gpt-oss-safeguard-20b is $0.005 cheaper per 1M input tokens (6.3% lower; 1.07x difference).
API cost decision in 10 seconds
Qwen3 32B vs gpt-oss-safeguard-20b
Pick Qwen3 32B when budget is the priority.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Qwen3 32B when budget is the priority.
On the standard 1M input plus 500K output workload, Qwen3 32B is estimated at $0.22 vs $0.22 for gpt-oss-safeguard-20b, saving $0.005 (2.2% lower).
Cost-first pickQwen3 32B
Context-first pickBoth models
Sample savings$0.0052.2%
10x traffic gap$0.05
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $0.05. 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-oss-safeguard-20b, balanced workload favors Qwen3 32B, and output-heavy chatbot favors Qwen3 32B.
| Workload shape | Token mix | Better pick | Qwen3 32B | gpt-oss-safeguard-20b |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | gpt-oss-safeguard-20b | $0.54 | $0.53 |
| Balanced workload | 1M input + 1M output | Qwen3 32B | $0.36 | $0.38 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3 32B | $1.48 | $1.57 |
Qwen3 32B is $0.02 cheaper per 1M output tokens (6.7% lower; 1.07x difference).
Both models report the same context window at 131.07K tokens.
Qwen3 32B is $0.005 cheaper on the standard workload (2.2% 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-oss-safeguard-20b has the lower input price; Qwen3 32B has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3 32B is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.22 for Qwen3 32B and $0.22 for gpt-oss-safeguard-20b.
Choose Qwen3 32B when you care most about lower output-token price.
Choose gpt-oss-safeguard-20b when you care most about lower input-token price.
- On the standard 1M input plus 500K output workload, Qwen3 32B is estimated at $0.22 vs $0.22 for gpt-oss-safeguard-20b, saving $0.005 (2.2% lower).
- Qwen3 32B is $0.005 cheaper on the standard workload (2.2% lower).
- gpt-oss-safeguard-20b is $0.005 cheaper per 1M input tokens (6.3% lower; 1.07x difference).
- Qwen3 32B is $0.02 cheaper per 1M output tokens (6.7% lower; 1.07x difference).
- Both models report the same context window at 131.07K tokens.
| Feature | Qwen3 32B (Qwen) | gpt-oss-safeguard-20b (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.08 | $0.075 |
| Completion Price per 1M tokens | $0.28 | $0.3 |
| Sample Workload Cost 1M input + 500K output | $0.22 | $0.22 |
| Context Window | 131.07K | 131.07K |
| Release Date | ||
| Popularity | #93 | #124 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen3 32B | On the standard 1M input plus 500K output workload, Qwen3 32B is estimated at $0.22 vs $0.22 for gpt-oss-safeguard-20b, saving $0.005 (2.2% lower). |
| High-volume input processing | gpt-oss-safeguard-20b | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen3 32B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Qwen3 Next 80B A3B Instruct (free) can replace Qwen3 32B when lower sample workload cost matters most: $0.
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- Qwen2.5 7B Instruct can replace Qwen3 32B when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen3 32B when lower sample workload cost matters most: $0.11.
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- MiMo-V2.5 offers 1.05M context with $0.28 sample workload cost.
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gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...