AINewsnow

Same effective batch does not mean same training time with gradient accumulation, tested on LoRA on T4 and L4

This story is from 2026-08-19. It is preserved in the archive; the latest stories are on the live feed.

I had assumed 1 × 4 , 2 × 2 and 4 × 1 will take somewhat similar time because effective batch is 4 in all cases. They did not. I ran Qwen3-1.7B with TRL and LoRA for 100 optimizer updates. GPU 1 × 4 2 × 2 4 × 1 T4 287.6s 258.8s 238.2s L4 213.02s 119.47s 124.76s Model, data, sequence length, precisi…

Read the full story at r/deeplearning ↗

Timeline · 1 report

  1. 2026-08-19 21:13 · r/deeplearning
    Same effective batch does not mean same training time with gradient accumulation, tested on LoRA on T4 and L4

More stories

  1. Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
  2. Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
  3. Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
  4. Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
  5. Alibaba ships Qwen3.8-Omni-Flash to watch, listen and call tools — r/LocalLLM
  6. NVIDIA CEO Jensen Huang rejects ‘AI will end the world’ claim, yet cautions ‘we should go as fast as we can but...’ — Mint AI
  7. Meet the Data Agent in ChatGPT Work — OpenAI YouTube
  8. Qwen Image 2.1 PR to ComfyUI — r/StableDiffusion

Get the daily brief of stories like this at 6:30 every morning →