Side-by-side comparison
MiniMax M2-her vs Llama 3 70B Instruct
| MiniMax M2-her | Llama 3 70B Instruct | |
|---|---|---|
| Provider | MiniMax | Meta |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 65,536 | 8,192 |
| 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 | 0.5100 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 1.2000 | 0.7400 |
Frequently asked questions
Which is cheaper, MiniMax M2-her or Llama 3 70B Instruct?
Llama 3 70B Instruct is cheaper than MiniMax M2-her on a 50/50 input/output blend by about $0.125 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 Llama 3 70B Instruct?
MiniMax M2-her has the larger context window at 66k tokens versus 8k tokens for Llama 3 70B Instruct. That means MiniMax M2-her can ingest about 8.0x as much text per request.
What is the difference between MiniMax M2-her and Llama 3 70B Instruct?
MiniMax M2-her comes from MiniMax; Llama 3 70B Instruct comes from Meta. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.