| Signal | GPT-5 Codex | Delta | MiniMax M2.5 |
|---|---|---|---|
Capabilities | 71 | +14 | |
Context window size | 89 | +5 | |
Output Capacity | 85 | -3 | |
Pricing Tier | 10 | +9 | |
Recency | 100 | -- | |
Versatility | 50 | +17 | |
| Overall Result | 4 wins | of 6 | 1 wins |
30
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OpenAI
MiniMax
MiniMax M2.5 saves you $535.50/month
That's $6426.00/year compared to GPT-5 Codex at your current usage level of 100K calls/month.
| Metric | GPT-5 Codex | MiniMax M2.5 | Winner |
|---|---|---|---|
| Overall Score | 62 | 54 | GPT-5 Codex |
| Rank | #43 | #79 | GPT-5 Codex |
| Quality Rank | #43 | #79 | GPT-5 Codex |
| Adoption Rank | #43 | #79 | GPT-5 Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 197K | GPT-5 Codex |
| Pricing | $1.25/$10.00/M | $0.29/$1.20/M | -- |
| Signal Scores | |||
| Capabilities | 71 | 57 | GPT-5 Codex |
| Context window size | 89 | 84 | GPT-5 Codex |
| Output Capacity | 85 | 88 | MiniMax M2.5 |
| Pricing Tier | 10 | 1 | GPT-5 Codex |
| Recency | 100 | 100 | GPT-5 Codex |
| Versatility | 50 | 33 | GPT-5 Codex |
GPT-5 Codex has a moderate advantage with a 7.900000000000006-point lead in composite score. It wins on more signal dimensions, but MiniMax M2.5 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-5 Codex
Marginally better benchmark scores; both are excellent
Best for Cost
MiniMax M2.5
87% lower pricing; better value at scale
Best for Reliability
GPT-5 Codex
Higher uptime and faster response speeds
Best for Prototyping
GPT-5 Codex
Stronger community support and better developer experience
Best for Production
GPT-5 Codex
Wider enterprise adoption and proven at scale
by OpenAI
GPT-5 Codex currently scores higher (62 vs 54), but the best choice depends on your specific use case, budget, and requirements.
GPT-5 Codex is ranked #43 and MiniMax M2.5 is ranked #79. Rankings are based on a composite score from multiple signals including benchmarks, community sentiment, and adoption metrics.
Compare the detailed pricing breakdown above to see which model offers better value for your usage pattern.