gpt-oss-120b Pricing
FastOpenAI · 131K tokens context
gpt-oss-120b from OpenAI costs $0.039 per 1 million input tokens and $0.180 per 1 million output tokens as of June 2026 (live OpenRouter data). The model supports a 131,072-token context window (approximately 98,304 words) with a 8K-token maximum output. A typical 1,000-token request costs $0.0000 in input charges; a 10,000-token request costs $0.0004.
| Input price | $0.039 / 1M tokens |
|---|---|
| Output price | $0.180 / 1M tokens |
| Output / input ratio | 4.6× |
| Context window | 131,072 tokens (~98,304 words) |
| Maximum output | 8,192 tokens |
| Cost per 1K tokens (input) | $0.0000 |
| Tier | Fast |
| Last verified |
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.
Input Price
$0.039
per 1 million tokens
Output Price
$0.180
per 1 million tokens
Context Window
131K tokens
max 8K output
Cost Examples
| Request Type | Tokens | Input Cost | Output Cost |
|---|---|---|---|
| 1,000 word article | 1,333 | $0.000052 | $0.000072 |
| 10-page document (2,500 words) | 3,333 | $0.00013 | $0.00018 |
| 1,000 lines of code | 5,000 | $0.000195 | $0.00027 |
| 100K token document | 100,000 | $0.0039 | $0.0054 |
Output cost estimated at 30% of input token count. Use the calculator for exact figures.
Strengths
- ✓Extremely cheap at $0.039/1M input tokens
- ✓Low latency for high-throughput workloads
- ✓Cost-effective at scale
Limitations
- –Less capable than flagship models on complex reasoning
- –Quality and availability can vary by hosting provider
Best Use Cases
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