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Training compute of notable open models

@EpochAIResearchX · Apr 8, 2025

Training compute of notable open models

@EpochAIResearch's scatter plot drew 874 views on X: 0.2x @epochairesearch's median post and #1,134 of 1,162 AI chart posts we hold by views. Read Oct 12, 2026.

Training compute of notable open models over time

XData Scatter plot Llama 4 All Meta modelsmT5-XXLOPT-175BFalcon-180BLlama 3.1-405B

@EpochAIResearch: Training compute of notable open models — Published by @EpochAIResearch on X, Apr 8, 2025. Source: x.com

32/ 100

ViralChart score

Small but loved

Fewer views than the median post but a higher engagement rate: a smaller crowd that acted on it.

#882 of 1,162 AI chart posts we hold · #49 of 59 @epochairesearch posts. Score = views 40%, likes 30%, engagement rate 15%, save rate 15%, each as a percentile of every AI chart post we hold.

Our read

It sits in the Small but loved quadrant, with a score rank of #882 of 1,162 AI chart posts.

Its 874 views sit at 0.17x @EpochAIResearch's 5.3K median, ranking #54 of 59 @EpochAIResearch posts.

The 1.95% engagement rate lands in the 98th percentile among AI chart posts, against a 0.73% median.

The score of 32 places it #882 of 1,162 AI chart posts and #49 of 59 @EpochAIResearch posts.

0.0xthe median scatter plot post

Across 187 scatter plot posts we hold, the median gets 22.4K views.

0.2x@epochairesearch's median post

874 views, where @epochairesearch's typical post gets 5.3K.

top 2%engagement rate

1.95% of viewers liked, reposted, quoted or replied. The median post gets 0.73%.

top 7%save rate

0.229% of viewers bookmarked it to come back to. The median post gets 0.076%.

Public X numbers from our read on Oct 12, 2026. Peers: 1,162 AI chart posts we hold and 59 from @epochairesearch.

Where it sits

Reach against resonance

Each dot is a post. Right is more views, up is a higher engagement rate. The lines are the medians, so the four corners are the four kinds of post.

Among 1,162 AI chart posts we hold

Score #882 of 1,162

Views	874	#1,134	bottom 2%
Likes	16	#1,060	bottom 9%
Engagement rate	1.95%	#29	top 2%
Save rate	0.229%	#79	top 7%

Among 59 @epochairesearch posts

Score #49 of 59

Views	874	#54	bottom 9%
Likes	16	#53	bottom 12%
Engagement rate	1.95%	#15	top 25%
Save rate	0.229%	#12	top 19%

Growth

One read so far

Age at our read552 days

Views per day of life2views divided by days since it was posted

Dots are our reads. The dotted line from the day it was posted to our first read is a gap, not data.

@epochairesearch's posts over time

Every post from this account we hold, by date and views. This one is marked; the line is the running median of the last 10.

News · Apr 8, 2025

@EpochAIResearch scatter plot on open model training compute

A scatter plot of training compute for notable open models drew 874 views and a 1.95% engagement rate, landing in the top decile.

What happened

@EpochAIResearch posted a scatter plot on training compute of notable open models on April 8, 2025. It was the account's only post that day.

The numbers

It reached 874 views, ranking #1,134 of 1,162 AI chart posts and #54 of 59 @EpochAIResearch posts. Its score of 32 ranked #882 of 1,162 AI chart posts.

The lesson

The 1.95% engagement rate sits at the 98th percentile among AI chart posts, against a 0.73% median. A scatter plot with 4 models shown drew a top-decile rate on 874 views.

What it means

At #49 of 59 @EpochAIResearch posts by score, this chart sits below the account's own output. The 874 views fall short of the 5.3K median for @EpochAIResearch posts.

Written by ViralChart from public numbers read on Oct 12, 2026. Every number is checked against our data before it is shown.

Updates: what @epochairesearch posted next

Data and API

27 points read off this chart

Estimated from the image 30%

Series	Group	Value	Read
Trend	Top-1	100000000000000000000 FLOP	estimated
Trend	Top-1	1e+21 FLOP	estimated
Trend	Top-1	1e+22 FLOP	estimated
Trend	Top-1	1e+23 FLOP	estimated
Trend	Top-1	1e+24 FLOP	estimated
Trend	Top-1	1e+25 FLOP	estimated
Trend	Top-1	1e+26 FLOP	estimated
Trend	Top-1	1e+27 FLOP	estimated
Trend	Top-1	1e+28 FLOP	estimated
Data	Top-1	100000000000000000000 FLOP	estimated
Data	Top-1	1e+21 FLOP	estimated
Data	Top-1	1e+22 FLOP	estimated

Showing 12 of 27. All points, the redraw and the maker

Max plan · API

GET https://viral-chart.com/api/posts/aa5016c91cd8.json
GET https://viral-chart.com/api/charts/aa5016c91cd8.json
GET https://viral-chart.com/api/charts/aa5016c91cd8.skill.md

Make one like this Open the post JSON Chart data JSON Skill file API docs

Static files in this prototype. The post JSON holds the public numbers, ranks, score, quadrant, our reads and, when checked, our copy.

API · Max

Use this chart via API

On the Max plan you can pull this chart's numbers with the provenance of each one, as JSON or CSV, with its redraw spec, or call it from an agent over MCP. Chart id aa5016c91cd8.

Approximate values. Our two readings of this chart agreed only in part (confidence 0.30 of 1), so check the original before you quote a number. The API marks it lowConfidence, and ?min_confidence=0.5 leaves it out.

See the Max plan API docs

	Path	Returns	Plan
GET	`/api/v1/charts/aa5016c91cd8`	Title, publisher, date, form, point count; with a Max key, the data link	Open
GET	`/api/v1/charts/aa5016c91cd8/data`	Every point with its provenance and confidence, plus the redraw spec. Add ?format=csv for CSV	Max
GET	`/api/v1/charts/aa5016c91cd8/render?view=1`	The draw-only view this page uses	Open
POST	`/mcp`	Tool get_chart_data with this id, for Claude, Cursor and other agents	Max

curlMax

curl -s https://viral-chart.com/api/v1/charts/aa5016c91cd8/data \
  -H "Authorization: Bearer $VIRALCHART_KEY"

Claude CodeMax

claude mcp add --transport http viralchart https://viral-chart.com/mcp \
  --header "Authorization: Bearer $VIRALCHART_KEY"

60 requests a minute per key; over that you get 429 with Retry-After. Up to 5 keys per account, made on your account page and shown once. Without Max, the data route answers 402 with a link to the plans. The numbers describe a chart its publisher owns, and every file carries a license note.