gpt-oss-120b is $0.06 cheaper per 1M input tokens (61% lower; 2.56x difference).
API cost decision in 10 seconds
🔥Gemini 2.5 Flash Lite vs 🔥gpt-oss-120b
Pick gpt-oss-120b for lower cost; pick Gemini 2.5 Flash Lite only if the larger context window matters more.
Budget verdict
Pick gpt-oss-120b for lower cost; pick Gemini 2.5 Flash Lite 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 $0.3 for Gemini 2.5 Flash Lite, saving $0.17 (57% lower).
Gemini 2.5 Flash Lite has more context, but gpt-oss-120b saves $0.17 on the standard workload. At 10x that traffic, the same price gap is about $1.71. Use the calculator below to replace the sample workload with your own token volume.
gpt-oss-120b is $0.22 cheaper per 1M output tokens (55% lower; 2.22x difference).
Gemini 2.5 Flash Lite has 917.5K more context (8x larger).
gpt-oss-120b is $0.17 cheaper on the standard workload (57% 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 2.5 Flash Lite 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 $0.3 for Gemini 2.5 Flash Lite and $0.13 for gpt-oss-120b.
Choose Gemini 2.5 Flash Lite 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 $0.3 for Gemini 2.5 Flash Lite, saving $0.17 (57% lower).
- gpt-oss-120b is $0.17 cheaper on the standard workload (57% lower).
- gpt-oss-120b is $0.06 cheaper per 1M input tokens (61% lower; 2.56x difference).
- gpt-oss-120b is $0.22 cheaper per 1M output tokens (55% lower; 2.22x difference).
- Gemini 2.5 Flash Lite has 917.5K more context (8x larger).
| Feature | 🔥Gemini 2.5 Flash Lite (Google) | 🔥gpt-oss-120b (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.1 | $0.039 |
| Completion Price per 1M tokens | $0.4 | $0.18 |
| Sample Workload Cost 1M input + 500K output | $0.3 | $0.13 |
| Context Window | 1.05M | 131.07K |
| Release Date | 2025-07-22 | 2025-08-05 |
| Popularity Rank current rank | #11 | #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 $0.3 for Gemini 2.5 Flash Lite, saving $0.17 (57% 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 2.5 Flash Lite | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
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Open OpenAI modelsGemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...
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...