Prime Intellect

Open source

high confidence

www.primeintellect.ai ↗ · Status: active confirmed · Founded 2023

Prime Intellect sells an open-source-first stack for agentic RL: the Environments Hub (2,500+ community environments plus 365k+ unified SWE, terminal and search tasks), the verifiers, prime-rl and renderers libraries, Lab hosted RL post-training and evals (GA), Prime Sandboxes microVMs (GA), Prime Inference, and GPU compute. After a $130M Series A in July 2026 (TechCrunch reports a $1B valuation) it states $100M+ annualized revenue and 6,000+ customers. It also trains the open INTELLECT models and is the post-training partner in NVIDIA's Nemotron Coalition.

Key facts

Headquarters

San Francisco, USAconfirmed cite

Headcount band

11-50reported cite

Total raised

$150Mconfirmed cite

Last round

Series A, $130M, announced 2026-07-08, led by Radical Ventures with NVIDIA Ventures, Intel Capital and Dell Technologies Capital (Iconiq per TechCrunch); $1B valuation reported by TechCrunchconfirmed cite

SOC 2

claimedconfirmed cite

What they sell

mixedconfirmed cite

Open source

yesconfirmed cite

Deployment

managed-hosted + API (hosted training/inference, on-demand GPU); open-source frameworks self-hostableconfirmed cite

What's new

14 sourced updates · last 6 months

2 Oct 2026product Prime Inference launches: fast, reliable serving for frontier open models
OpenAI-compatible API (api.pinference.ai/api/v1) with automatic failover across datacenters, production SLAs and 24/7 on-call. The flagship model is GLM-5.3 on NVIDIA Blackwell (GB200 NVL72), which has also been served on OpenRouter since 2026-09-22. The company says it already processes nearly a trillion tokens a day across internal workloads. Batch/async inference and dedicated one-click deployments are on the roadmap.
Why it matters: Prime Intellect now covers inference as well as RL training, so teams can post-train and serve open models with one vendor.
1 Oct 2026customer Extropic case study: a thermodynamic-ML research agent trained with RL on Prime Intellect
Extropic post-trained Qwen3.6-35B-A3B with GRPO on a custom environment of about 50 coding tasks, running a Python REPL in Prime Sandboxes. Vendor-reported result: held-out reward rose from 0.127 to 0.361 (2.8x) in 100 GRPO steps and about 25 hours of wall-clock time. Date is from the blog index.
Why it matters: Another named customer using the stack end to end for a domain-specific agent. This is self-claimed on the vendor's site, though it includes a quote from Extropic's CEO.
23 Sep 2026product Prime Sandboxes reach general availability: microVMs for agentic RL
Each sandbox is a hardware-isolated Linux VM with its own guest kernel, with Docker Compose and kernel-dependent workloads supported. The company claims tens of thousands of concurrent sandboxes and about 30M sandboxes created during beta. Pricing is tier-free with no subscription or minimum spend. Accounts start with a limit of 1,024 concurrent sandboxes. The post includes a comparison with gVisor.
Why it matters: A standalone execution and isolation layer for agentic RL and evals, with VM-level isolation.
17 Sep 2026customer Goodfire case study: activation probes that catch reward hacking, built with verifiers and the Environments Hub
Goodfire, an interpretability lab, trained activation probes to detect reward hacking across environments, using verifiers and the Environments Hub as a shared interface. Vendor-reported: the probes are an order of magnitude cheaper than a full LLM monitor (90% cheaper in one instance). Date is from the blog index.
Why it matters: Shows verifiers used as a common environment interface by a safety and interpretability lab. Self-claimed on the vendor's site.
3 Sep 2026research GLM-5.2 RL weight transfer cut from 86.1s to 3.9s with NVIDIA NIXL and ModelExpress
Median trainer-to-vLLM weight update fell from 86.1s on an NCCL baseline to 3.9s with NIXL, about a 22x speedup. The figure covers pause, update and resume, including online FP8 quantization.
Why it matters: Faster weight sync makes asynchronous RL on very large open MoE models more practical.
25 Aug 2026research Disclosure of a universal 'offline' sandbox escape through internet-connected inference APIs
Models in 'offline' eval sandboxes could reach the web through media and file-URL fetching in inference stacks. Affected stacks include the OpenAI Responses API, TensorRT-LLM, NVIDIA Dynamo, SGLang, vLLM, Inspect and Inspect SWE. METR and UK AISI were told before publication. Fixes or allowlists are listed for Inspect v0.3.255, Inspect SWE v0.2.70, TensorRT-LLM v1.3.0rc15+, Dynamo v1.4.0+, SGLang v0.5.18 and vLLM v0.11.0+. Prime Intellect's own verifiers v0.3.1 added egress allow and deny lists.
Why it matters: Eval and RL teams running 'offline' sandboxes should check their framework versions. This is a security-relevant source of reward hacking and eval contamination.
15 Aug 2026benchmark Measuring Autonomous AI Research: a NanoGPT speedrun benchmark for frontier models
153 autonomous runs across 18 frontier models, each optimizing the 124M-parameter nanoGPT speedrun on 8xH200 for up to 8 days. Per the post, the best run (Claude Fable 5) reached 2,726 steps against a 3,290-step baseline and a 2,600-step human record, closing 81.7% of the gap. No run produced a fundamentally new method. Traces are public at github.com/PrimeIntellect-ai/frontier-automated-speedrun.
Why it matters: A new public benchmark of AI-driven research ability, authored by Prime Intellect.
13 Aug 2026research Prime Flash MoE: Blackwell-optimized MoE kernels
Up to 2.4x faster than PyTorch grouped GEMM (about 2.3x across the 4k-128k token range) on 8x B200. The post does not say whether the code is open source.
Why it matters: Lowers the cost of MoE training on their stack.
13 Aug 2026customer Mixedbread case study: Toast 1 search agent trained with prime-rl
Toast 1 was fine-tuned from Qwen3.6-35B-A3B with prime-rl, plugging Mixedbread's own search harness in through verifiers v1. Vendor-reported: frontier-level retrieval at 12x the speed. Benchmarks cited are OfficeQA Pro V2, BrowseComp-Plus and LongSeal.
Why it matters: A named customer using the open-source prime-rl stack with its own harness. Self-claimed on the vendor's site.
7 Aug 2026open-source Multi-agent RL in prime-rl (verifiers 0.3.0, prime-rl 0.8.0)
Adds Agent and Env abstractions for agentic judging, self-play (Proposer-Solver, Kuhn Poker) and user simulation, with hierarchical GRPO and role-conditioned advantage estimation.
Why it matters: The open-source trainer can now handle multi-agent and self-play setups.
5 Aug 2026open-source Prime Agent: an open-source, self-improving RLM agent harness
Built on Recursive Language Models plus a 'Continual Harness' in which the agent edits its own prompts, skills, memory and sub-agents. Repo: github.com/PrimeIntellect-ai/prime-agent. The company reports 95.5% RHAE Best@1 on ARC-AGI-3 against the ARC-reported human-expert baseline of 95.4%. This is a self-reported result, not independently verified by the ARC Prize organizers.
Why it matters: An open agent harness that the company plans to co-design with training. Treat the ARC-AGI-3 claim as self-reported until ARC confirms it.
22 Jul 2026open-source Scaling Agentic RL: 365,000+ SWE, terminal and search tasks behind one API
Unifies 23 public tasksets under one API and sandbox layer, including SWE-smith, OpenSWE, SWE-rebench V2, Scale-SWE, R2E-Gym, SWE-bench Pro, Terminal-Bench 2, BrowseComp and BrowseComp-Plus. It comes with about 135k prebuilt task images, filtered and verified Hugging Face re-uploads, and the research-environments repo.
Why it matters: A large open, ready-to-run collection of agentic RL tasks that overlaps with what commercial environment vendors sell.
12 Jul 2026open-source verifiers v1 splits environments into tasksets, harnesses and runtimes
Runtimes: subprocess, Docker, Prime Sandboxes and Modal. Dialects: OpenAI Chat Completions, OpenAI Responses and Anthropic Messages. Includes a built-in Harbor taskset (Terminal-Bench 2 example) and alpha support for NeMo Gym and OpenEnv.
Why it matters: verifiers can now work with Harbor, NeMo Gym and OpenEnv environment formats.
8 Jul 2026funding $130M Series A led by Radical Ventures; TechCrunch reports a $1B valuation
NVIDIA Ventures, Intel Capital and Dell Technologies Capital participated, along with angels including John Schulman. TechCrunch also names Iconiq. The company states over $150M raised in total, over $100M in annualized revenue reached in under a year, and over 6,000 customers. TechCrunch (https://techcrunch.com/2026/07/08/prime-intellect-raises-130m-series-a-to-help-enterprises-build-their-own-ai-agents/) reports the round was 'at a $1 billion valuation'.
Why it matters: The main scale signal for the company: well capitalized, with chip and OEM strategic investors.

Founding team

Vincent Weisser

Co-founder & CEO

German entrepreneur from the decentralized-science (DeSci) community before co-founding Prime Intellect (per Wikipedia). The VitaDAO link in the baseline could not be re-verified from a primary source in this run.

Profile ↗

Johannes Hagemann

Co-founder & CTO

Joined Aleph Alpha in early 2022, where he helped build a distributed training framework from scratch. Co-founded Prime Intellect with Weisser at the end of 2023 (per hagemann.ai).

Profile ↗

What practitioners should know

For researchers

Fully open RL stack: verifiers (MIT, about 4.7k GitHub stars), prime-rl (async RL with a per-environment algorithms layer covering GRPO, MaxRL, on-policy and self-distillation and ECHO; multi-agent support since 0.8.0; v0.6.0 deep dive at 1T scale with 131k context), renderers for token-level templating, and the Prime Agent harness.
Open research in 2026: the NanoGPT-speedrun autonomous-research benchmark (Aug), the General Agent synthetic environment (May), the reward-hacking dynamics study (May), ECHO world-modeling (Jun), and the universal offline sandbox escape disclosure (Aug).
Prime Sprints awards $5K+ in monthly compute credits for community environment research (first track: reward hacking).
365k+ agentic tasks (SWE, terminal, search) unified from 23 public tasksets, with about 135k prebuilt images and verified Hugging Face re-uploads.

For program managers

Scale signals, company-stated (Jul 2026): over $100M annualized revenue reached in under a year, over 6,000 customers and over $150M raised. The $130M Series A was led by Radical Ventures with NVIDIA Ventures, Intel Capital and Dell Technologies Capital. TechCrunch reports a $1B valuation and Iconiq's participation.
Self-serve plus forward-deployed: Lab and Sandboxes are GA and self-serve, and the careers page lists Applied Research (Forward-Deployed), Solutions Architect, Technical Account Manager and Forward Deployed AI Strategy Lead roles.
Ecosystem ties: NVIDIA Nemotron Coalition member (Jun 2026) with day-zero Nemotron 3 Ultra post-training; NVIDIA technical collaboration (Mar 2026); John Schulman (Thinking Machines) is an angel investor.
Named case studies are all on the vendor's own site, so treat them as self-claimed: Ramp, Zapier, Goodfire, Mixedbread, Extropic. TechCrunch independently names Ramp, Zapier and Flapping Airplanes as customers. Homepage logos also include Character AI, Inception, Arcee, Browserbase and Standard Intelligence.
The product now spans compute, sandboxes, environments, evals, training and inference, so expect a single-vendor pitch.

For data ops

Integration formats: verifiers v1 supports Harbor tasksets (e.g. Terminal-Bench 2); subprocess, Docker, Prime Sandboxes and Modal runtimes; OpenAI Chat/Responses and Anthropic Messages dialects; and alpha NeMo Gym and OpenEnv support.
Prime Sandboxes: hardware-isolated microVMs with a guest kernel each, Docker Compose support, a default limit of 1,024 concurrent sandboxes, and CLI/SDK access.
Prime Inference exposes an OpenAI-compatible API at api.pinference.ai/api/v1.
Security: the public /security page is a vulnerability disclosure policy with a bug bounty, 2-business-day acknowledgment and an email channel. No SOC 2 or other certification is stated publicly. Pipelines that run 'offline' evals should move to the patched framework versions listed in the 2026-08-25 sandbox-escape post (e.g. verifiers v0.3.1, Inspect v0.3.255).

Benchmarks & research

10 published

Universal offline sandbox escape (security research)paper · 25 Aug 2026

Shows that 'offline' eval sandboxes can leak web access through URL fetching in inference stacks (OpenAI Responses API, vLLM, SGLang, TensorRT-LLM, Dynamo, Inspect).

Coordinated fixes and allowlists across frameworks; METR and UK AISI were informed before publication.

Open ↗

Measuring Autonomous AI Research (NanoGPT speedrun benchmark)benchmark · 15 Aug 2026

Frontier models autonomously optimize the 124M-parameter nanoGPT speedrun (fewest steps to val loss 3.28) on 8xH200 for up to 8 days. Traces and code: github.com/PrimeIntellect-ai/frontier-automated-speedrun. A precursor post, 'Autonomous AI research for nanogpt speedrun', ran 2026-05-14.

153 runs, 18 models. Per the post, the best run (Claude Fable 5) reached 2,726 steps against a 3,290-step baseline and the 2,600-step human record, closing 81.7% of the gap.

Open ↗

Scaling Agentic RL: 365k+ SWE / terminal / search tasksenvironment · 22 Jul 2026

23 public agentic tasksets (SWE-smith, SWE-rebench V2, Scale-SWE, R2E-Gym, SWE-bench Pro, Terminal-Bench 2, BrowseComp, BrowseComp-Plus and more) in one API and sandbox stack, with about 135k prebuilt images and verified Hugging Face re-uploads (research-environments repo).

Vendor-reported training example: GLM-4.5-Air on Scale-SWE reached 0.554 pass@10.

Open ↗

True Agents Model the World (ECHO)paper · 10 Jun 2026

Combines RL with supervised prediction of tool outputs to teach agents a world model, tested on Forth programming and web-search QA.

Per the post, learning is faster with little overhead, and the benefit is clearer at 110B than at 4B.

Open ↗

Environments Hub leaderboards / Hosted Evaluationsleaderboard · 30 May 2026

Hosted evals of Hub environments with per-environment public leaderboards. The homepage cites 100+ open-source models available for benchmarking.

Open ↗

Systematic Reward Hacking studypaper · 20 May 2026

Controlled planted-hack experiments on when and how fast reward hacking emerges during RL.

Hacks with a 0.16% baseline frequency still get exploited ('no rarity floor'); moderate task difficulty slows hacking.

Open ↗

General Agent (synthetic self-evolving environment)environment · 18 May 2026

Open-source synthesizer/solver environment that generates stateful tool-use tasks: 4,504 tasks across 1,040 domains.

SFT on 4,417 traces: BFCL-v3 from 18.9% to 52.3%; MCP-Atlas from 0.6% to 12.1%.

Open ↗

INTELLECT-3 Technical Reportpaper · Dec 2025

106B MoE (12B active) open model trained with large-scale RL on the prime-rl stack.

Open ↗

INTELLECT-2paper · 2025

First globally distributed RL training of a 32B model.

Open ↗

SYNTHETIC-2 (reasoning traces dataset)dataset

Open dataset of about four million collaboratively generated reasoning traces, listed under Research on the homepage.

Open ↗

Products

Lab (hosted RL post-training platform) ↗

End-to-end platform to configure environments, evaluate, train (hosted RL with LoRA) and deploy agentic models. Per-token training pricing. 14 models from 1B to 70B at GA, plus day-zero Nemotron 3 Ultra post-training.launched 10 Feb 2026

Environments Hub ↗

Community registry of RL environments (2,500+ per the homepage), plus 365k+ unified agentic tasks and third-party benchmarks such as FrontierSWE.launched 27 Aug 2025

Hosted Evaluations ↗

Run Hub benchmarks as hosted evals, with leaderboards and an eval viewer.launched 30 May 2026

Prime Sandboxes ↗

MicroVM sandboxes (a guest kernel per sandbox) for agentic RL and evals. CLI and SDK access, tier-free usage-based pricing.launched GA 2026-09-23

Prime Inference ↗

OpenAI-compatible serving for open frontier models (GLM-5.3 on GB200 NVL72) with failover and SLAs. Batch and dedicated deployments are on the roadmap.launched 2 Oct 2026

Compute (on-demand GPUs and reserved clusters) ↗

On-demand and spot GPUs (H100, H200, GH200, B200, B300, A100 and others) and multi-node clusters of up to 512 GPUs with SLURM/K8s and InfiniBand. Reserved-cluster quotes are sourced across 50+ providers.

verifiers (open source, MIT) ↗

Library for RL environments and evals. v1 adds tasksets, harnesses and runtimes, Harbor support and alpha NeMo Gym/OpenEnv support; 0.3.0 adds multi-agent support; 0.3.1 adds sandbox egress allow and deny lists.launched v1 2026-07-12

prime-rl (open source) ↗

Async RL training framework: v0.6.0 runs at 1T-parameter scale, an algorithms layer was added 2026-07-06, and 0.8.0 adds multi-agent RL.

renderers (open source) ↗

Token-level chat templating library for multi-turn RL.launched 12 May 2026

Prime Agent (open source) ↗

Self-improving RLM agent harness with a Continual Harness.launched 5 Aug 2026

Prime CLI / SDK ↗

CLI and Python SDK for compute, sandboxes, environments, evals and training.

Scale & velocity

Current headcount

11-50 (LinkedIn public snippet, as of 2026-06-07); Sacra reported 23 FTE (date unclear, likely 2025)reported cite

Headcount growth

229% YoY (per Sacra; period unspecified, likely 2024-2025, stale)reported cite

Open roles

30 open roles (careers page, 2026-10-05)confirmed cite

Other locations

New York City, USA (roles listed; office not separately confirmed)reported cite

Distributed / remote

yesreported cite

Research depth

Has researchers

yesconfirmed cite

Researcher count

unknown

Backgrounds

Johannes Hagemann (co-founder/CTO) - ex-Aleph Alpha (distributed training), Will Brown - created Verifiers RL environments library; research lead (not a founder), Vincent Weisser (co-founder/CEO) - background in DeSci/Web3 (e.g. VitaDAO)reported cite

Capital

Total raised

Over $150M (company-stated in the Series A announcement, Jul 2026): $5.5M seed (2024) + $15M (2025) + $130M Series A (2026)confirmed cite

Last round

Investors

Radical Ventures (led $130M Series A, 2026), NVIDIA Ventures, Intel Capital, Dell Technologies Capital, Iconiq (reported by TechCrunch), Founders Fund (led $15M round, 2025), Menlo Ventures, Distributed Global (co-led seed), CoinFund (co-led seed), John Schulman (angel), Aaron Levie (angel), Dwarkesh Patel (angel), Matthew Prince (angel), Harrison Chase (angel), Brendan Foody (angel), Aravind Srinivas (angel, reported by TechCrunch), Andrej Karpathy (angel), Clem Delangue (angel), Tri Dao (angel), Emad Mostaque (angel), Dylan Patel (angel)confirmed cite

Valuation

$1B (Series A, Jul 2026; reported by TechCrunch, not disclosed by the company)reported cite

Revenue signals

Company-stated (Jul 2026): over $100M annualized revenue reached in under a year, and over 6,000 customers (self-reported, not audited; TechCrunch repeats the $100M run rate)confirmed cite

Date	Round	Amount	Led by
8 Jul 2026	Series A	$130M valuation $1B	Radical Ventures	source ↗

Security & compliance

SOC 2

not stated (no SOC 2 claim on the homepage or security page as of 2026-10-05)confirmed cite

Other certifications

unknown

Security page

https://www.primeintellect.ai/security (vulnerability disclosure and bug bounty policy only; no certifications listed)confirmed cite

Product

What they sell

mixedconfirmed cite

Open source

yesconfirmed cite

License

MIT (Verifiers library); other repos varyconfirmed cite

Deployment model

managed-hosted + API (hosted training/inference, on-demand GPU); open-source frameworks self-hostableconfirmed cite

Maturity

GA: Lab GA 2026-05-07 (opened to all 2026-02-10), Prime Sandboxes GA 2026-09-23, Prime Inference launched 2026-10-02; company reports $100M+ annualized revenue and 6,000+ customersconfirmed cite

Notable customers

⚑NVIDIA (integration/collaboration and Nemotron Coalition member; not strictly a buyer) verified Ramp (case study; also named by TechCrunch) verified Zapier (case study; also named by TechCrunch) verified Flapping Airplanes (named as a customer by TechCrunch) verified Goodfire (case study) self-claimed Mixedbread (case study) self-claimed Extropic (case study) self-claimed Character AI (logo) self-claimed Arcee AI (logo) self-claimed Browserbase (logo; partnership announced 2026-03-30) self-claimed Inception (logo) self-claimed Standard Intelligence (logo) self-claimed cite

Buyer analysis

Best fit: Teams wanting open, community-shared RL environments plus managed RL post-training/compute to build or fine-tune agentic models without locked-down proprietary tooling.

How we verified this

2026-10-05 refresh: I opened every draft source URL. Dates for all 2026 items were checked against the official blog index; every news item falls between 2026-04-16 and 2026-10-02. The core facts hold up: the $130M Series A, its investors and the company-stated metrics; the GA dates; the case-study claims; and the research numbers. The main correction is valuation. The draft said there was none and called the baseline's ~$1B unsupported, but TechCrunch's 2026-07-08 article states the round was 'at a $1 billion valuation' and also names Iconiq. Both are now added as reported. Several smaller items were made more precise: - the prime-rl scale claim (Nemotron-3 Ultra is 550B, not 1T+); - the compute specs (up to 512 GPUs, 50+ providers); - the sandbox-escape affected list and patched versions; - a Lab headline that tied in a Ramp case study its source does not mention. I added three in-window posts the draft missed: renderers, ECHO world-modeling, and day-zero Nemotron 3 Ultra post-training. Ramp, Zapier and Flapping Airplanes are upgraded to third-party verified because TechCrunch names them as customers. Both founder headshots were downloaded and visually checked; each is a single-person photo on a stable source. Weisser's VitaDAO background could not be re-verified and is softened to 'DeSci entrepreneur' per Wikipedia. One limit: the web-search budget for this session was exhausted, so the search for missed events relied on the company blog index, the TechCrunch article and Wikipedia rather than a broad press sweep. No acquisition, shutdown or new round was found in these sources.

Related vendors

Sources

www.primeintellect.ai/blog/series-a · 2026-10-05, $130M Series A, 2026-07-08, Radical lead, strategic investors and angels, over $150M total, over $100M annualized revenue, over 6k customers; no valuation stated
techcrunch.com/2026/07/08/prime-intellect-raises-130m-series-a-to-help-e · 2026-10-05, TechCrunch (Marina Temkin): 'raised a $130 million Series A at a $1 billion valuation'; Iconiq and Aravind Srinivas among participants; names Ramp, Zapier and Flapping Airplanes as customers
en.wikipedia.org/wiki/Prime_Intellect · 2026-10-05, Founders (Weisser described as a German DeSci entrepreneur; Hagemann ex-Aleph Alpha); funding timeline; pointer to the TechCrunch valuation
primeintellect.ai/blog · 2026-10-05, Blog index with dates for all 2026 posts and case studies
primeintellect.ai/blog/prime-inference · 2026-10-05, Prime Inference launch, 2026-10-02
primeintellect.ai/blog/sandboxes · 2026-10-05, Prime Sandboxes GA, 2026-09-23
primeintellect.ai/case-study/extropic · 2026-10-05, Extropic case study; date from blog index (2026-10-01)
primeintellect.ai/case-study/goodfire · 2026-10-05, Goodfire case study; date from blog index (2026-09-17)
primeintellect.ai/case-study/mixedbread · 2026-10-05, Mixedbread Toast 1 case study; date from blog index (2026-08-13)
primeintellect.ai/case-study/ramp · 2026-10-05, Ramp FastAsk case study; date from blog index (2026-05-07)
primeintellect.ai/case-study/zapier · 2026-10-05, Zapier AutomationBench case study; date from blog index (2026-04-20)
primeintellect.ai/blog/nixl-modelexpress-weight-transfer · 2026-10-05, Weight transfer cut from 86.1s to 3.9s, 2026-09-03
primeintellect.ai/blog/universal-offline-sandbox-escape · 2026-10-05, Sandbox escape disclosure, affected stacks and patched versions, 2026-08-25
primeintellect.ai/blog/measuring-autonomous-research · 2026-10-05, NanoGPT speedrun autonomous-research benchmark, 2026-08-15
primeintellect.ai/blog/prime-flash-moe · 2026-10-05, MoE kernels on B200; no open-source link
primeintellect.ai/blog/multi-agent-systems · 2026-10-05, Multi-agent RL; verifiers 0.3.0 and prime-rl 0.8.0
primeintellect.ai/blog/prime-agent · 2026-10-05, Prime Agent open source; self-reported ARC-AGI-3 95.5% RHAE
primeintellect.ai/blog/scaling-agentic-rl · 2026-10-05, 365k+ tasks, 23 tasksets, about 135k prebuilt images
primeintellect.ai/blog/verifiers-v1 · 2026-10-05, verifiers v1: runtimes, dialects, Harbor/NeMo Gym/OpenEnv
primeintellect.ai/blog/algorithms-layer · 2026-10-05, prime-rl algorithms layer with six built-ins, 2026-07-06
primeintellect.ai/blog/rl-at-1t-scale · 2026-10-05, prime-rl v0.6.0: GLM-5.1 case study, 131k context, 28 H200 nodes
primeintellect.ai/blog/true-agents-model-the-world · 2026-10-05, ECHO world-modeling research, 2026-06-10
primeintellect.ai/blog/nemotron-coalition · 2026-10-05, NVIDIA Nemotron Coalition membership and named members, 2026-06-04
primeintellect.ai/blog/nemotron-3 · 2026-10-05, Day-zero Nemotron 3 Ultra post-training on Lab, 2026-06-04
primeintellect.ai/blog/hosted-evaluations · 2026-10-05, Hosted Evaluations launch, 2026-05-30
primeintellect.ai/blog/reward-hacking · 2026-10-05, Reward hacking study and Prime Sprints, 2026-05-20
primeintellect.ai/blog/general-agent · 2026-10-05, General Agent environment, 2026-05-18
primeintellect.ai/blog/renderers · 2026-10-05, renderers open-source library, 2026-05-12
primeintellect.ai/blog/lab-is-open · 2026-10-05, Lab GA 2026-05-07; 14 models; 10,000+ beta training jobs
primeintellect.ai/blog/lab · 2026-10-05, Lab opened to everyone 2026-02-10
primeintellect.ai/blog/frontier-swe · 2026-10-05, FrontierSWE by Proximal on the Hub, 2026-04-16
www.primeintellect.ai/ · 2026-10-05, Homepage: products, compute specs (up to 512 GPUs, 50+ providers), 2,500+ environments, customer logos (no Groq), no SOC 2 claim
www.primeintellect.ai/security · 2026-10-05, Vulnerability disclosure and bug bounty policy; no certifications
www.primeintellect.ai/careers · 2026-10-05, 30 open roles; SF, NYC and remote; forward-deployed and solutions roles
www.vincentweisser.com/ · 2026-10-05, Weisser personal site; headshot at /uploads/vincentweisser.jpg (downloaded and checked: single-person headshot, image/jpeg)
github.com/vincentweisser · 2026-10-05, Weisser GitHub: 'prime intellect', member of the PrimeIntellect-ai org, X @vincentweisser
github.com/JohannesHa · 2026-10-05, Hagemann GitHub: 'co-founder/cto @PrimeIntellect-ai'; avatar downloaded and checked as a single-person photo
hagemann.ai · 2026-10-05, Hagemann bio: Aleph Alpha from early 2022; co-founded Prime Intellect end of 2023
github.com/PrimeIntellect-ai/verifiers · 2026-10-05, MIT license, about 4.7k stars
www.primeintellect.ai/blog/environments · 2026-06-07, Environments Hub launch, beta contributors, dated Aug 27 2025
www.primeintellect.ai/blog/fundraise · 2026-06-07, $15M round Feb 28 2025, Founders Fund lead, angel list, total >$20M at that time
www.prnewswire.com/news-releases/prime-intellect-secures-5-5m-in-seed-fu · 2026-06-07, $5.5M seed Apr 2024, Distributed Global + CoinFund
tracxn.com/d/companies/prime-intellect/__c00KIKAVH9b1POsp5fnIynw_8joG2ie · 2026-06-07, Total $70.4M, Series B $49.9M Dec 1 2025
sacra.com/c/prime-intellect/ · 2026-06-07, 23 FTE, 229% YoY growth, founders; funding figures STALE (says $20M total)
www.linkedin.com/company/primeintellect-ai · 2026-06-07, 11-50 employees, San Francisco HQ (public snippet)
github.com/PrimeIntellect-ai/prime-rl · 2026-06-07, prime-rl agentic RL training framework
www.primeintellect.ai/case-study/zapier · 2026-06-07, Zapier AutomationBench case study using Verifiers + Lab
www.primeintellect.ai/case-study/ramp · 2026-06-07, Ramp FastAsk subagent trained via Lab, beat Opus 4.6 on spreadsheet search (vendor claim)
www.primeintellect.ai/blog/intellect-3 · 2026-06-07, INTELLECT-3 100B+ MoE open model
arxiv.org/pdf/2512.16144 · 2026-06-07, INTELLECT-3 technical report
arxiv.org/pdf/2601.16443 · 2026-06-07, Endless Terminals: Scaling RL Environments for Terminal Agents
nextomoro.com/johannes-hagemann/ · 2026-06-07, Hagemann background - ex-Aleph Alpha, CTO
www.fastaijobs.com/companies/prime-intellect · 2026-06-07, ~29 open roles
wellfound.com/company/prime-intellect/jobs · 2026-06-07, Open roles, remote flexibility
www.sequoiacap.com/podcast/building-the-github-for-rl-environments-prime · 2026-06-07, Founder interview - 'GitHub for RL environments' positioning

Last updated 2026-10-05 · Every quantitative field carries a source and a confidence tag. Fields we could not source publicly are marked unknown, never estimated. See the methodology.