Side-by-side comparison
MiniMax M2-her vs Coder Large
| MiniMax M2-her | Coder Large | |
|---|---|---|
| Provider | MiniMax | Arcee AI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 65,536 | 32,768 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | text-only | text-only |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.3000 | 0.5000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 1.2000 | 0.8000 |
Frequently asked questions
Which is cheaper, MiniMax M2-her or Coder Large?
Coder Large is cheaper than MiniMax M2-her on a 50/50 input/output blend by about $0.1 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, MiniMax M2-her or Coder Large?
MiniMax M2-her has the larger context window at 66k tokens versus 33k tokens for Coder Large. That means MiniMax M2-her can ingest about 2.0x as much text per request.
What is the difference between MiniMax M2-her and Coder Large?
MiniMax M2-her comes from MiniMax; Coder Large comes from Arcee AI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.