Quickstart
1
Get an API
Get an API key or download weights
2
Pick model
Pick Mini for cloud or Nano for edge
3
Choose workload
Choose Reasoning or Standard per workload
4
Plug in your tools
5
Ship to production
Trinity Models
Reliable intelligence you can run anywhere.
Open weights and a production API for multi-turn conversations, tool use, and structured outputs. Pick your size based on where you deploy. Capabilities stay consistent.
Models
All Trinity variants share the same skill profile. Choose the footprint that fits your infrastructure.
Trinity Nano〔6B, 1B active〕
Edge, embedded, and privacy-critical
Runs fully local on consumer GPUs, edge servers, and mobile-class devices. Tuned for offline operation and latency-sensitive voice or UI loops.
Deploy on: on-device, edge servers, mobile, kiosks
Active parameters: 1B per token
Context window: 128K tokens
Variants: Standard and Reasoning
Trinity Mini〔26B, 3B active〕
Cloud and on-prem production
Serve customer-facing apps, agent backends, and high-throughput services in your cloud or VPC.
Deploy on: AWS, GCP, Azure, on-prem (vLLM, SGLang, llama.cpp)
Active parameters: 3B per token
Context window: 128K tokens
Variants: Standard and Reasoning
Faster and lower cost. Best for routing, retrieval, summarization, classification, extraction, and straightforward tool calls. Same APIs, schemas, prompts. Switch per request.
Enhanced stepwise planning and long‑horizon tool use. Best for multi‑step workflows, complex coding, and analysis. Slightly higher latency and cost per token.
Capabilities
- Agent reliability: Accurate function selection, valid parameters, schema-true JSON, graceful recovery when tools fail.
- Coherent multi-turn conversation: holds goals and constraints over long sessions; follows up naturally without re-explaining context.
- Structured outputs: JSON schema adherence; native function calling and tool orchestration.
- Same skills across sizes: Move workloads between edge and cloud without rebuilding prompts or playbooks.
- Super efficient attention: Reduced cost of running at long contexts compared to other models.
- Strong context utilization: Makes full use of large input docs for more relevant, grounded responses.
Technical Overview
Sparse mixture of experts with highly efficient attention for lower latency and lower cost.
- Trinity Mini: 26B total / 3B active per token
- Trinity Nano: 6B total / 1B active per token
- Curated, high‑quality data across diverse domains with strict filtering and classification pipelines.
- Heavy synthetic augmentation to cover edge cases, tool calling, schema adherence, error recovery, preference following, and voice‑friendly styles.
- Evaluation focuses on tool reliability, long‑turn coherence, and structured output accuracy.
Sparse mixture of experts with highly efficient attention for lower latency and lower cost.
- 128K token context window
- Structured outputs with JSON schema adherence
- Native function calling and tool orchestration
Read the Technical Docs
Deploy Your Way
FAQs
Yes. Both variants accept the same prompts and tools.
Provide a schema and the model will produce schema‑true outputs. See the structured outputs guide.
Tell the model exactly how brief you want it to be. See the examples above.
