r/mlscaling
19k members
r/mlscaling is a subreddit with 19k members. The community frequently discusses ai, scaling, models, training, and model, and the most common flair used is r, theory, data, research, and oa.
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
Popular Topics in r/mlscaling
#1
Ai
110 posts
#2
Scaling
66 posts
#3
Models
44 posts
#4
Training
35 posts
#5
Model
32 posts
#6
Deep Learning
23 posts
#7
Ml
21 posts
#8
Llm
20 posts
#9
Reasoning
18 posts
#10
Language
18 posts
Flair Used in r/mlscaling
#1
R
: "FrontierMath is now saturated"
15 posts
#2
Theory
: "Apodex 1.0: Orchestration & Verification Scaling vs Pure Parameter Scaling for Deep Research"
5 posts
#3
Data
: "Podcast on evals, RL environments, and data quality from Mechanize Inc."
3 posts
#4
Research
: "GPT-5.4 Arabic–Hebrew Hybrid Artifact: 12,160 Frozen Trials Across a One-Code-Point Prompt Split"
3 posts
#5
OA
: "GPT-5.6 Sol scores 7.78% on ARC-AGI-3"
2 posts
#6
MoE
: "Kimi K3 (huge 2.8t MoE)"
2 posts
#7
R, T, Emp, Data
: ""Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance", Ye et al 2024"
2 posts
#8
Hardware
: "Nvidia reportedly testing lower memory configs of Rubin Ultra as memory shortage bites back — designs tested include as little as 192 GB"
2 posts
#9
N, G, T, Econ
: "Google silently degrades suspected LLM distillation attempts"
1 post
#10
N, OA, T, Emp, RL
: ""Summary of METR's predeployment evaluation of GPT-5.6 Sol", METR ("71hrs (95% CI: 13hrs - 11400hrs)"; now so reward-hackprone + eval-aware that de facto un-evaluable)"
1 post
Member Growth in r/mlscaling
Yearly
+5k members(32.5%)
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Last updated: August 12, 2026