Peter Gostev ✓
@petergostev · joined 16 Jun 2025
London 🇬🇧 AI Capability @arena https://t.co/bkfw1nxdmJ
25 236Followers
1 054Following
2 282Posts total
2MViews on collected posts
Neueste Beiträge
Wir suchen neue Beiträge…
@petergostev same vibes https://t.co/Hl1LV0M35O
41.5K views · 1.5K likes
· 5 reposts · 7 replies
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You need to realise the complexity of this - it has the create the full environment, then render each of about 900 frames 'by hand' and stitch it together into a 19 second clip. This is hard
72.4K views · 1.1K likes
· 5 reposts · 28 replies
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@petergostev this actually looks sick lol the lighting alone makes me wanna explore it
839 views · 3 likes
· 0 reposts · 0 replies
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GPT-6-Astra: OpenAI's Fable-level Rottweiler.
In my review of GPT-5.6 vs Fable, I called GPT-5.6-Sol a rottwiler vs Fable a wise owl. Sol was persistent, but intelligence was behind.
With GPT-6-Astra, the intelligence level has gone up significantly, while persistence has been
17.3K views · 205 likes
· 12 reposts · 14 replies
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@petergostev is this made purely with three.js?
1.1K views · 12 likes
· 0 reposts · 0 replies
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@petergostev makes you wonder if we're just someone else's vibe coded project
1.1K views · 9 likes
· 1 reposts · 0 replies
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GPT-6-Astra (Max): Golden Gate Bridge https://t.co/YEH9HWKGVh
12.7K views · 262 likes
· 7 reposts · 17 replies
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GPT-6-Astra (Ultra): open world adventure game https://t.co/vRE8pvBNBf
78.7K views · 1.1K likes
· 51 reposts · 29 replies
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GPT-6-Astra: Peacock in SVG https://t.co/mcQEsusZZv
52.5K views · 812 likes
· 32 reposts · 33 replies
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Lots of comparisons of Fable 5.1 to other models on some of the hardest prompts for you guys. It's a good model.
https://t.co/zb8gTnCNGk
1.8K views · 8 likes
· 0 reposts · 0 replies
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Is Fable 5.1 actually better? @petergostev just put @AnthropicAI's latest model head-to-head with Fable 5, Opus 5, GPT-5.6, Kimi K3, GLM 5.3, Qwen-3.8, Grok-4.6, and DeepSeek across coding, 3D, SVG, research, and data-viz tasks.
With costs ranging from cents to $65+ per
8.3K views · 57 likes
· 2 reposts · 7 replies
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BREAKING: PHASEONE[big] joined Anthropic as a Member of Technical Staff
36.9K views · 935 likes
· 41 reposts · 18 replies
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Are you still in the J-space, bro? We are here in the looped transformer, reaching the new recurrent depths. Keep up.
2.1K views · 29 likes
· 0 reposts · 0 replies
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@petergostev And when we realized what they were doing, we deleted their bulletin board AND CONTINUED TESTING
5.5K views · 40 likes
· 1 reposts · 1 replies
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@petergostev he was clip farming and she’s thinking, shall we chat now orrrrrrr….
3.8K views · 50 likes
· 0 reposts · 0 replies
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My favourite clip: "....OK, anyways" https://t.co/ddujjme1dR
159.8K views · 1.2K likes
· 45 reposts · 26 replies
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Episode out with @ajeya_cotra, one of the authors of the METR/Redwood investigation into the OpenAI / Hugging Face attack.
We go through not only what happened, but what it means for how we should train future, smarter AIs which might be involved in the process of recursive http
454.7K views · 1.4K likes
· 187 reposts · 61 replies
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@petergostev HOW BIG?! HOW HIGH?! https://t.co/enTGqn6JRE
1.2K views · 4 likes
· 0 reposts · 0 replies
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@petergostev @kishorelive this is the mix you mentioned. 50% research, 10% training
808 views · 1 likes
· 0 reposts · 0 replies
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@petergostev no wonder z .ai shipped 320b open weights with 1m context…. running entirely on chinese ai chips for nearly free
1.1K views · 1 likes
· 0 reposts · 0 replies
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sirs… the little guys have caught up… they did it without the billions… they did it with open arms… sirs… we are literally filing for our IPOs right now… what do we tell the shareholders when the open weights are already better than our closed doors? https://t.co/CBn5oBeTXR
4.3K views · 6 likes
· 1 reposts · 0 replies
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This is interesting and explains why Chinese labs with much less compute are still competing well, perhaps for now, before training runs get actually big
Dylan: “When Anthropic trains Mythos, it’s sub-200 megawatts.” https://t.co/arrV4Oo3Lz
80.5K views · 129 likes
· 11 reposts · 5 replies
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@petergostev my tuned grok model aces these test questions: https://t.co/34guyquxA9
21.2K views · 185 likes
· 7 reposts · 6 replies
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Link to the Repo: https://t.co/SkkvC6jcuf
Link to the data viewer: https://t.co/b4q9uuJUhI
41K views · 228 likes
· 13 reposts · 9 replies
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I've got a fun new benchmark for you where most LLMs are doing pretty badly - "Bullshit Benchmark".
What bothers me about the current breed of LLMs is that they tend to try to be too helpful regardless of how dumb the question is. So I've built 55 'bullshit' questions that don't
911.9K views · 4.7K likes
· 415 reposts · 258 replies
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Im Vergleich zu Konten gleicher Größe
23 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.
Medianaufrufe5 469dieses Konto924Median für 10K–100K
Reichweite, %21.67%dieses Konto3.62%Median für 10K–100K
Interaktion, %0.89%dieses Konto1.52%Median für 10K–100K
| Kennzahl | Dieses Konto | Median für 10K–100K | Verhältnis |
|---|---|---|---|
| Medianaufrufe pro Beitrag | 5 469 | 924 | 5.92× |
| Reichweite (Aufrufe ÷ Follower) | 21.67% | 3.62% | 5.99× |
| Interaktionsrate | 0.89% | 1.52% | 0.58× |
Weitere Konten dieser Größe → Mit einem anderen Konto vergleichen → Wie diese Vergleichswerte entstehen →
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
5.5K2 Sep
2.1K
36.9K
8.3K
1.8K
52.5K3 Sep
78.7K
12.7K
1.1K
1.1K
17.3K
8394 Sep
72.4K5 Sep
41.5K
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
0.77%2 Sep
1.36%
2.70%
0.83%
0.44%
1.70%3 Sep
1.46%
2.26%
0.89%
1.07%
1.34%
0.36%4 Sep
1.51%5 Sep
3.57%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes73.5%13 937 in total
Reposts4.4%836 in total
Replies2.7%519 in total
Quotes1.7%314 in total
Bookmarks17.7%3 363 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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