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Arcee AI

Trinity Mini

Trinity Mini is a 26B-parameter sparse MoE from Arcee AI with 3B active parameters per forward pass. It handles function calling and multi-step agent workflows at low per-token cost, trained end-to-end in the United States. Your use is subject to Arcee AI's Terms & Privacy Policies.

Tool Use
Use with AI GatewayView docs
import { streamText } from 'ai'


const result = streamText({
  model: 'arcee-ai/trinity-mini',
  prompt: 'Why is the sky blue?'
})
Read docs
OverviewAPIAboutProvidersUptimeStatusSimilarFAQ

Copy link to headingPlayground

Try out Trinity Mini by Arcee AI. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.

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Trinity Mini

Copy link to headingProviders

Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.

Provider
Context
Max Output
Latency
Throughput
Input
Output
Cache
Web Search
Capabilities
ZDR
No Training
Release Date
Arcee AI
Legal:Terms•Privacy
131K131K
$0.04/M
$0.15/M
—
12/01/2025

Copy link to headingThroughput

P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the docs for more info.

Copy link to headingLatency

P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the docs for more info.

Copy link to headingUptime

Direct request success rate on AI Gateway and per-provider. Visit the docs for more info.

Copy link to headingMore models by Arcee AI

Model
Context
Latency
Throughput
Input
Output
Cache
Web Search
Capabilities
Providers
ZDR
No Training
Release Date
arcee-ai/trinity-large-thinking
262K
0.5s
232tps
$0.25/M
$0.90/M
—
arcee-ai logo
04/01/2026

Copy link to headingAbout Trinity Mini

Trinity Mini is a sparse mixture-of-experts model with 26B total parameters and 3B active per forward pass. The compact active footprint keeps inference costs low while the full parameter set provides enough capacity for function calling and multi-step agent workflows.

Arcee AI trained the model end-to-end in the United States, which teams cite for sovereignty and sourcing reviews.

Use https://docs.arcee.ai/language-models/trinity-mini-26b for weights and licensing detail.

Copy link to headingWhat To Consider When Choosing a Provider

  • Configuration: MoE routing keeps active parameters low per token, which helps cost at scale. At $0.045 per million input tokens and $0.15 per million output tokens, stress-test cost against quality on your traffic.
  • Zero Data Retention: AI Gateway does not currently support Zero Data Retention for this model. See the documentation for models that support ZDR.
  • Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.

Copy link to headingWhen to Use Trinity Mini

Best for

  • High-volume reasoning routes: Deployments where cost per token is a hard constraint
  • Structured inference tasks: Reverse engineering or deduction from partial observations
  • U.S. training provenance: Teams that need domestic-only training for policy or procurement

Consider alternatives when

  • Deepest large-model reasoning: Trinity Large Preview offers a larger parameter space at higher cost
  • Long-term enterprise SLA: This tier does not offer a fixed enterprise support contract
  • Tight latency budgets: Some workloads rule out even a compact MoE path

Copy link to headingConclusion

Trinity Mini pairs MoE efficiency with U.S. training provenance for teams that balance cost, control, and reasoning depth. Match spend to $0.045 and $0.15, then scale what works.