Prime Intellect

Open Superintelligence Stack

[Prime Intellect @PrimeIntellect]

Announcing our $130M Series A to build the Open Superintelligence Stack

Led by Radical Ventures, with NVIDIA, Intel Capital, Dell Capital, and existing investors

Train, deploy, and continuously improve your own models using our stack.

Own your intelligence.

[Siddarth @siddarthv66]

It’s fairly well known frontier labs use value functions now, but we still don't have good open value function infra. Here's something cool from my ongoing internship @MistralAI with @laurence_ai getting value functions to work

Introducing - Prime Values

> Clean hackable, independent abstractions built on top of prime-rl by @PrimeIntellect
> First-class asynchronous value trainer and evaluator nodes, with no trainer bottleneck
> Native value warmup support
> Streaming replay buffer feeds value model exploiting its greater staleness/reuse tolerance

Defaults validated to match or outperform mean-baseline GRPO on both single-turn and multi-turn tasks

[Prime Intellect @PrimeIntellect]

@siddarthv66 @MistralAI @laurence_ai 🔥

[Prime Intellect @PrimeIntellect]

https://t.co/0p9Pfxp6Ba

[Prime Intellect @PrimeIntellect]

@cyberpengk 🔥

[elie @eliebakouch]

we replicated anthropic jspace analysis on @thinkymachines Inkling new 1T model!

it seems to be an outlier: where other models split into near-orthogonal sensory/workspace/motor blocks, inkling keeps roughly one geometry across the whole stack (early-late CKA ~0.8 vs ~0.5 elsewhere)

we also look computed the J-space of @poolsideai's laguna XS 2.1 in bf16 vs nvfp4 to test the impact of quantization. result: almost none. the quantized model has the same jlens space as the non-quantized one

both jspace checkpoint are up on hugging face!

[Leonardo @leonardofed]

choose your fighter

PI hoodies available in store
limited run, link below

[Prime Intellect @PrimeIntellect]

https://t.co/0p9Pfxp6Ba

[Prime Intellect @PrimeIntellect]

@aidanjnn https://t.co/0p9Pfxp6Ba 🫡

[Vincent Weisser @vincentweisser]

Prime Intellect is built to provide the best price for any given task.

if you're able to get better price/perf on any workload, would love to hear the details and look at it together — [email protected]

[Prime Intellect @PrimeIntellect]

@MatthiasRossini @slobkebap https://t.co/aURHfGVCYm 🫡

[kenneth @kennethnym]

today is my first day @PrimeIntellect

i'm so grateful to be able to work alongside such incredible team, i have so much to learn !! :)

[AI Engineer @aiDotEngineer]

Congrats to PI on the unicorn round and $100M ARR!

we were proud to have @willccbb introduce verifiers at the first AIE NYC a year ago and now... it is v1!

Will joins a rare list of three-time AIE speakers, and his talk on the full PI stack is linked below!

[Prime Intellect @PrimeIntellect]

Today, we are releasing verifiers v1 — an overhaul of our environment stack for the modern era of agentic RL and evals.

We decompose environments into a taskset, a harness, and a runtime.

Run complex agentic tasks like coding and computer use at scale, in any harness.

[Florian Brand @xeophon]

verifiers v1 is finally out, something we worked on for months to nail it properly

Lets talk about some of the non-obvious things that these changes unlock:

[Prime Intellect @PrimeIntellect]

@mikasenghaas 🙌

[Mika Senghaas @mikasenghaas]

super proud to get this out and in the hands of the people !!

a quick thread on some personal highlights

[Anirudh Ravichandran @anravich94]

We envision verifiers V1 becoming the standard format for environments. It's built to be highly composable, support training and evaluation on rollouts and yet be highly flexible.
Put plainly, these abstractions make it really easy to design your environments, and evaluate and train on them!

@mikasenghaas, @xeophon and @willccbb cooked big time with this one 👊👊