better performance for local AI models. Watch the full video to understand context length, token limits, prompt size and overall LLM optimisation so you can run local AI tools faster and smoother.

More Videos For You:
GLM 4.7 Flash Local Test: https://youtu.be/EoOZNSbJPXw
Chat GPT-OSS-20b Local LLM Test: https://youtu.be/czaHEkVGjiQ
RTX 5060 Ti AI Test: https://youtu.be/5Qy-xSfF5Vk
LM Studio Tutorial in Hindi: https://youtu.be/0Lm3LF52nyU

#aitechgyan #openaichatgpt #rtx5060ti #llm

Видео How Context Length Affect LLM Speed - Tested with GPT-OSS-20b - CPU & RTX 5060 Ti (16 GB VRAM) GPU канала AI Tech Gyan