The compute efficient layer for AI inference
Austin, TX
Joined October 2025
- Tweets268
- Following30
- Followers177
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ZeroGPU AI retweeted
This is like watching one of my own tweet!
@ZeroGPU_AI is all about small models that can perform a specialized task faster, with better accuracy and faster speed. These models don’t need larger GPUs and can even run on the edge!
We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case).
I think we'll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you'll see specialist models out perform on more narrow tasks, either working on teams, or by themselves.
We're making it easy to fine tune models internally for our employees. We even have a skill for it in our internal harness that makes it easy to spin these up and start training them:
"/fine-tune-and-serve-llm I want to fine-tune Qwen for payments risk review. help me get started"
I imagine we'll have some backend services that could be replaced entirely by this new architecture.
ZeroGPU AI retweeted
@ZeroGPU_AI we are building ai inference infra powered by small and open weight models. You dont need frontier models for high volume repeatable tasks.
We are also currently running a $10k compute credit matching.
ZeroGPU AI retweeted
We embraced @ZeroGPU_AI at @DappierAI early on.
Cut costs on 40% + of AI tasks by leveraging SLMs running at the edge.
As @GavinSBaker mentioned on a recent episode of @theallinpod the vast majority of tasks do not require frontier models; the recent report from OpenRouter underscores this.
ZeroGPU is building a new kind of inference cloud using Small Language Models - SLMs - orchestrated and running across a variety of edge devices, freeing up data centers for higher leverage tasks.
Every nook and cranny of compute will be taken up and is the greatest bottleneck to AI progress - creative solutions like ZeroGPU will help meaningfully unlock the market.
Give them a try!
Not every task needs a frontier model.
More than 40% of OpenRouter spend is already SLM-ready. By switching to the right small language model, you can reduce latency, cut costs by 5x.
We have more models coming soon. Stay tuned!
zerogpu.ai
ZeroGPU AI retweeted
Not every token needs a frontier model.
40.5% of @OpenRouter spend is SLM-ready.
@ZeroGPU_AI has models that can cover all these flows with SLMs
- workflow execution: 19%
- classification: 9.8%
- extraction + transformation: 8.3%
- summarization + tool dispatch + memory: 3.4%
Right model. Right task.
We have more models coming soon. Stay tuned!
lnk.bio/zerogpu
ZeroGPU AI retweeted
This is where AI inference is heading.
Compute can't be built fast enough. Capable models keep getting smaller.
The answer is smaller models running closer to the user, on the devices that already exist.
That's the layer we're building.
Today we're also opening the weights for Muse Glimmer, a great 30B parameter dense model that can run locally. Soon we'll also release the weights for Muse Spark 1.2, our latest foundation model. Meta is a strong supporter of open source and I'm proud of these releases. Congrats to @alexandr_wang and the MSL team for all your great work on these models.
ZeroGPU AI retweeted
ZeroGPU is now on LangChain 🦜
If you're running a @LangChainAI agent, a lot of what that agent does on every turn doesn't need frontier reasoning.
Point those tasks at specialized small language models instead and cut your inference bill.
ZeroGPU AI retweeted
Automate your company's most recurring tasks, without involving an expensive frontier model.
Here's how you can screen resumes at scale using specialized Small Language Models (SLMs) & LangChain.
Add our catalog of SLMs to your Langchain agent:
pip install langchain-zerogpu
ZeroGPU AI retweeted
If you're using a frontier AI like ChatGPT or Claude to perform basic adtech tasks like classification - save your $$$.
We just dropped our specialized small language models for adtech.
Thanks to @adexchanger for covering the launch in our first-ever feature interview.
ZeroGPU AI retweeted
We benchmarked our @ZeroGPU_AI moderation model head-to-head against OpenAI's omni-moderation on 4,277 real production-range inputs.
It won. 🏆
ZeroGPU AI retweeted
@ZeroGPU_AI has @deepseek_ai flash models. We have prices no other inference provider can compete.
Pay as you go through many integrations we have @openclaw , Hermes, OpenAI endpoints and even x402.
We are on a mission to prove you don’t need frontier model for 80-90% of your tasks. Save it for reasoning. Sign up today!
Zerogpu.ai
ZeroGPU AI retweeted
@GoogleResearch and @UCSanDiego are building a computing platform using retired Pixel phones by turning hardware people no longer use into low-cost, low-carbon cloud infrastructure.
This is closely aligned with what we’re building at @ZeroGPU_AI
We don’t believe every AI request should require a massive GPU or a frontier model. Tasks like classification, extraction, moderation, routing, and summarization can often run on specialized small models using lightweight or edge hardware.
🤖 Made with AI
ZeroGPU AI retweeted
Agreed, that’s why we’re working on task-specific models for repetitive workloads: summary, classification, PII, fetching/scraping, etc.
Our take: frontier models are for reasoning. Specialized SLMs are going to increasingly handle everything else.
Benchmarks if you’re interested in checking out what we’re doing for specific adtech tasks, for example - zerogpu.ai/benchmarks/iab-cl…
ZeroGPU AI retweeted
For normie prompts, small and nano models are the future
Almost every major electronics company (Apple, Samsung, LG) will go this route imo
That’s why I was a big fan of what @ZeroGPU_AI is doing here
cc: @its_maddy_a
(Not a paid post)
ZeroGPU AI retweeted
We are constantly running evals on our models to improve - this is our ad tech model. It outperforms GPT 5.4 Nano being <100M params.
zerogpu.ai/benchmarks/iab-cl…
ZeroGPU AI retweeted
“I think we are getting brainwashed.”
@Benioff said this on @theallinpod.
“We’re using $300M of @AnthropicAI this year… the vast majority of those tokens don’t need to go to Anthropic.”
Some tasks need @claudeai .
Some need @OpenAI .
Most need smaller, cheaper, faster models like @ZeroGPU_AI
@Benioff believes in what we do - @salesforcevc should take a look.
zerogpu.ai/
ZeroGPU AI retweeted
Excited to see @ZeroGPU_AI featured in @adexchanger.
Most ad tech AI work doesn’t need a giant frontier model.
It needs fast, accurate, specialized models for classification, extraction, and IAB mapping at scale.
That’s what we built at ZeroGPU.
adexchanger.com/ai/large-lan…
ZeroGPU AI retweeted
Paying for a frontier LLM to do every task is like paying a rocket scientist to fetch your mail👨🔬🐕📩
That's what Small Language Models are for. Save LLMs for the high-level reasoning. Use our SLMs for everything else.
Save 50%+ & reduce latency by 10x
zerogpu.ai
