OneTriangle GTM brain
OneTriangle provides optimized open-model inference to AI teams running long-context workloads.
category
LLM inference optimizationmarket profile
- text: Long prompts make prefill an important contributor to latency and inference spend.
- text: Hosted inference competes with both managed model APIs and internally operated GPU serving.
personas
- title: Head of AI infrastructurepains:
- Long context drives slow time to first token and expensive GPU usage
- Must evaluate whether a new serving path preserves model quality
- title: ML platform engineerpains:
- Operating open-weight models consumes GPU and serving engineering time
- Integrating a new endpoint must fit an existing application
icp
- text: AI application companies with production LLM traffic and long prompts or agentic workflows are a strong fit; size is not specified.
- text: Teams deploying open-weight Llama, Qwen, Mistral, Gemma or DeepSeek models on managed or dedicated GPU infrastructure.
message pillars
- text: Reduce latency and cost through cross-model KV cache transfer.
- text: Use smaller models for prefill and larger models for decoding.
- text: Avoid managing the GPU serving stack internally.
objections
- objection: Will cross-model cache transfer degrade answer quality?response: Ask for held-out quality results and model-pair benchmarks; the company says ordinary prefill is the fallback when a pair fails its gates.
- objection: Will moving inference require major application changes?response: Validate the endpoint and deployment requirements in a pilot; the site describes a one-line configuration change for serviced models.
competitors
- name: Together AIwhy: Offers managed open-model inference and dedicated endpoints.
- name: Fireworks AIwhy: Managed inference platform for open models and production workloads.
influencers
- name: Hannah Chungurl: https://www.linkedin.com/posts/hannahchung1_onetriangle-yc-s26-is-building-the-cheapest-activity-7496242168534163458-rmuowhy: CEO discussing inference and the company launch.
keywords
- LLM inference optimization
- time to first token
- KV cache transfer
- long context inference
- GPU inference cost
- open model serving
voice
- technical
- benchmark-led
- direct
signals
- text: A team is deploying long-context agents and complains about first-token latency or GPU spend.
- text: An organization is migrating to open-weight models or expanding dedicated GPU endpoints.
stack
- Llama
- Qwen
- Mistral
- Gemma
- DeepSeek
pricing
model: unknown
motion
sales_ledchannels
- X
- technical research
- demo
confidence
mediumFounders
- name: Hannah Chungtitle: Founder/CEOrole: CEObio: MIT CS & Econ → @Virtu Financial → Fastest Inference @OneTriangle
- name: Medha Venkatapathytitle: Founder/CTOrole: CTObio: Hi! I studied physics + cs at mit, and we're building the cheapest/fastest inference with KV cache transferability. In my free time, I like to bike and get lost.