Model comparison
Coder Large vs Trinity Mini
Compare Coder Large and Trinity Mini: input/output $/Mtoken, context window, modalities, and license. OpenRouter-synced pricing.
Arcee Ai
Coder Large
Coder‑Large is a 32 B‑parameter offspring of Qwen 2.5‑Instruct that has been further trained on permissively‑licensed GitHub, CodeSearchNet and synthetic bug‑fix corpora. It suppor
Arcee Ai
Trinity Mini
Trinity Mini is a 26B-parameter (3B active) sparse mixture-of-experts language model featuring 128 experts with 8 active per token. Engineered for efficient reasoning over long con
| Metric | Coder Large | Trinity Mini |
|---|---|---|
| Provider | Arcee Ai | Arcee Ai |
| Context window | 32,768 | 131,072 |
| Input $/Mtok | $0.500 | $0.045 |
| Output $/Mtok | $0.800 | $0.150 |
| Modalities | text | text |
| License | closed | open-weights |
Quick take
On input price, Trinity Mini is cheaper at $0.045/Mtok. For context window, Trinity Mini leads with 131,072 tokens.
Pick based on your workload: high-volume cheap inference vs long-document / agent loops. Enterprise DNA can wire either model into Omni with evals, secrets, and job orchestration.