GPT-5.1-Codex-Mini is $0.21 cheaper per 1M input tokens (45.1% lower; 1.82x difference).
API cost decision in 10 seconds
Qwen3 235B A22B vs GPT-5.1-Codex-Mini
Pick GPT-5.1-Codex-Mini when budget and context both matter.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick GPT-5.1-Codex-Mini when budget and context both matter.
On the standard 1M input plus 500K output workload, GPT-5.1-Codex-Mini is estimated at $1.25 vs $1.36 for Qwen3 235B A22B, saving $0.11 (8.4% lower).
Cost-first pickGPT-5.1-Codex-Mini
Context-first pickGPT-5.1-Codex-Mini
Sample savings$0.118.4%
10x traffic gap$1.15
GPT-5.1-Codex-Mini is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $1.15. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Cost winner changes by workload shape: input-heavy / RAG favors GPT-5.1-Codex-Mini, balanced workload favors GPT-5.1-Codex-Mini, and output-heavy chatbot favors Qwen3 235B A22B.
| Workload shape | Token mix | Better pick | Qwen3 235B A22B | GPT-5.1-Codex-Mini |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | GPT-5.1-Codex-Mini | $3.19 | $2.25 |
| Balanced workload | 1M input + 1M output | GPT-5.1-Codex-Mini | $2.27 | $2.25 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3 235B A22B | $9.55 | $10.25 |
Qwen3 235B A22B is $0.18 cheaper per 1M output tokens (9% lower; 1.1x difference).
GPT-5.1-Codex-Mini has 268.93K more context (3.05x larger).
GPT-5.1-Codex-Mini is $0.11 cheaper on the standard workload (8.4% lower).
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
GPT-5.1-Codex-Mini has the lower input price; Qwen3 235B A22B has the lower output price; GPT-5.1-Codex-Mini offers the larger context window. For the 1M input plus 500K output sample, GPT-5.1-Codex-Mini is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.36 for Qwen3 235B A22B and $1.25 for GPT-5.1-Codex-Mini.
Choose Qwen3 235B A22B when you care most about lower output-token price.
Choose GPT-5.1-Codex-Mini when you care most about lower input-token price, and larger context window.
- On the standard 1M input plus 500K output workload, GPT-5.1-Codex-Mini is estimated at $1.25 vs $1.36 for Qwen3 235B A22B, saving $0.11 (8.4% lower).
- GPT-5.1-Codex-Mini is $0.11 cheaper on the standard workload (8.4% lower).
- GPT-5.1-Codex-Mini is $0.21 cheaper per 1M input tokens (45.1% lower; 1.82x difference).
- Qwen3 235B A22B is $0.18 cheaper per 1M output tokens (9% lower; 1.1x difference).
- GPT-5.1-Codex-Mini has 268.93K more context (3.05x larger).
| Feature | Qwen3 235B A22B (Qwen) | GPT-5.1-Codex-Mini (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.455 | $0.25 |
| Completion Price per 1M tokens | $1.82 | $2 |
| Sample Workload Cost 1M input + 500K output | $1.36 | $1.25 |
| Context Window | 131.07K | 400K |
| Release Date | ||
| Popularity | #131 | #141 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | GPT-5.1-Codex-Mini | On the standard 1M input plus 500K output workload, GPT-5.1-Codex-Mini is estimated at $1.25 vs $1.36 for Qwen3 235B A22B, saving $0.11 (8.4% lower). |
| High-volume input processing | GPT-5.1-Codex-Mini | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen3 235B A22B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-5.1-Codex-Mini | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
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Open OpenAI modelsQwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...
GPT-5.1-Codex-Mini is a smaller and faster version of GPT-5.1-Codex