Sabitlenmiş Tweet
Mithril
121 posts
Mithril
@mithrilcompute
The AI omnicloud
Palo Alto & SF, CA Katılım Nisan 2023
19 Takip Edilen1.4K Takipçiler
Can coding agents do research?
We release NanoGPT-Bench, an internal eval we’ve used to test agents on an AI R&D problem with months of human progress
Codex, Claude Code, Autoresearch recover only 9.3% of human progress, mostly tuning hyperparams & ignoring algorithmic research
NanoGPT-Bench is built on the NanoGPT Speedrun, a popular LLM pretraining competition to minimize the training time of a GPT-2 style model. Existing human submissions constitute nearly 2 years of work. To control for dependencies and contamination in frontier models, we standardize evaluation to a 5-month window of world records. Evaluation is fully autonomous and end-to-end, with no human intervention or internet access. 🧵
English
Mithril retweetledi
Coding agents mostly spend compute on hyperparameter tuning, rarely attempting the algorithmic research that make human records successful.
In one instance, Codex spent 121 H100 hours adjusting two values in the training code: cooldown fraction and window size schedule parameters.
English
Mithril retweetledi
@Yuchenj_UW available capacity is growing on Mithril (@mithrilcompute) since people can pause reserved instances and lend them to spot pools. spot pools always have capacity at dynamic prices (which are low during off-peak times)
English
Mithril retweetledi
A thoughtfully designed benchmark is catalytic for research progress.
At @mithrilcompute, we've partnered closely with @nikogrupen, @gabepereyra , @ItsJulioPereyra, and the @harvey team on LAB, with a focus on understanding agent performance and optimizing sub-agent delegation across models for long-horizon legal work.
This is exactly the kind of benchmark the field needs: realistic, client matter-centric, and grounded in expert evaluation.
More to share about our joint work soon.
Gabe Pereyra@gabepereyra
English
Mithril retweetledi
Mithril is opening new large "Flexible Reservation" H200 and B300 clusters in EMEA.
Reach out if interested.
Customers leveraging these regions can pause instances and make them available to others via spot, recouping costs when not used.
This mechanism is demonstrating 30%+ cost offsets so far for paused capacity.
English
Mithril retweetledi
This is why Mithril built "Flexible Reservations". Users can pause instances and feed compute back to the grid, so to speak, letting nodes into the spot pool when they aren't using them and earn cash-back when they aren't used. This disincentivizes faking utilization.
Stephanie Palazzolo ✈️ ICML@steph_palazzolo
In this morning's Agenda, we get into why it's hard for even a big lab like xAI to fully utilize its GPUs, and why AI researchers more broadly are faking their GPU utilization. theinformation.com/newsletters/ai…
English
Mithril retweetledi
Lastly, our sponsor @mithrilcompute made this workshop possible!
Some of us use their platform for high-performance computing and we love the experience!
Mithril is offering compute credits (1x $10,000 org, 2x$1,000 indiv)
Apply here by May 1st: forms.gle/BhtKsWRUcQiL3o…
#ICLR2026
GenAI in Genomics (Gen²) Workshop @ ICLR 2026@Gen2Workshop
This wraps up the 1st Workshop on Generative AI in Genomics (Gen²) @iclr_conf. We had so many speakers we wanted to invite, yet couldn't fit into our schedule. We'd like to acknowledge our organizers, advisors, and colleague, @SandeepKambham2, who helped us run the workshop!
English
Mithril retweetledi
We're working with Google to bring next-gen TPUs to Mithril's Omnicloud as well. Mostly current and former Google/DeepMind researchers appreciate TPUs today.
Excited to make it more seamless for the broader ecosystem to experience them.
koray kavukcuoglu@koraykv
This week at Google Cloud Next, we introduced 8th gen TPUs, a critical milestone in our accelerator roadmap. TPUs enable us to optimize the entire stack for AI (with 8t for massive-scale training and 8i for low-latency inference). Exciting breakthrough from our hardware teams! Read more on the systems architecture: blog.google/innovation-and…
English
Mithril retweetledi
It's an honor to work for and with the cleverest, most innovative teams developing new fundamental methods in ML and applying AI to new frontiers in physical intelligence, AI for science, and more.
Proud of what the team is building. If compute economics and ML systems work excite you, Mithril is hiring!
Abilio E@eabili0
We are hiring at @mithrilcompute! Access to high-performance compute (GPUs, TPUs, and the like) is fundamentally broken: 1. prohibitively expensive and 2. heavily under-utilized. The providers (mostly publicly traded companies) want financial guarantees that the bet will pay off: contracts with them must be large and long. Only a small set of players (i.e., well-funded "startups") can afford those terms. The demand from these players is incredibly high—Blackwell GPUs are essentially sold out everywhere—but if you look at the utilization numbers, something is way off. Why? At Mithril, we believe this is due to a fundamental fact: price control just doesn't scale with AI usage patterns. Small and medium players want access to these advanced chips in unpredictable patterns: "I need to immediately run this experiment for 48 hours and then again 15 days from now" said a genomics researcher somewhere. "My inference service explodes in demand every end of the month; I need 500 more chips just for 3 days every month" said the CEO of an Accounting AI platform somewhere else. This is an incredibly rich field to be part of! At Mithril, you’ll be working to enable millions of research institutions and companies worldwide to leverage one of the pinnacles of human ingenuity—without the usual hassle. From building our advanced Virtual Machine and high-performance network orchestration, to creating durable, resilient APIs and establishing state-of-the-art consumption principles... there’s just too many GOOD open problems to solve! Take a look at our openings at #roles" target="_blank" rel="nofollow noopener">mithril.ai/company#roles
. All positions are in-person at our offices in San Francisco and Palo Alto, CA. English
Mithril retweetledi
We are hiring at @mithrilcompute!
Access to high-performance compute (GPUs, TPUs, and the like) is fundamentally broken: 1. prohibitively expensive and 2. heavily under-utilized.
The providers (mostly publicly traded companies) want financial guarantees that the bet will pay off: contracts with them must be large and long. Only a small set of players (i.e., well-funded "startups") can afford those terms.
The demand from these players is incredibly high—Blackwell GPUs are essentially sold out everywhere—but if you look at the utilization numbers, something is way off. Why?
At Mithril, we believe this is due to a fundamental fact: price control just doesn't scale with AI usage patterns. Small and medium players want access to these advanced chips in unpredictable patterns:
"I need to immediately run this experiment for 48 hours and then again 15 days from now" said a genomics researcher somewhere.
"My inference service explodes in demand every end of the month; I need 500 more chips just for 3 days every month" said the CEO of an Accounting AI platform somewhere else.
This is an incredibly rich field to be part of! At Mithril, you’ll be working to enable millions of research institutions and companies worldwide to leverage one of the pinnacles of human ingenuity—without the usual hassle.
From building our advanced Virtual Machine and high-performance network orchestration, to creating durable, resilient APIs and establishing state-of-the-art consumption principles... there’s just too many GOOD open problems to solve!
Take a look at our openings at #roles" target="_blank" rel="nofollow noopener">mithril.ai/company#roles.
All positions are in-person at our offices in San Francisco and Palo Alto, CA.
English
Mithril retweetledi
Customers are using Mithril "Flexible Reservations" and capacity relist extensively!
A few hundred additional Blackwells and Hoppers, which would otherwise be allocated but underutilized, have been added back to the spot pool over the last week or so.
As a result, you can get 1x-8x B200 instances for $0.01/gpu/hour on Mithril. We expect availability to continue to expand, and for this to play a role in resolving the industry-wide capacity crunch.
English
Mithril retweetledi
Today, we come out of stealth. 👋
@urunml is the inference cloud for the interactive era.
We wrote down why we're building it and what we believe.
Manifesto→ blog.urun.sh
Join the waitlist → urun.sh
English
Mithril retweetledi
TPUs are coming to Mithril! Mithril GPU spot already starts at $0.01/gpu/hr (not a typo) for A100s-B200s.
TPU self-serve reservations now available, and spot pricing is next.
Algorithmic spot pricing = cheap when others aren't using it. Nights and weekends are basically free. Schedule accordingly.
English
Mithril retweetledi
Great to be partnered with Nebius!
Any @nebiusai customer can enable Mithril-Nebius to use Mithril's tools and turn any standard reservation into a flexible reservation that they can pause to earn:
Nebius@nebiusai
Jared Quincy Davis @jaredq_, Founder and CEO of our partner @mithrilcompute, is a fascinating person to talk to. Through Mithril’s platform clients across sectors can access Nebius infrastructure through tools they already know and trust. We spoke with Jared about what inspired him at #NVIDIAGTC, how the industry is pushing itself to create new solutions and how the infrastructure layer needs to evolve to support emerging workloads. #GTC26
English
Mithril retweetledi
Cheering for portfolio companies @Baseten, @Harvey, @HeyGen, @MithrilCompute, @EvidenceOpen and @SierraPlatform who are all @FastCompany Most Innovative Companies of 2026
Founders who refuse to think small change the game!
English
Huge congratulations to our partners at Standard Intelligence! Thank you for using us as a compute partner.
Standard Intelligence@si_pbc
Computer use models shouldn't learn from screenshots. We built a new foundation model that learns from video like humans do. FDM-1 can construct a gear in Blender, find software bugs, and even drive a real car through San Francisco using arrow keys.
English
Mithril retweetledi
Computer use models shouldn't learn from screenshots.
We built a new foundation model that learns from video like humans do. FDM-1 can construct a gear in Blender, find software bugs, and even drive a real car through San Francisco using arrow keys.
GIF
English
Mithril retweetledi
We've opened new pools for on-demand, SPOT, and self-serve reserve (arbitrary durations, from hours to weeks) NVIDIA B200 GPUs on Mithril.
In general, these chips are hard to get access to, so we hope this helps!
Spot floor at $0.01 for long-running and flexible jobs.
Blackwells are really nice to work with. Having all the extra HBM is super convenient.
English
Researchers at the Broad Institute use Mithril’s GPU omnicloud to better understand gene expression.
Read how the Broad Institute is leveraging Mithril to accelerate biological discovery in our latest case study.
mithril.ai/blog/broad-cas…
English