OpenAI: GPT-5 Codex vs MiniMax: MiniMax M2: Which AI Model Is Better?
Updated March 24, 2026· Based on independent benchmark data
Quick Verdict
MiniMax: MiniMax M2 leads in intelligence with a score of 49.6 vs 44.6. MiniMax: MiniMax M2 is 4.9x cheaper at $0.26/1M tokens vs $1.25/1M. For speed, OpenAI: GPT-5 Codex wins at 170 tok/s vs 44 tok/s.
Head-to-Head Comparison
| Metric | OpenAI: GPT-5 Codex | MiniMax: MiniMax M2 |
|---|---|---|
| Intelligence Score | 44.6 | 49.6 |
| Coding Score | 38.9 | 41.9 |
| Math Score | 98.7 | N/A |
| Speed (tok/s) | 170 tok/s | 44 tok/s |
| Latency (TTFT) | 4.79s | 2.03s |
| Input Price / 1M tokens | $1.25 | $0.26 |
| Output Price / 1M tokens | $10 | $1.00 |
| Context Window | 400K | 197K |
| Max Output Tokens | 128K | 197K |
| Input Modalities | Text + Image | Text |
| Output Modalities | Text | Text |
| Free Tier | No | No |
Detailed Analysis
Intelligence & Quality
MiniMax: MiniMax M2 outperforms OpenAI: GPT-5 Codex on the Artificial Analysis intelligence index with a score of 49.6 compared to 44.6. For coding tasks, MiniMax: MiniMax M2 has the edge with a coding score of 41.9 vs 38.9.
Speed & Latency
OpenAI: GPT-5 Codex generates output significantly faster at 170 tok/s compared to MiniMax: MiniMax M2's 44 tok/s, making it 3.9x faster for streaming responses. Time to first token is 2.03s for MiniMax: MiniMax M2 vs 4.79s for OpenAI: GPT-5 Codex, which affects perceived responsiveness in interactive applications.
Pricing
MiniMax: MiniMax M2 is more affordable at $0.26/1M input tokens ($1.00/1M output), while OpenAI: GPT-5 Codex costs $1.25/1M input ($10/1M output). That makes OpenAI: GPT-5 Codex 4.9x more expensive per token, which can add up significantly at scale. For a typical workload of 100 requests per day at 2,000 tokens each, OpenAI: GPT-5 Codex would cost approximately $7.50/month vs $1.53/month for MiniMax: MiniMax M2 in input costs alone.
Context Window
OpenAI: GPT-5 Codex offers a larger context window at 400K tokens compared to MiniMax: MiniMax M2's 197K. This means OpenAI: GPT-5 Codex can process roughly 200 pages of text in a single request vs 98 pages for MiniMax: MiniMax M2. For output length, MiniMax: MiniMax M2 can generate up to 197K tokens per response vs 128K for OpenAI: GPT-5 Codex.
Best Use Cases
Choose OpenAI: GPT-5 Codex when you need faster output (170 tok/s), larger context window (400K). Choose MiniMax: MiniMax M2 when you need higher intelligence (49.6), stronger coding performance (41.9), lower cost.
Choose OpenAI: GPT-5 Codex if:
- ✓You need faster throughput (170 tok/s vs 44 tok/s)
- ✓You need a larger context window (400K vs 197K)
- ✓You need image understanding (Supports image input)
Choose MiniMax: MiniMax M2 if:
- ✓You need higher intelligence (score: 49.6 vs 44.6)
- ✓You prioritize coding performance (score: 41.9 vs 38.9)
- ✓You want lower latency (2.03s vs 4.79s TTFT)
- ✓Budget is a concern ($0.26/1M vs $1.25/1M)
Frequently Asked Questions
Is OpenAI: GPT-5 Codex better than MiniMax: MiniMax M2 for coding?
MiniMax: MiniMax M2 scores higher on coding benchmarks (41.9 vs 38.9), making it the better choice for programming tasks.
Which is cheaper, OpenAI: GPT-5 Codex or MiniMax: MiniMax M2?
MiniMax: MiniMax M2 is cheaper at $0.26/1M input tokens vs $1.25/1M for OpenAI: GPT-5 Codex.
Is OpenAI: GPT-5 Codex faster than MiniMax: MiniMax M2?
OpenAI: GPT-5 Codex is faster, producing output at 170 tok/s compared to MiniMax: MiniMax M2's 44 tok/s.
Can OpenAI: GPT-5 Codex process images?
Yes, OpenAI: GPT-5 Codex supports image input. MiniMax: MiniMax M2 does not support image input.
Which has a larger context window, OpenAI: GPT-5 Codex or MiniMax: MiniMax M2?
OpenAI: GPT-5 Codex has a larger context window at 400K compared to MiniMax: MiniMax M2's 197K.
Should I use OpenAI: GPT-5 Codex or MiniMax: MiniMax M2?
It depends on your priorities. MiniMax: MiniMax M2 scores higher on intelligence (49.6), but OpenAI: GPT-5 Codex may be better for specific use cases like budget-conscious projects or speed-critical applications.
Related Comparisons
Benchmark data by Artificial Analysis
Data last synced: March 24, 2026