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LLM inference optimization: Tutorial & Best Practices

launchdarkly.com · published 7 July 2025

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https://launchdarkly.com/solutions/optimize-ai-performance/

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https://www.llama.com/

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https://ai.google.dev/gemma

ai.google.dev

https://www.deepseek.com/en

deepseek.com

https://docs.mistral.ai/deployment/self-deployment/overview/

docs.mistral.ai

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https://arxiv.org/abs/1706.03762

arxiv.org

https://github.com/vllm-project/vllm

github.com

https://github.com/triton-inference-server/server

github.com

https://huggingface.co/docs/text-generation-inference/en/index

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https://docs.vllm.ai/en/latest/serving/distributed_serving.html

docs.vllm.ai

https://arxiv.org/abs/1607.06450

arxiv.org

https://d2l.ai/chapter_multilayer-perceptrons/dropout.html

d2l.ai

https://github.com/deepspeedai/DeepSpeed

github.com

https://github.com/deepspeedai/Megatron-DeepSpeed/tree/main/examples_deepspeed/sequence_parallel

github.com

https://huggingface.co/RedHatAI/Sparse-Llama-3.1-8B-2of4

huggingface.co

https://www.patronus.ai/llm-testing

patronus.ai

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https://launchdarkly.com/docs/guides/metrics/launchdarkly-metrics

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https://launchdarkly.com/docs/home/ai-configs

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