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Lambda is a 12-year-old San Francisco company best known for offering graphics processing units (GPUs) on demand as a service to machine learning researchers and AI model builders and trainers.
But today it’s taking its offerings a step further with the launch of the Lambda Inference API (application programming interface), which it claims to be the lowest-cost service of its kind on the market, allowing enterprises to deploy AI models and applications into production for end-users without worrying about procuring or maintaining compute.
The launch compliments its existing focus on providing GPU clusters for training and fine-tuning machine learning models.
“Our platform is fully verticalized, meaning we can pass dramatic cost savings to end users compared to other providers like OpenAI,” said Robert Brooks, Lambda’s Vice President of Revenue, in a video call interview with VentureBeat. “Plus, there are no rate limits inhibiting scaling, and you don’t have to talk to a salesperson to get started.”
In fact, as Brooks told VentureBeat, developers can head over to Lamda’s new Inference API webpage, generate an API key, and get started in less than 5 minutes.
Lambda’s Inference API supports leading-edge models such as Meta’s Llama 3.3 and 3.1, Nous’s Hermes-3, and Alibaba’s Qwen 2.5, making it one of the most accessible options for the machine learning community. The full list is available here and includes:
- deepseek-coder-v2-lite-instruct
- dracarys2-72b-instruct
- hermes3-405b
- hermes3-405b-fp8-128k
- hermes3-70b
- hermes3-8b
- lfm-40b
- llama3.1-405b-instruct-fp8
- llama3.1-70b-instruct-fp8
- llama3.1-8b-instruct
- llama3.2-3b-instruct
- llama3.1-nemotron-70b-instruct
- llama3.3-70b
Pricing begins at $0.02 per million tokens for smaller models like Llama-3.2-3B-Instruct and scales up to $0.90 per million tokens for larger, state-of-the-art models such as Llama 3.1-405B-Instruct.
As Lambda co-founder and CEO Stephen Balaban put it recently on X, “Stop wasting money and start using Lambda for LLM Inference,” publishing a graph showing its per-token cost for serving up AI models through inference compared to other rivals in the space.
Furthermore, unlike many other services, Lambda’s pay-as-you-go model ensures customers only pay for the tokens they use, eliminating the need for subscriptions or rate-limited plans.
Closing the AI loop
Lambda has a decade-plus history of supporting AI advancements with its GPU-based infrastructure.
From offering hardware solutions to its training and fine-tuning capabilities, the company has built a reputation as a reliable partner for enterprises, research institutions, and startups.
“Understand that Lamda has been deploying GPUs for well over a decade to our user base, and so we’re sitting on literally tens of thousands of Nvidia GPUs, and some of them can be from older life cycles and newer life cycles, allowing us to still get maximum utility out of those AI chips for the wider ML community, at reduced costs as well.” Brooks explained. “With the launch of Lambda Inference, we’re closing the loop on the full-stack AI development lifecycle. The new API formalizes what many engineers had already been doing on Lambda’s platform—using it for inference—but now with a dedicated service that simplifies deployment.”
One of Lambda’s distinguishing features is its deep reservoir of GPU resources. Brooks noted, “Lambda has deployed tens of thousands of GPUs over the past decade, allowing us to offer cost-effective solutions and maximum utility for both older and newer AI chips.”
This GPU advantage enables the platform to support scaling to trillions of tokens monthly, providing flexibility for developers and enterprises alike.
Open and flexible
Lambda is positioning itself as a flexible alternative to cloud giants by offering unrestricted access to high-performance inference.
“We want to give the machine learning community unrestricted access to rate-limited inference APIs. You can plug and play, read the docs, and scale rapidly to trillions of tokens,” Brooks added.
The API supports a range of open-source and proprietary models, including popular instruction-tuned Llama models.
The company has also hinted at expanding to multimodal applications, including video and image generation, in the near future.
“Initially, we’re focused on text-based LLMs, but soon we’ll expand to multimodal and video-text models,” Brooks said.
Serving devs and enterprises with privacy and escurity
The Lambda Inference API targets a wide range of users, from startups to large enterprises in media, entertainment, and software development.
These industries are increasingly adopting AI to power applications like text summarization, code generation, and generative content creation.
“There’s no retention or sharing of user data on our platform. We act as a conduit for serving data to end users, ensuring privacy,” Brooks emphasized, reinforcing Lambda’s commitment to security and user control.
As AI adoption continues to rise, Lambda’s new service is poised to attract attention from businesses seeking cost-effective solutions for deploying and maintaining AI models. By eliminating common barriers such as rate limits and high operating costs, Lambda hopes to empower more organizations to harness the potential of AI.
The Lambda Inference API is available now, with detailed pricing and documentation accessible through Lambda’s website.
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