Term · Topic

FP8 Precision Inference (FP8)

Q: What is FP8 Precision Inference?

FP8 Precision Inference (FP8) is a Neural Network (NN) inference approach that uses 8-bit floating-point number formats to execute trained models with lower memory and compute requirements while maintaining model accuracy within tolerances established during quantization and calibration. Expanded Explanation 1. Technical Function and Core Characteristics FP8 uses 8-bit floating-point data types, such as E4M3 and E5M2, for weights, activations, or both during NN inference. These formats allocate

FP8 precision inference is the use of 8-bit floating-point formats to run trained neural networks, enabling higher throughput and lower memory usage in enterprise AI deployments while maintaining accuracy within validated tolerances for large models and latency-sensitive workloads.

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curl -X POST https://mcp.decisioninsights.ai/api/mcp-public \
  -H "content-type: application/json" \
  -H "accept: application/json, text/event-stream" \
  -d '{"id":1,"jsonrpc":"2.0","method":"tools/call","params":{"arguments":{"slug":"fp8-precision-inference-fp8"},"name":"di_get_term"}}'

REST

GET https://api.decisioninsights.ai/api/public/v1/glossary/e0c0ccf0-1626-442a-9f30-f112335dd8f2

CLI

di get-glossary --slug fp8-precision-inference-fp8

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What the record lets an agent check before it uses the term in an answer.

The check	What the record shows	Where it is in the data
It's a known term	One entry, with its abbreviation and type (topic)	`name, alternateName`
It sits in a glossary	Linked to FP8 Precision, Precision Scaling, Mixed Precision Training, Bfloat16 Format	`inDefinedTermSet`

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