Papers › GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

20 Dec 2021arXiv:2112.10741archive 2025-07-28

Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen

Diffusion models have recently been shown to generate high-quality synthetic images, especially when paired with a guidance technique to trade off diversity for fidelity. We explore diffusion models for the problem of text-conditional image synthesis and compare two different guidance strategies: CLIP guidance and classifier-free guidance. We find that the latter is preferred by human evaluators for both photorealism and caption similarity, and often produces photorealistic samples. Samples from a 3.5 billion parameter text-conditional diffusion model using classifier-free guidance are favored by human evaluators to those from DALL-E, even when the latter uses expensive CLIP reranking. Additionally, we find that our models can be fine-tuned to perform image inpainting, enabling powerful text-driven image editing. We train a smaller model on a filtered dataset and release the code and weights at https://github.com/openai/glide-text2im.

PaperPDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2112.10741")

Code

Syntology Ran 9 of 15 code samples harvested from 1 repository linked to this paper; 6 have no recorded run. Of those that ran: 1 ran · our draft was wrong; 8 ran with no contract checked.

By repository: official repository: 15 samples from 1 repository, 9 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

openai/glide-text2im officialmentioned in papermentioned on GitHubpytorch report
ermongroup/SDEdit mentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

15 samples harvested; 9 ran; 0 honoured the contract we drafted; 6 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · our draft was wrong
8ran
6unverified

Licence: 0 of the 15 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from openai/glide-text2im. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

GroupNorm32 openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · metamorphic tier: deterministic fingerprinted MIT (permissive) · afad4c14b97816a5 · report
LayerNorm openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · metamorphic tier: deterministic fingerprinted MIT (permissive) · b4ca43deda023234 · report
MLP openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · metamorphic tier: deterministic fingerprinted MIT (permissive) · 1df304371337469d · report
MultiheadAttention openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · metamorphic tier: deterministic MIT (permissive) · 001daee6f2379723 · report
QKVAttention openai/glide-text2im/glide_text2im/text2im_model.py official repository ran MIT (permissive) · 84ffe49eed5f64f8 · report
QKVMultiheadAttention openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · metamorphic tier: deterministic MIT (permissive) · be1f454b2f7a88fc · report
ResidualAttentionBlock openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · metamorphic tier: deterministic MIT (permissive) · 240a712d20a01f00 · report
Transformer openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · metamorphic tier: deterministic MIT (permissive) · d67f9d0e7ed82f5f · report
normalization openai/glide-text2im/glide_text2im/text2im_model.py official repository ran · our draft was wrong MIT (permissive) · c93ddadd4581c6e6 · report
AttentionBlock openai/glide-text2im/glide_text2im/text2im_model.py official repository unverified MIT (permissive) · 267115dc63f308a8 · report
ResBlock openai/glide-text2im/glide_text2im/text2im_model.py official repository unverified MIT (permissive) · 86554561a414fdb7 · report
Text2ImUNet openai/glide-text2im/glide_text2im/text2im_model.py official repository unverified MIT (permissive) · e25a725bbd980bac · report
TimestepEmbedSequential openai/glide-text2im/glide_text2im/text2im_model.py official repository unverified MIT (permissive) · ebfd51a2d88f9da8 · report
UNetModel openai/glide-text2im/glide_text2im/text2im_model.py official repository unverified MIT (permissive) · e28a6df0e478f28e · report
convert_module_to_f16 openai/glide-text2im/glide_text2im/text2im_model.py official repository unverified MIT (permissive) · 503bb7076a4bd667 · report

Tasks

DiversityImage GenerationImage InpaintingRerankingText-to-Image GenerationZero-Shot Text-to-Image Generation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Text-to-Image Generation COCO (Common Objects in Context) GLIDE (zero-shot) FID 12.24 #31 of 69 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Introduced by this paper: GLIDE

CLIPDiffusionGLIDE

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections