Together AI

@togethercompute · San Francisco, CA · joined 14 Nov 2022

Accelerate inference, model shaping, and pre-training on a research-optimized platform.

62 694Followers

372Following

3 115Posts total

42.9KViews on collected posts

Derniers posts

Together AI@togethercompute3 Sep

Huge congrats to @wonderful_ai on their Series C! Hundreds of agents and systems running across a dozen verticals and 30+ markets in less than 2 years. An absolutely impressive pace, and we're proud to be part of the infrastructure powering it. 2.6K views · 11 likes · 1 reposts · 1 replies Open on X →

Together AI@togethercompute3 Sep

@togethercompute @Equinix @nvidia Inference exchanges could make geographic deployment a first-class choice for AI teams. 29 views · 0 likes · 0 reposts · 0 replies Open on X →

Together AI@togethercompute3 Sep

@togethercompute @Equinix @nvidia 模型能选，部署位置也能选，这个思路挺顺的。 146 views · 0 likes · 0 reposts · 0 replies Open on X →

Together AI@togethercompute3 Sep

Last week's Together Table at Officina: engineering leaders from Ramp, Reducto AI, Datadog, Webflow, DoorDash, Zendesk, Notion, and Atlassian on the real trade-offs of closed vs. open models in production. Smart people, strong opinions, great food. More of these coming. https:/ 3K views · 13 likes · 2 reposts · 0 replies Open on X →

Together AI@togethercompute2 Sep

everyone’s trying to find where to test glm 5.3 & glm 5.3 flash you can try it free on Together Chat, no api setup just pick one + start prompting served on secure north american infrastructure https://t.co/IgND3kr22e https://t.co/aEtdzISxE2 4.7K views · 53 likes · 8 reposts · 6 replies Open on X →

Together AI@togethercompute2 Sep

@togethercompute @Equinix @nvidia This is the real shift. The question isn't which model to use anymore, it's where you run it. Sovereign inference is becoming the default for teams that care about data and latency. Are you seeing enterprises move workloads on-prem first or hybri 491 views · 1 likes · 0 reposts · 0 replies Open on X →

Together AI@togethercompute2 Sep

Open source is becoming the default way enterprises build with AI. Not just which model runs, but where it runs. Today we're partnering with @Equinix and @nvidia on Equinix Inference Exchange: our open-model platform, live across Equinix's global data centers. Model choice and 19.9K views · 36 likes · 8 reposts · 4 replies Open on X →

Together AI@togethercompute31 Aug

@togethercompute @HUMAIN Congrats 🚀 746 views · 1 likes · 0 reposts · 0 replies Open on X →

Together AI@togethercompute31 Aug

Power is the real bottleneck in AI right now. This deal solves for that at a scale most companies can't access on their own balance sheet. 3.5K views · 8 likes · 1 reposts · 2 replies Open on X →

Together AI@togethercompute31 Aug

This is what the next phase of AI infra looks like: partnerships that unlock compute, not everyone racing to raise their own billions. 2.5K views · 7 likes · 1 reposts · 0 replies Open on X →

Together AI@togethercompute31 Aug

Closed models had hyperscalers bankrolling their compute for years. Open source is catching up, starting now. 5.3K views · 19 likes · 0 reposts · 2 replies Open on X →

Face aux comptes de taille comparable

11 posts des 90 derniers jours, à côté de la tranche de 10K–100K abonnés. portée ordinaire pour sa taille, réaction plus faible que la moyenne.

Vues médianes2 581ce compte924médiane pour 10K–100K

Portée, %4.12%ce compte3.62%médiane pour 10K–100K

Engagement, %0.32%ce compte1.52%médiane pour 10K–100K

Indicateur	Ce compte	Médiane pour 10K–100K	Rapport
Vues médianes par post	2 581	924	2.79×
Portée (vues ÷ abonnés)	4.12%	3.62%	1.14×
Taux d'engagement	0.32%	1.52%	0.21×

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

5.3K31 Aug

2.5K

3.5K

746

19.9K2 Sep

491

4.7K

3K3 Sep

146

2.6K

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.41%31 Aug

0.32%

0.13%

0.25%2 Sep

0.20%

1.44%

0.50%3 Sep

0.00%

0.50%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes64.5%149 in total

Reposts9.1%21 in total

Replies6.5%15 in total

Quotes1.7%4 in total

Bookmarks18.2%42 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.

Derniers posts

Face aux comptes de taille comparable

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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