gpt-oss-120b is $0.21 cheaper per 1M input tokens (84.5% lower; 6.46x difference).
API cost decision in 10 seconds
🔥DeepSeek V3.2 vs 🔥gpt-oss-120b
Pick gpt-oss-120b when budget is the priority.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick gpt-oss-120b when budget is the priority.
On the standard 1M input plus 500K output workload, gpt-oss-120b is estimated at $0.13 vs $0.44 for DeepSeek V3.2, saving $0.31 (70.7% lower).
Cost-first pickgpt-oss-120b
Context-first pickBoth models
Sample savings$0.3170.7%
10x traffic gap$3.12
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $3.12. Use the calculator below to replace the sample workload with your own token volume.
gpt-oss-120b is $0.2 cheaper per 1M output tokens (52.4% lower; 2.1x difference).
Both models report the same context window at 131.07K tokens.
gpt-oss-120b is $0.31 cheaper on the standard workload (70.7% 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-120b has the lower input price; gpt-oss-120b has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, gpt-oss-120b is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.44 for DeepSeek V3.2 and $0.13 for gpt-oss-120b.
Choose DeepSeek V3.2 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose gpt-oss-120b when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, gpt-oss-120b is estimated at $0.13 vs $0.44 for DeepSeek V3.2, saving $0.31 (70.7% lower).
- gpt-oss-120b is $0.31 cheaper on the standard workload (70.7% lower).
- gpt-oss-120b is $0.21 cheaper per 1M input tokens (84.5% lower; 6.46x difference).
- gpt-oss-120b is $0.2 cheaper per 1M output tokens (52.4% lower; 2.1x difference).
- Both models report the same context window at 131.07K tokens.
| Feature | 🔥DeepSeek V3.2 (DeepSeek) | 🔥gpt-oss-120b (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.252 | $0.039 |
| Completion Price per 1M tokens | $0.378 | $0.18 |
| Sample Workload Cost 1M input + 500K output | $0.44 | $0.13 |
| Context Window | 131.07K | 131.07K |
| Release Date | 2025-12-01 | 2025-08-05 |
| Popularity Rank current rank | #7 | #20 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | gpt-oss-120b | On the standard 1M input plus 500K output workload, gpt-oss-120b is estimated at $0.13 vs $0.44 for DeepSeek V3.2, saving $0.31 (70.7% lower). |
| High-volume input processing | gpt-oss-120b | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | gpt-oss-120b | 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. |
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