MiniMax M2-her is cheaper than GPT-5.3-Codex at $0.3/M vs $1.75/M input tokens.
| Spec | GPT-5.3-Codex | MiniMax M2-her |
|---|---|---|
| Input price | $1.75/M tokens | $0.3/M tokens |
| Output price | $14/M tokens | $1.2/M tokens |
| Context window | 400K tokens | 66K tokens |
| Released | Feb 2026 | Jan 2026 |
Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, bigger context window, major provider backing.
MiniMax M2-her costs 12x less per token.
MiniMax M2-her is cheaper on both — 5.8× input, 12× output
MiniMax M2-her uses 7.5x more transitions
MiniMax M2-her is cheaper than GPT-5.3-Codex at $0.3/M vs $1.75/M input tokens.
| Spec | GPT-5.3-Codex | MiniMax M2-her |
|---|---|---|
| Input price | $1.75/M tokens | $0.3/M tokens |
| Output price | $14/M tokens | $1.2/M tokens |
| Context window | 400K tokens | 66K tokens |
| Released | Feb 2026 | Jan 2026 |
Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, bigger context window, major provider backing.
MiniMax M2-her costs 12x less per token.
MiniMax M2-her is cheaper on both — 5.8× input, 12× output
MiniMax M2-her uses 7.5x more transitions