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
Posts recentes
Procurando novos 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
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@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
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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
642.1K views · 3K likes
· 186 reposts · 74 replies
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0:21
@skalskip92 nice, btw for video understanding gemini flash is still the best bet, right?
2K views · 11 likes
· 0 reposts · 1 replies
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GPT-6 Astra is fast and expensive https://t.co/EjHb51ooBs
5K views · 43 likes
· 2 reposts · 2 replies
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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
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tire size text detection
GPT-6 Astra sees text everywhere https://t.co/OiuNFWqt5W
4.3K views · 34 likes
· 1 reposts · 1 replies
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cargo container damage detection https://t.co/MpabGLb5na
4.5K views · 29 likes
· 1 reposts · 1 replies
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ceramic insulator damage detection https://t.co/NGi5mBFR7Z
4.8K views · 32 likes
· 1 reposts · 1 replies
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poker chips detection https://t.co/Dt0VSNGH6T
5.2K views · 34 likes
· 1 reposts · 1 replies
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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
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areal and satellite images https://t.co/uLu9sWCa2q
5.7K views · 35 likes
· 2 reposts · 3 replies
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cargo container serial number https://t.co/1SD4TASZGA
7K views · 38 likes
· 3 reposts · 1 replies
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document layout detection https://t.co/fd6cyZVBzM
7.9K views · 44 likes
· 2 reposts · 1 replies
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technical drawings https://t.co/Txky7ioF7v
10.2K views · 54 likes
· 3 reposts · 2 replies
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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
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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
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@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
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@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
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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
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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
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technical drawing reasoning, Gemini 3.8 Flash (high) https://t.co/8DP5T5C93h
1.7K views · 13 likes
· 0 reposts · 2 replies
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tables with handwritten data reasoning, Gemini 3.8 Flash (high) https://t.co/U9RxDmpHT4
1.6K views · 13 likes
· 0 reposts · 1 replies
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quality assurance, Gemini 3.8 Flash (high) https://t.co/CP093s8iGV
1.9K views · 14 likes
· 0 reposts · 1 replies
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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
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tire size extraction, Gemini 3.8 Flash (high) https://t.co/Ckb2YQoHAk
2.7K views · 20 likes
· 0 reposts · 1 replies
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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
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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
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Em comparação com contas do mesmo porte
38 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para muita gente, mas poucos desses espectadores reagem.
Mediana de visualizações4 712esta conta946mediana para 10K–100K
Alcance, %9.54%esta conta3.31%mediana para 10K–100K
Engajamento, %0.69%esta conta1.89%mediana para 10K–100K
| Métrica | Esta conta | Mediana para 10K–100K | Proporção |
|---|---|---|---|
| Mediana de visualizações por post | 4 712 | 946 | 4.98× |
| Alcance (visualizações ÷ seguidores) | 9.54% | 3.31% | 2.88× |
| Taxa de engajamento | 0.69% | 1.89% | 0.36× |
Outras contas desta faixa → Comparar com outra conta → Como estas referências são construídas →
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
5.7K
6.3K
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 1.89%.
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.
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