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Model Performance on SimpleVQA, ZeroBench, and CharXiv Reaso

MetaX · Aug 20, 2026 · official

Model Performance on SimpleVQA, ZeroBench, and CharXiv Reasoning

Meta's grouped bar chart drew 10.1K views on X: 0.3x its median post and #815 of 1,162 AI chart posts we hold by views. Read Oct 12, 2026.

Model performance comparison across three benchmarks

XData Grouped bar chart Muse Spark All Meta modelsGemini 3.7 FlashMuse Spark 1.2Muse Spark 1.1Opus 5GPT 5.6 Sol

Meta: Model Performance on SimpleVQA, ZeroBench, and CharXiv Reasoning — Published by Meta on X, Aug 20, 2026. 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.

#868 of 1,162 AI chart posts we hold · #27 of 31 Meta 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, at #868 of 1,162 AI chart posts.

Its 0.012 views-per-follower sits at 0.06x the median across posts with known followers, the 5th percentile.

The post's 10.1K views are 0.28x Meta's company median of 36.4K views.

Saves landed at 0.040%, 0.52x the AI chart median of 0.076% and the 21st percentile.

0.01views per follower

10.1K views from an account with 865.4K followers.

0.1xthe median grouped bar chart post

Across 108 grouped bar chart posts we hold, the median gets 87.5K views.

0.3xMeta's median post

10.1K views, where Meta's typical post gets 36.4K.

bottom 21%save rate

0.040% 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 31 from Meta.

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 #868 of 1,162

Views	10.1K	#815	bottom 30%
Likes	67	#819	bottom 30%
Engagement rate	0.77%	#538	top 46%
Save rate	0.040%	#920	bottom 21%

Among 31 Meta posts

Score #27 of 31

Views	10.1K	#25	bottom 21%
Likes	67	#27	bottom 15%
Engagement rate	0.77%	#17	bottom 47%
Save rate	0.040%	#28	bottom 11%

Growth

One read so far

Views10.1K

Age at our read53 days

Views per day of life190views 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.

Meta'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 · Aug 20, 2026

Meta charts model performance across three benchmarks

A grouped bar chart of model performance drew 10.1K views, below the AI chart median of 39.9K.

What happened

Meta posted a grouped bar chart on August 20, 2026, comparing model performance across three benchmarks. It was one of 2 posts from the account that day, alongside a Multimodal Intelligence post at 2.9K views.

The numbers

It reached 10.1K views, #815 of 1,162 AI chart posts, and #25 of 31 Meta posts by views. Its score of 32 ranks #868 of 1,162 AI chart posts and #27 of 31 Meta posts.

The lesson

At 0.040%, saves ran 0.52x the AI chart median of 0.076%: a grouped bar chart of 5 models drew fewer bookmarks than the median AI chart post. The 0.77% engagement rate sits at or above the AI chart median even as saves trail it.

What it means

At #27 of 31 Meta posts by score, this chart sits near the bottom of the account's own output. The 0.28x gap to Meta's 36.4K company median views marks it as a low-reach post for this publisher.

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

Updates: what Meta posted next

Data and API

15 points read off this chart

Estimated from the image 97%

Series	Group	Value	Read
SimpleVQA	Gemini 3.7 Flash	77.8 %	printed
SimpleVQA	Muse Spark 1.2	75 %	printed
SimpleVQA	Muse Spark 1.1	73.3 %	printed
SimpleVQA	Opus 5	70.3 %	printed
SimpleVQA	GPT 5.6 Sol	64.7 %	printed
ZeroBench	GPT 5.6 Sol	54.6 %	printed
ZeroBench	Muse Spark 1.2	54 %	printed
ZeroBench	Opus 5	47.5 %	printed
ZeroBench	Muse Spark 1.1	46 %	printed
ZeroBench	Gemini 3.7 Flash	30 %	printed
CharXiv Reasoning	Opus 5	89.3 %	printed
CharXiv Reasoning	Gemini 3.7 Flash	88.7 %	printed

Showing 12 of 15. All points, the redraw and the maker

Max plan · API

GET https://viral-chart.com/api/posts/ee2cf5335965.json
GET https://viral-chart.com/api/charts/ee2cf5335965.json
GET https://viral-chart.com/api/charts/ee2cf5335965.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 ee2cf5335965.

See the Max plan API docs

	Path	Returns	Plan
GET	`/api/v1/charts/ee2cf5335965`	Title, publisher, date, form, point count; with a Max key, the data link	Open
GET	`/api/v1/charts/ee2cf5335965/data`	Every point with its provenance and confidence, plus the redraw spec. Add ?format=csv for CSV	Max
GET	`/api/v1/charts/ee2cf5335965/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/ee2cf5335965/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.