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Dmytro Dzhulgakov ✓

@dzhulgakov

Co-founder and CTO @FireworksAI_HQ. PyTorch core maintainer. Previously FB Ads. Ex-Pro Competitive Programmer

7 374Followers
817Following
473Posts total
67.3KViews on collected posts

Derniers posts

@dzhulgakov Wait, so just to be clear, what you're saying is the https://t.co/6GSKi2RNuZ API was what was wrong? And the longer thinking you were experiencing was actually correct? Also, wow, that's a huge difference between the LLM and SGLang. I would not have guessed that. Inte 1.1K views · 7 likes · 0 reposts · 0 replies Open on X →
Huge thanks to @Zai_org , @vllm_project and @sgl_project for partnering with us on this investigation Try GLM-5.3-Flash on Fireworks, and let us know if you notice any issues. We also launched GLM-5.3 (Flash’s bigger cousin) same day it was released on Friday. All smooth this 10.6K views · 29 likes · 3 reposts · 2 replies Open on X →
Along the way, we found a few peculiar behaviors. EvalScope prompt included explicit “think step by step” instructions. It caused Flash to significantly overthink (2-3x more tokens). It was still a fair comparison as we used identical eval harness across endpoints AIME and GPQA 4.2K views · 31 likes · 0 reposts · 1 replies Open on X →
We believe delaying the launch to investigate quality was the right call. Quality trumps hype. High bar for any launch, gated by public & internal benchmarks and functional tests, sharing fixes with the community - that’s been our consistent focus over the years: DeepSeek V4 ht 4.8K views · 35 likes · 1 reposts · 2 replies Open on X →
GLM 5.3 is now live on Fireworks, day zero: → 50% improvement over GLM 5.2 on https://t.co/T8ecPJPEiq’s Code Bench → State-of-the-art open-weight performance on cybersecurity tasks → Excels at complex coding and long-horizon tasks → US-Hosted Serverless on Fireworks Try it http 21.9K views · 307 likes · 16 reposts · 18 replies Open on X →
Quality from day 1 is something we focus a lot on at @FireworksAI_HQ: including model numerics, tool calling (we identified and fixed bugs even in OpenAI reference code) and reasoning effort control (below) 24.7K views · 20 likes · 1 reposts · 1 replies Open on X →

Face aux comptes de taille comparable

5 posts des 90 derniers jours, à côté de la tranche de under 10K abonnés. en dessous de ses pairs à la fois en portée et en engagement.

Vues médianes4 754ce compte4 175médiane pour under 10K
Portée, %64.47%ce compte250.82%médiane pour under 10K
Engagement, %0.79%ce compte1.41%médiane pour under 10K
IndicateurCe compteMédiane pour under 10KRapport
Vues médianes par post4 7544 1751.14×
Portée (vues ÷ abonnés)64.47%2.5× audience0.26×
Taux d'engagement0.79%1.41%0.56×

Autres comptes de cette tranche →   Comparer avec un autre compte →   Comment ces repères sont établis →

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

24.7K29 Nov
21.9K28 Aug
4.8K29 Aug
4.2K
10.6K
1.1K

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.09%29 Nov
1.57%28 Aug
0.80%29 Aug
0.79%
0.34%
0.64%

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.41%.

What the audience does

Likes87.4%429 in total
Reposts4.3%21 in total
Replies4.9%24 in total
Quotes1.2%6 in total
Bookmarks2.2%11 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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