API cost decision in 10 seconds
Qwen3.5-122B-A10B vs 🔥gpt-oss-120b
Pick gpt-oss-120b for lower cost; pick Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B 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 $1.3 for Qwen3.5-122B-A10B, saving $1.17 (90.1% lower).
Cost-first pickgpt-oss-120b
Context-first pickQwen3.5-122B-A10B
Sample savings$1.1790.1%
10x traffic gap$11.71
Qwen3.5-122B-A10B has more context, but gpt-oss-120b saves $1.17 on the standard workload. At 10x that traffic, the same price gap is about $11.71. 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 | Qwen3.5-122B-A10B | gpt-oss-120b |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | gpt-oss-120b | $2.34 | $0.29 |
| Balanced workload | 1M input + 1M output | gpt-oss-120b | $2.34 | $0.22 |
| Output-heavy chatbot | 1M input + 5M output | gpt-oss-120b | $10.66 | $0.94 |
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, and Qwen3.5-122B-A10B offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.3 for Qwen3.5-122B-A10B and $0.13 for gpt-oss-120b.
Choose Qwen3.5-122B-A10B 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.
| Feature | Qwen3.5-122B-A10B (Qwen) | 🔥gpt-oss-120b (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.26 | $0.04 |
| Completion Price per 1M tokens | $2.08 | $0.18 |
| Sample Workload Cost 1M input + 500K output | $1.3 | $0.13 |
| Context Window | 262.14K | 131.07K |
| Release Date | 2026-02-25 | 2025-08-05 |
| Popularity | #20 |
The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...
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...
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 $1.3 for Qwen3.5-122B-A10B, saving $1.17 (90.1% lower). |
| High-volume input processing | gpt-oss-120b | Lower prompt-token price matters most when prompts or retrieved passages 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 | Qwen3.5-122B-A10B | A larger context window leaves more room for retrieved passages and source files. |