Trusted by teams
building the future of india
We're building a new kind of language model — one that adapts how deeply it thinks based on how hard the problem is. Simple questions get fast answers. Complex reasoning gets more compute. Automatically.
Research SoonBuilt by a single founder, 0labs represents a relentless pursuit of technical excellence and focused execution. We operate with clarity of purpose to solve hard problems in how AI uses computation. There are no committees, no roadmap politics, no quarterly performance reviews shaping our research direction. Every architectural choice, every dataset, every evaluation answers one question: does this make the model think better with less? That focus is our edge against organizations with ten times our resources. We choose small sharp interventions over sprawling rewrites, and we measure progress in benchmarks, not headcount.
We believe India must develop its own intelligence infrastructure. 0labs is dedicated to building independent AI systems that don't waste compute, focusing on efficient resource allocation and adaptive architectures. Every model we ship is engineered for the realities of our region — constrained compute budgets, diverse languages, and use cases the global frontier consistently overlooks. By owning the stack from research to deployment, we make sure the intelligence powering Indian businesses, governments, and creators is built here, by us, on principles we control. Sovereignty over data is sovereignty over destiny, and that begins with the models that interpret it.
A post-hoc architectural enhancement framework designed to improve reasoning, instruction-following, and structured output quality in pretrained language models.
Applied to the 1B-parameter HRM-Text base. Reasoning, math, and instruction-following all moved up across the board.
Learn moreARC-Challenge
MATH 0-shot CoT
Instruction Following
Overall Capabilities
Fine-tuned variant achieved these gains using only 4.5M tokens — up to 10,000x less compute and 1,000x less data than comparable approaches.
Learn more10,000x
less training compute
A zero-shot variant keeps 100% of base model weights unchanged and uses no extra training data, preserving benchmarks immediately.
Learn moreweights preserved
base model intact
0labs
Launch agents that qualify leads, schedule meetings, answer questions, and update your stack automatically.
Text to Text model
Configure llms, connect tools, evaluate calls, and deploy workflows from a single orchestration layer. coming soon!
A single orchestration layer for configuring models, connecting tools, and shipping workflows.
coming soon!
For developers
Stream audio, trigger tools, observe calls, and deploy production-grade agents with a simple API. coming soon!
Soon docs
Preview · coming soon
Stream, evaluate, and deploy agents with a single primitive.
