Running 1M-token context on a single GPU (the math)
📰 Dev.to · João André Gomes Marques
Learn how to run 1M-token context on a single GPU by understanding the math behind it, not just relying on hardware upgrades.
Action Steps
- Calculate the memory requirements for your LLM using the formula: memory = tokens * embedding_size * hidden_size
- Determine the optimal batch size for your model based on the available GPU memory
- Configure your GPU to use the optimal batch size and sequence length
- Implement model parallelism to split the model across multiple GPUs if necessary
- Test and evaluate the performance of your LLM on the single GPU
Who Needs to Know This
Data scientists and AI engineers working with large language models (LLMs) can benefit from this knowledge to optimize their infrastructure and improve model performance.
Key Insight
💡 Understanding the mathematical requirements of LLMs can help optimize infrastructure and improve model performance.
Share This
🤖 Run 1M-token context on a single GPU? It's a math problem, not a hardware one! 📊
Key Takeaways
Learn how to run 1M-token context on a single GPU by understanding the math behind it, not just relying on hardware upgrades.
Full Article
Title: Running 1M-token context on a single GPU (the math)
URL Source: https://dev.to/jagmarques/running-1m-token-context-on-a-single-gpu-the-math-odd
Published Time: 2026-04-07T18:22:50Z
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[João André Gomes Marques](https://dev.to/jagmarques)
Posted on Apr 7 • Edited on May 4 • Originally published at [dev.to](https://dev.to/jagmarques/running-1m-token-context-on-a-single-gpu-the-math-odd)
# Running 1M-token context on a single GPU (the math)
[#ai](https://dev.to/t/ai)[#gpu](https://dev.to/t/gpu)[#llm](https://dev.to/t/llm)[#infrastructure](https://dev.to/t/infrastructure)
Most people dismiss million-token context windows as a hardware problem. It is not. It is a math problem - and the math has a solution.
##
URL Source: https://dev.to/jagmarques/running-1m-token-context-on-a-single-gpu-the-math-odd
Published Time: 2026-04-07T18:22:50Z
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[](https://dev.to/jagmarques)
[João André Gomes Marques](https://dev.to/jagmarques)
Posted on Apr 7 • Edited on May 4 • Originally published at [dev.to](https://dev.to/jagmarques/running-1m-token-context-on-a-single-gpu-the-math-odd)
# Running 1M-token context on a single GPU (the math)
[#ai](https://dev.to/t/ai)[#gpu](https://dev.to/t/gpu)[#llm](https://dev.to/t/llm)[#infrastructure](https://dev.to/t/infrastructure)
Most people dismiss million-token context windows as a hardware problem. It is not. It is a math problem - and the math has a solution.
##
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