gpt-oss-120b is $1.96 cheaper per 1M input tokens (98% lower; 51.3x difference).
API cost decision in 10 seconds
🔥Gemini 3.1 Pro Preview vs 🔥gpt-oss-120b
Pick gpt-oss-120b for lower cost; pick Gemini 3.1 Pro Preview 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 gpt-oss-120b for lower cost; pick Gemini 3.1 Pro Preview only if the larger context window matters more.
On the standard 1M input plus 500K output workload, gpt-oss-120b is estimated at $0.13 vs $8 for Gemini 3.1 Pro Preview, saving $7.87 (98.4% lower).
Cost-first pickgpt-oss-120b
Context-first pickGemini 3.1 Pro Preview
Sample savings$7.8798.4%
10x traffic gap$78.71
Gemini 3.1 Pro Preview has more context, but gpt-oss-120b saves $7.87 on the standard workload. At 10x that traffic, the same price gap is about $78.71. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
gpt-oss-120b stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Gemini 3.1 Pro Preview | gpt-oss-120b |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | gpt-oss-120b | $16 | $0.29 |
| Balanced workload | 1M input + 1M output | gpt-oss-120b | $14 | $0.22 |
| Output-heavy chatbot | 1M input + 5M output | gpt-oss-120b | $62 | $0.94 |
gpt-oss-120b is $11.82 cheaper per 1M output tokens (98.5% lower; 66.7x difference).
Gemini 3.1 Pro Preview has 917.5K more context (8x larger).
gpt-oss-120b is $7.87 cheaper on the standard workload (98.4% 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-oss-120b has the lower input price; gpt-oss-120b has the lower output price; Gemini 3.1 Pro Preview offers the larger 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 $8 for Gemini 3.1 Pro Preview and $0.13 for gpt-oss-120b.
Choose Gemini 3.1 Pro Preview when you care most about larger context window.
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 $8 for Gemini 3.1 Pro Preview, saving $7.87 (98.4% lower).
- gpt-oss-120b is $7.87 cheaper on the standard workload (98.4% lower).
- gpt-oss-120b is $1.96 cheaper per 1M input tokens (98% lower; 51.3x difference).
- gpt-oss-120b is $11.82 cheaper per 1M output tokens (98.5% lower; 66.7x difference).
- Gemini 3.1 Pro Preview has 917.5K more context (8x larger).
| Feature | 🔥Gemini 3.1 Pro Preview (Google) | 🔥gpt-oss-120b (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $2 | $0.039 |
| Completion Price per 1M tokens | $12 | $0.18 |
| Sample Workload Cost 1M input + 500K output | $8 | $0.13 |
| Context Window | 1.05M | 131.07K |
| Release Date | ||
| Popularity | #13 | #18 |
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 $8 for Gemini 3.1 Pro Preview, saving $7.87 (98.4% 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 | Gemini 3.1 Pro Preview | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
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Open OpenAI modelsGemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...