tweetindex
EN

SkalskiP

@skalskip92

Open-source Lead @roboflow. VLMs. GPU poor. Dog person. Coffee addict. Dyslexic. | GH: https://t.co/dEmzMDGXVf | HF: https://t.co/4Lx1Yw3CLF

49 402Followers
1 394Following
12 688Posts total
1.8MViews on collected posts

Latest posts

@skalskip92 Might be the moment where we crossed the threshold. - Astra (batch): ~$0.03–0.06 / image - Human (India/PH, $0.02–0.08 per box × 12–18 objects): $0.25–$1.00 / image 1,000 frames: - Astra: $30–60 - Human: $250–800 Astra also does the team ID + home/away context in 3.4K views · 35 likes · 0 reposts · 2 replies Open on X →
@skalskip92 Yeap 3.7K views · 22 likes · 0 reposts · 1 replies Open on X →
@skalskip92 for anything with a million internet photos behind it, agreed. the labeling that actually gets paid for is the long tail: 40 examples of one defect on one production line, classes the customer invented last month, zero web presence. knowing celtics jerseys says noth 5.6K views · 37 likes · 1 reposts · 2 replies Open on X →
data labeling is dead GPT-6 Astra easily tells Celtics players from Knicks players whether they play at home or on the road https://t.co/RCth36rbiU
0:21
642.1K views · 3K likes · 186 reposts · 74 replies Open on X →
@skalskip92 nice, btw for video understanding gemini flash is still the best bet, right? 2K views · 11 likes · 0 reposts · 1 replies Open on X →
GPT-6 Astra is fast and expensive https://t.co/EjHb51ooBs
5K views · 43 likes · 2 reposts · 2 replies Open on X →
empty / full gas cylinder detection, GPT-6 Astra (high) how to tell which one is open and which one is closed? the only clue is the pin on the valve https://t.co/jtzS96BLYk
5.8K views · 36 likes · 1 reposts · 1 replies Open on X →
tire size text detection GPT-6 Astra sees text everywhere https://t.co/OiuNFWqt5W
4.3K views · 34 likes · 1 reposts · 1 replies Open on X →
cargo container damage detection https://t.co/MpabGLb5na
4.5K views · 29 likes · 1 reposts · 1 replies Open on X →
ceramic insulator damage detection https://t.co/NGi5mBFR7Z
4.8K views · 32 likes · 1 reposts · 1 replies Open on X →
poker chips detection https://t.co/Dt0VSNGH6T
5.2K views · 34 likes · 1 reposts · 1 replies Open on X →
areal and satellite images https://t.co/uLu9sWCa2q
5.7K views · 35 likes · 2 reposts · 3 replies Open on X →
jelly bean detection notice I did not use color. I used taste. https://t.co/tuhP1zHrG8
6.3K views · 40 likes · 2 reposts · 1 replies Open on X →
cargo container serial number https://t.co/1SD4TASZGA
7K views · 38 likes · 3 reposts · 1 replies Open on X →
document layout detection https://t.co/fd6cyZVBzM
7.9K views · 44 likes · 2 reposts · 1 replies Open on X →
technical drawings https://t.co/Txky7ioF7v
10.2K views · 54 likes · 3 reposts · 2 replies Open on X →
Gemini dethroned GPT-6 Astra is the best "vision" model I've seen - notices tiny details - draws conclusions - produces precise and tight boxes - sees and reads text in different contexts - knows a lot about a lot - fast - expensive ↓ GPT-6 Astra detection deep dive https://t.
860.6K views · 1.4K likes · 88 reposts · 47 replies Open on X →
detection mAP@50 - low effort: #1, 82.1 - high effort: #1, 83.6 link: https://t.co/puUowt3HbY https://t.co/f7dYaFHwCm
18.9K views · 88 likes · 5 reposts · 1 replies Open on X →
@skalskip92 is it open source, your hands, or the prompt or testing environment? i want a similar thing and i tried for a week but the architecture and prompt for object detection, bounding box, drawings, and coordinates, etc 74 views · 1 likes · 0 reposts · 0 replies Open on X →
@skalskip92 I am beginning to understand why Qwen didn’t release the vision encoder on the new qwen3.8 max! It’s so strong! 741 views · 5 likes · 0 reposts · 1 replies Open on X →
Gemini 3.8 Flash’s speed is insane link: https://t.co/tC22dvHj1Y https://t.co/VP1YePh0dS
1.9K views · 18 likes · 0 reposts · 2 replies Open on X →
spatial reasoning, Gemini 3.8 Flash (high) compare Gemini 3.8 Flash, Qwen 3.8 Flash, Muse Spark 1.3, Claude Fable 5.1 and GPT 5.6 Terra: https://t.co/MuTyzQKuou https://t.co/KeKnDZiQyB
2.1K views · 16 likes · 0 reposts · 1 replies Open on X →
tables with handwritten data reasoning, Gemini 3.8 Flash (high) https://t.co/U9RxDmpHT4
1.6K views · 13 likes · 0 reposts · 1 replies Open on X →
technical drawing reasoning, Gemini 3.8 Flash (high) https://t.co/8DP5T5C93h
1.7K views · 13 likes · 0 reposts · 2 replies Open on X →
quality assurance, Gemini 3.8 Flash (high) https://t.co/CP093s8iGV
1.9K views · 14 likes · 0 reposts · 1 replies Open on X →
another Gemini model at the top of the image reasoning leaderboard link: https://t.co/Eu5loa2uw7 https://t.co/BeOWp1LlX3
2.2K views · 13 likes · 0 reposts · 1 replies Open on X →
x https://t.co/7A774bmYQ4
2.4K views · 15 likes · 0 reposts · 1 replies Open on X →
tire size extraction, Gemini 3.8 Flash (high) https://t.co/Ckb2YQoHAk
2.7K views · 20 likes · 0 reposts · 1 replies Open on X →
handwritten notes extraction, Gemini 3.8 Flash (high) compare Gemini 3.8 Flash, Qwen 3.8 Flash, Muse Spark 1.3, Claude Fable 5.1 and GPT 5.6 Terra: https://t.co/cLYO2zaZSj https://t.co/f1fFpldlKw
5.3K views · 24 likes · 0 reposts · 1 replies Open on X →
another Gemini model at the top of the data extraction leaderboard link: https://t.co/heRxM0xCsJ https://t.co/4N6n45lngO
4.5K views · 21 likes · 0 reposts · 1 replies Open on X →

Against accounts of the same size

38 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views4 712this account956median for 10K–100K
Reach, %9.54%this account3.36%median for 10K–100K
Engagement, %0.69%this account1.90%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post4 7129564.93×
Reach (views ÷ followers)9.54%3.36%2.84×
Engagement rate0.69%1.90%0.36×

Others in this range →   Compare with another account →   How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

7K5 Sep
6.3K
5.7K
5.2K
4.8K
4.5K
4.3K
5.8K
5K
2K
642.1K6 Sep
5.6K
3.7K
3.4K

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.62%5 Sep
0.70%
0.70%
0.69%
0.70%
0.69%
0.83%
0.69%
0.95%
0.59%
0.51%6 Sep
0.71%
0.62%
1.09%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.90%.

What the audience does

Likes62.8%5 115 in total
Reposts3.7%299 in total
Replies1.9%156 in total
Quotes1.0%79 in total
Bookmarks30.7%2 502 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

Followers by day

8 Sep

Daily snapshots since 08 Sep 2026; the dashed line is the starting count.

Similar accounts