Baseten Loops is now GA, and serverless.
Teams at @AmbienceAI, @datadoghq, and @LangChain use the Loops SDK for SFT and RL training to build durable intelligence.
Serverless Loops includes:
- Always-warm infra that eliminates cold starts
- Pay-per-token pricing for training and sampling
- One-click deployment from your trained checkpoint to production inference
- Model-specific numerical validation, with a focus on reducing mismatch between training and sampling
You bring the data, reward functions, and training logic.
We handle the infrastructure.
You always own the weights.
Learn more:
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Inference, training, routing, governance, and sandboxes are the building blocks of every AI product today.
We’ve learned a lot from our customers about what it takes to build that system well: @OpenEvidence trains models that outperform the closed frontier, then serves them on Dedicated Inference. @datadoghq post-trains on Loops. @Opendoor routes every AI request across the company through Grid.
This week we have three launches expanding our inference platform:
- Grid: gateway, intelligent router, and guardrails for every model your company uses (launching tomorrow)
- Sandboxes: stateful, VM-isolated environments for agents that scale to thousands of instances in seconds (launching Thursday)
- Loops: serverless SFT and RL on open-weight models, deployable straight to Dedicated Inference (GA Friday)
@amiruci, @saimaddali, @paul_s3i, and @oneill_c break down what we're launching. You might notice the visuals have a new look as well.
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Today we’re announcing the Baseten Environment Network, a group of the best RL environment companies that will help our customers build custom environments for post-training.
The Network extends our applied research capacity, helping more customers build environments around their own tasks, data, and feedback.
Partners work directly with customers to create the environments, while we continue to handle model training and production deployment.
Learn more:
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Today we’re releasing two decision models, elephant-1 (9B) and mammoth-1 (27B), trained by the @baselabs team, available for free for one week on our Model APIs.
mammoth-1 is #1# on the Jev Decision Index and elephant-1 is tied for #1# on the Artificial Analysis Decision Index.
It’s a new model, but more importantly, this is an open-source model you can access, deploy, and post-train on Baseten (or wherever you do your best work).
The free week ends 10/27/26 at 11:59 PM PT. Try it and let us know what you think.
Try mammoth-1 here:
Try elephant-1 here:
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Progress that moves the frontier is almost never made alone.
We’re thrilled to announce All-Gather, our first-ever research conference that will bring together the brightest minds in research, founders, and engineers to join us for a day of debate and exchange.
Come hear Noam Brown, Sarah Guo, Horace He, Bryan Catanzaro, Jerry Tworek, Sabri Eyuboglu, Tuhin Srivastava, and many more debate pre-training, post-training, infrastructure, model performance, and emerging fields. Join us on November 18th in San Francisco.
Research has been part of our DNA from our early days of optimizing open-source models through our recent launch of Base Labs. We’ve grown with the open ecosystem, and we’re excited to keep building alongside it.
Space is limited, but we’d love you to join us. Apply here:
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Baseten joined the @OpenAI B2B marketplace today as one of the first open-model inference providers.
The best AI companies are already running a mix of closed and open models at huge scale. We're excited to give OpenAI enterprise customers the ability to use open models powered by Baseten natively within Codex and through the Responses API.
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RL teaches models to work longer, but reasoning is dependent on domain-specific post-training.
Baseten's Head of Model Training @oneill_c sat down with @dwarkesh_sp to explain horizon generalization and what's next at the frontier.
Full episode here:
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"Your user data, your signal from these models, the improvements to these models themselves will become the core IP of every company in the world."
@tuhinone sat down with @alexeheath to talk about the future of inference, Base Labs, bringing Blaxel on board, and why every company will want to own its intelligence.
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Baseten’s CEO on why every company will want to own its AI / @tuhinone on the rise of AI agents, the demand for inference, and building a new kind of hyperscaler.
Lately, I’ve been spending a lot of time thinking about the AI inference market and how big it could get. Agents like Muse, Instinct, Town, and Grok Bot aggressively use browsers, run their own computers, and burn through far more tokens than a traditional chatbot.
As more people put them to work (Muse is number two in the App Store), the demand for inference, or the computing needed to run these models, should grow enormously.
Tuhin and I discuss the rise of agents using browsers and virtual machines to get things done, and @baseten's recent acquisition to help power that shift.
We also talk about the data center backlash, why companies are embracing Chinese open models, his plans for Baseten’s new research lab, and why he thinks inference becomes the only market left after AGI.
Timestamps:
00:00 What Is AI Inference?
06:05 Competing With the Cloud Giants
09:24 Why Companies Want to Own Their AI
15:30 Building Baseten Before the AI Boom
23:45 DeepSeek and the Race for Open AI Models
29:32 Baseten’s Growth and Expansion
33:05 AI Agents and the Blaxel Acquisition
38:32 Data Centers and the AI Backlash
43:25 What Happens to Inference After AGI?
45:12 When AI Agents Become Customers
Thanks to the show's premier sponsors: @Atlassian, @meetgranola, and @mercury.
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We sat down with the team at @elise_ai to talk about why they're betting on specialized, post-trained models, how to evaluate them, and what it takes to run them in production.
We're doing round two at SF Tech Week on October 7th. @oneill_c, our Co-Head of Training, is doing a fireside chat with Mario Martone, who leads applied research at EliseAI, on fine-tuning and continuous retraining for housing and healthcare.
Join us for drinks and Mario Kart afterward!
RSVP here:
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We're proud to partner with the team at @p0 to power fast, accurate, low-cost web search for open-weight models via Baseten Grounded Inference.
Parallel Search is now available in @baseten.
Pick Parallel for the most accurate web search at the lowest price. Your agents will thank you for the upgrade.
We're excited to work with @youdotcom to offer web search with open-weight models at a fraction of the price of closed frontier labs.
We're partnering with @baseten to make the case for open-weight models.
Paired with @youdotcom web search, they're a real alternative to closed models at a fraction of the price.
Already calling Baseten's Chat Completions endpoint? Add one line to your tools array:
tools=[{"type": "baseten__you__search"}]
Same model, same request. No search vendor to wire up, no retry path, no resending a growing context every turn.
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Excited to partner with @KeenableAI to power open-model web search via Baseten Grounded Inference!
Keenable Search is now native to @baseten
Models search, read, and reason inside one inference request.
Excited to partner with the @ExaAILabs and @ExaDevelopers teams to help us power Baseten Grounded Inference, our new server-side web search tool for open-weight models.
Use Exa with Baseten!
Add Exa's web search to any open-source model using Baseten Hosted Tools.
How to install 👇
Many of our customers run workloads with speaker attribution, with the strictest demands on both quality and speed.
We partnered with the team at @pyannoteAI to deliver both: some of the highest-quality diarization models on the market, with 3.2x higher throughput and 9.6x lower latency.
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Excited to see Vercel push the open-weights ecosystem forward. 💚
v0 is now model-agnostic.
Frontier models, cheap models, open models, and fast models, all from Vercel's AI Gateway.
Choose from Claude, GPT, Kimi, GLM, Grok, DeepSeek and more to build your apps.
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Open models on Baseten can now search the web, within the inference path, thanks to our partnership with Exa, Keenable, Parallel, and A lot more to come here soon.
Web search is now a first-class citizen for open models, only on Baseten.
Baseten Hosted Tools and Baseten Grounded Inference bring real-time, server-side web search to your favorite open models via multiple providers: @youdotcom, @p0, @KeenableAI, and @ExaAILabs.
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Happy to start collaborating with @baselabs from @baseten and @GoodfireAI to push safety and interpretability for open models.
As open-source models catch up in performance to frontier models, the community at large have a great opportunity to establish a common practice for effective safety, security and interpretability research.
Some past discussions confused “open” with “unmonitored”. On the contrary, an open model provides much more tooling and visibility for safety research from a broader audience, which has led to a lot of the safety and security techniques we use today.
Linux is a great example of this: open-source and secure deployment are not only compatible but heavily intertwined, as a properly secure system needs an extensive feedback loop of finding and fixing vulnerabilities.
We're excited to share more soon.
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Safety is not just for closed models. The closed frontier labs are a canary in the coal mine for what is coming at scale. They give us a glimpse into the future and a window to harden our systems and prepare for abundant intelligence, with all the risks that come along with it. The OpenAI agent swarm attack on Hugging Face is the kind of failure we need to prepare for as open-source models catch up. The providers serving those models (such as Baseten) have a big role in establishing what safety and monitoring standards look like.
We’re proud to be taking the lead on this at @baselabs with our collaborators @huggingface and @GoodfireAI. We’re developing safety research in the open and building it directly into Baseten’s inference infrastructure, with the aim of making it available to all our customers. This includes training models to follow explicit policies, detecting failures at runtime, and connecting those signals to controls that can intervene.
We invite others in the open-source ecosystem to join us in building the tools and standards we’ll all need.
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Until now, adding web search to open-source models meant hand-wiring orchestration, managing separate keys, and paying latency taxes on every round trip.
Today, we're solving that. We're excited to introduce Baseten Hosted Tools and Baseten Grounded Inference to bring real-time web search server-side to open models running on Baseten through a single configuration:
- 15% lower latency compared to client-side execution
- No extra vendor key required
- Zero orchestration
We're launching this preview version with four leading web search partners, @ExaAILabs, @KeenableAI, @p0, and @youdotcom.
Get frontier-level web search parity for your open-weight models. More here:
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We believe openness to be an advantage for AI safety. Openness provides more visibility into the behavior of models and, most importantly, greater means of turning safety research into actionable and transparent controls than closed-source.
This is why Baseten and Base Labs are building a stronger safety and security standard for open models, with the launch of our safety infrastructure. Base Labs will develop and publish methods for training and monitoring open models, and Baseten will integrate that work into its deployment infrastructure, live at runtime, and offer this work as a managed service. This will be a standard that is transparent and built into how our models are trained and deployed.
We invite the open-source community to contribute, and are proud to partner with @huggingface and @GoodfireAI to bring this vision to fruition.
Together, we are building an ecosystem of open models that are safe and accessible to all.
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