LLMTR × WorkDaddy: LLM Provider Integration (2026)

At a glance

Why run WorkDaddy agents on LLMTR in 2026

Tool calling, context size, and cost decide how well a provider drives an agent team. LLMTR brings 1 tool-calling models to WorkDaddy — enough to power the full loop of storefront edits, analytics queries, and content production — with 128K tokens of context at the top end for whole-codebase and long-report work. Because WorkDaddy is model-agnostic, you can route heavy reasoning to LLMTR’s strongest model and bulk work to its cheapest, inside one team.

Best LLMTR models for e-commerce agents (2026)

The current flagships from LLMTR in the WorkDaddy catalog, newest first:

• Trendyol 7B — Qwen instruction model for multilingual chat, reasoning, and tool use (33K context)

• Magibu 11B v8 — General-purpose chat model for instruction following, writing, and analysis (8K context)

• Sincap — General-purpose chat model for instruction following, writing, and analysis (128K context)

• MedGemma 4B — Multimodal model for analyzing text, images, documents, and rich media (8K context)

• Gemma 4 — Open Gemma instruction model for efficient chat and self-hosted deployments (33K context)

• Qwen3.6 35B-A3B — Open multimodal Qwen MoE for local agents that need vision, audio, and code (16K context)

How to connect LLMTR to WorkDaddy

WorkDaddy talks to LLMTR at llmtr.com via the @ai-sdk/openai-compatible adapter. Add your credential (typically LLMTR_API_KEY) in Settings → Models, pick a default model, and every agent can use it immediately — or add LLMTR as one engine among several and let tasks route to the best fit.

Featured models