API cost decision in 10 seconds
GPT-5.1-Codex-Max vs MiniMax M2
Pick MiniMax M2 for lower cost; pick GPT-5.1-Codex-Max only if the larger context window matters more.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick MiniMax M2 for lower cost; pick GPT-5.1-Codex-Max only if the larger context window matters more.
On the standard 1M input plus 500K output workload, MiniMax M2 is estimated at $0.76 vs $6.25 for GPT-5.1-Codex-Max, saving $5.5 (87.9% lower).
Cost-first pickMiniMax M2
Context-first pickGPT-5.1-Codex-Max
Sample savings$5.587.9%
10x traffic gap$54.95
GPT-5.1-Codex-Max has more context, but MiniMax M2 saves $5.5 on the standard workload. At 10x that traffic, the same price gap is about $54.95. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
MiniMax M2 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | GPT-5.1-Codex-Max | MiniMax M2 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiniMax M2 | $11.25 | $1.77 |
| Balanced workload | 1M input + 1M output | MiniMax M2 | $11.25 | $1.25 |
| Output-heavy chatbot | 1M input + 5M output | MiniMax M2 | $51.25 | $5.25 |
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
MiniMax M2 has the lower input price, MiniMax M2 has the lower output price, and GPT-5.1-Codex-Max offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $6.25 for GPT-5.1-Codex-Max and $0.76 for MiniMax M2.
Choose GPT-5.1-Codex-Max when you care most about larger context window.
Choose MiniMax M2 when you care most about lower input-token price, and lower output-token price.
| Feature | GPT-5.1-Codex-Max (OpenAI) | MiniMax M2 (MiniMax) |
|---|---|---|
| Input Price prompt tokens per 1M | $1.25 | $0.26 |
| Completion Price per 1M tokens | $10 | $1 |
| Sample Workload Cost 1M input + 500K output | $6.25 | $0.76 |
| Context Window | 400K | 204.8K |
| Release Date | 2025-12-04 | 2025-10-23 |
GPT-5.1-Codex-Max is OpenAI’s latest agentic coding model, designed for long-running, high-context software development tasks. It is based on an updated version of the 5.1 reasoning stack and trained on agentic...
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | MiniMax M2 | On the standard 1M input plus 500K output workload, MiniMax M2 is estimated at $0.76 vs $6.25 for GPT-5.1-Codex-Max, saving $5.5 (87.9% lower). |
| High-volume input processing | MiniMax M2 | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | MiniMax M2 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-5.1-Codex-Max | A larger context window leaves more room for retrieved passages and source files. |