IEEE Std 2941-2021 PDF

Full title and description

IEEE Std 2941-2021 — IEEE Standard for Artificial Intelligence (AI) Model Representation, Compression, Distribution, and Management. This standard defines an AI development interface and an interoperable model representation, including coding and encapsulated formats, intended to support efficient AI model inference, storage, distribution and lifecycle management.

Abstract

IEEE 2941 specifies formats and interfaces for representing AI models in a compact, interoperable way, together with guidance for model compression, encapsulation for distribution, and management practices to support deployment and inference across devices and platforms. The standard aims to reduce friction when sharing, storing, and deploying trained models while enabling efficient inference.

General information

• Status: Active standard (approved by the IEEE Standards Board and listed as active by IEEE).
• Publication date: Published March 18, 2022 (designation 2941-2021; the approval/ballot process completed in late 2021 with board approval in December 2021).
• Publisher: Institute of Electrical and Electronics Engineers (IEEE), IEEE Computer Society / Data Compression Standards Committee work area.
• ICS / categories: Information technology (ICS 35 — IT); relates to coding/representation and data compression / model storage and distribution topics within IT classifications.
• Edition / version: First published edition (designated IEEE Std 2941-2021; published March 18, 2022).
• Number of pages: 226 pages (electronic PDF edition).

Scope

Defines an AI model representation and associated interfaces for interoperable model coding, compression, encapsulation and management to support model inference, storage, distribution and lifecycle operations across platforms and devices. The scope covers model representation formats, compact/encoded model formats, and packaging approaches needed to distribute and manage models efficiently. The working group scope explicitly targets model-level format and distribution problems rather than specifying training algorithms.

Key topics and requirements

• Interoperable model representation: a standard internal representation for AI models to enable portability across tools and runtimes.
• Coding and compression formats: definitions for compact encodings and compression techniques suitable for model storage and fast inference.
• Encapsulated model package: a standardized container/packaging format for model files plus metadata, dependencies, and runtime hints.
• Model metadata and manifests: provisions for describing model inputs/outputs, versioning, provenance, hardware/runtime requirements and licenses.
• Interfaces and APIs (normative or informative): definitions to support integration with operator interfaces and inference engines (see companion parts 2941.1, 2941.2).
• Distribution and management guidance: recommendations for packaging, secure distribution, and lifecycle management to enable reproducible deployment and updates.

Typical use and users

Intended users include ML engineers, data scientists, runtime/inference engine vendors, model hub and repository operators, device and NPU vendors, platform integrators and organizations that distribute or deploy pretrained models at scale. Typical uses are packaging and exchanging trained models, compressing models for embedded or edge deployment, and enabling runtime systems to load and run models from a standardized representation.

Related standards

Companion and related standards from the same working group include IEEE 2941.1 (Operator Interfaces of Artificial Intelligence / 2941.1-2022) and IEEE 2941.2 (APIs for Deep Learning Inference Engines / 2941.2-2023). Other IEEE standards addressing model-based coding and neural-network-related coding practices (for example in image/video coding families) may reference or integrate with 2941 for model packaging and management.

Keywords

AI model representation, model compression, coding format, encapsulated format, model packaging, model distribution, model management, interoperable model format, inference runtime, model metadata.

FAQ

Q: What is this standard?

A: IEEE Std 2941-2021 is a standard that defines interoperable representations, compressed coding formats, and encapsulation/packaging methods for AI models to support efficient inference, storage, distribution and management.

Q: What does it cover?

A: It covers model representation formats, compact model encodings and compression, a packaged/encapsulated model format with metadata, and guidance for distributing and managing models; it is focused on the model artifact and its lifecycle rather than training procedures.

Q: Who typically uses it?

A: ML engineers, data scientists, model repository operators, inference engine and device vendors, and platform integrators who need standardized ways to package, compress, distribute and run pretrained models.

Q: Is it current or superseded?

A: As published, IEEE Std 2941-2021 is listed as an active standard (board approved in December 2021 and published March 18, 2022). Check IEEE or authorized distributors for any later amendments, corrigenda or revisions.

Q: Is it part of a series?

A: Yes — the 2941 family includes companion parts such as 2941.1 (operator interfaces) and 2941.2 (APIs for inference engines). The working group continues to develop related projects around model representation and runtime interoperability.

Q: What are the key keywords?

A: AI model representation, compression, coding format, encapsulation, model distribution, model management, interoperability, inference packaging.