gpt-oss-120b is $4.96 cheaper per 1M input tokens (99.2% lower; 128.2x difference).
API cost decision in 10 seconds
🔥GPT-5.5 vs 🔥gpt-oss-120b
Pick gpt-oss-120b for lower cost; pick GPT-5.5 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 GPT-5.5 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 $20 for GPT-5.5, saving $19.87 (99.4% lower).
Cost-first pickgpt-oss-120b
Context-first pickGPT-5.5
Sample savings$19.8799.4%
10x traffic gap$198.71
GPT-5.5 has more context, but gpt-oss-120b saves $19.87 on the standard workload. At 10x that traffic, the same price gap is about $198.71. Use the calculator below to replace the sample workload with your own token volume.
gpt-oss-120b is $29.82 cheaper per 1M output tokens (99.4% lower; 166.7x difference).
GPT-5.5 has 918.93K more context (8.01x larger).
gpt-oss-120b is $19.87 cheaper on the standard workload (99.4% 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; GPT-5.5 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 $20 for GPT-5.5 and $0.13 for gpt-oss-120b.
Choose GPT-5.5 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 $20 for GPT-5.5, saving $19.87 (99.4% lower).
- gpt-oss-120b is $19.87 cheaper on the standard workload (99.4% lower).
- gpt-oss-120b is $4.96 cheaper per 1M input tokens (99.2% lower; 128.2x difference).
- gpt-oss-120b is $29.82 cheaper per 1M output tokens (99.4% lower; 166.7x difference).
- GPT-5.5 has 918.93K more context (8.01x larger).
| Feature | 🔥GPT-5.5 (OpenAI) | 🔥gpt-oss-120b (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $5 | $0.039 |
| Completion Price per 1M tokens | $30 | $0.18 |
| Sample Workload Cost 1M input + 500K output | $20 | $0.13 |
| Context Window | 1.05M | 131.07K |
| Release Date | 2026-04-24 | 2025-08-05 |
| Popularity Rank current rank | #19 | #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 $20 for GPT-5.5, saving $19.87 (99.4% 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 | GPT-5.5 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
Cheaper alternatives
Review low-cost models ranked by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsOpenAI catalog
Review all tracked OpenAI models before deciding whether this matchup is the right shortlist.
Open OpenAI modelsGPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token...
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...