GPT OSS 120B
dinference/gpt-oss-120b出品方： dinference · 發布 2025-08
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
能力清單
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding43
- Tool calling40/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)2/20
- Provider availability1/10
Agents51
- Tool calling35/35
- Structured output0/25
- Reasoning0/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output49
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency74
- Headline price (log-scaled)74/95
- Has prompt-cache pricing0/5
Long context46
- Context window (100K → 2M)36/90
- Has published price for full window10/10
Production-readiness65
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.47 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $0.95 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.27 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.81 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.97 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
定價詳情
推薦定價來自 dinference · gpt-oss-120b
於 1 家供應商可用
| 服務商 | 服務商模型 ID | 輸入 / 1M | 輸出 / 1M | 上下文 | 發布日期 |
|---|---|---|---|---|---|
| DInference dinference | gpt-oss-120b | $0.068 | $0.270 | 131K | 2025-08 |
Frequently asked questions
How much does GPT OSS 120B cost?
GPT OSS 120B costs $0.068 per 1M input tokens and $0.270 per 1M output tokens, sourced from dinference. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of GPT OSS 120B?
GPT OSS 120B has a context window of 131K tokens, with a max output of 33K tokens per reply. This is the total combined size of prompt + completion.
Does GPT OSS 120B support tool calling?
Yes. GPT OSS 120B supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does GPT OSS 120B support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for GPT OSS 120B in our data source. Verify with dinference's official documentation before relying on it in production.
Can GPT OSS 120B accept image input?
No. GPT OSS 120B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is GPT OSS 120B open-weight?
Yes. GPT OSS 120B's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
Where does this data come from?
All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
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Capability lists this model is in
最近更新：
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.