AI 模型情報

GPT OSS 120B

frogbot/gpt-oss-120b

出品方: frogbot · 系列: gpt-oss · 發布 1970-01-01

$0.150
輸入 / 1M token
$0.600
輸出 / 1M token
131K
上下文長度
33K
最大輸出

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

能力清單

工具呼叫推理結構化輸出附件開放權重溫度可調
支援模態: 輸入 text · 輸出 text

Model fit scores

0–100 · higher is better

These 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.

Coding73
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)2/20
  • Provider availability1/10
Agents91
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output99
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume19/20
Cost efficiency65
  • Headline price (log-scaled)65/95
  • 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.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$1.05
< $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
$2.10
< $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
$0.60
< $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
$1.80
< $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
$2.16
< $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 frogbot · gpt-oss-120b

$0.150
輸入
$0.600
輸出

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
FrogBot
frogbot
gpt-oss-120b$0.150$0.600131K1970-01-01

Frequently asked questions

How much does GPT OSS 120B cost?

GPT OSS 120B costs $0.150 per 1M input tokens and $0.600 per 1M output tokens, sourced from frogbot. 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?

Yes. GPT OSS 120B supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

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.

What are the best alternatives to GPT OSS 120B?

If GPT OSS 120B doesn't fit, consider GPT OSS 20B. Each one targets the same use case — see the Related links below for direct head-to-head pages.

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.

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.