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GPT OSS 120B (Together AI)

GPT OSS 120B belongs to OpenAI's gpt-oss family of open-weight language models, reflecting a lineage focused on releasing capable open-source alternatives rather than proprietary frontier systems. Together AI positions this 120-billion-parameter model as part of its serverless catalog, making the open weights accessible through managed inference rather than requiring self-hosting. This approach lets developers tap into a large-scale open model without managing GPU infrastructure, while still benefiting from the transparency and customization potential that open weights provide.

On the practical side, Together AI's serverless deployment of GPT OSS 120B is aimed at teams that want flexible, on-demand access to a substantial open-source LLM for tasks like reasoning, tool integration, and general text generation. The Together AI Python SDK offers a straightforward integration path, letting developers send chat completions requests using the model identifier "gpt-oss-120b" without complex deployment steps. This makes the model a practical fit for organizations seeking a large open-weight model with managed serving, especially when comparing across multiple providers to balance cost, latency, and operational simplicity.

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LLM Gateway
Model key
together-ai/gpt-oss-120b
Release date
Aug 5, 2025
Last updated
Aug 5, 2025
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.15
Output token cost
$0.60

Limits

Output tokens
32,768 tokens
Context window
131,072 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about GPT OSS 120B (Together AI)

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CoverageBenchmark

SemiAnalysis InferenceX published a detailed architecture and evaluation breakdown of gpt-oss-120b, confirming it as an open-weight reasoning language model launched on August 5, 2025 alongside gpt-oss-20b under the Apache 2.0 license. The model is described as 117B total and 5.1B active parameters with a 131K token co The page highlights that over 90% of the model's weights are natively quantized to MXFP4 at roughly 4.25 bits per parameter, enabling the 120B model to fit on a single 80GB GPU such as an NVIDIA H100 or AMD MI300X. It also summarizes OpenAI's positioning claims, noting near-parity with o4-mini on core reasoning benchma

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Coverage

Databricks published a blog post demonstrating how its GEPA automated prompt optimization technique can lift gpt-oss-120b above leading proprietary frontier models on enterprise agent workloads. According to the post, gpt-oss-120b surpasses Claude Sonnet 4 and Claude Opus 4.1 by roughly 3% on the evaluation while being The same article shows that applying GEPA prompt optimization to the proprietary baselines raises Claude Opus 4.1 and Claude Sonnet 4 by an additional 6-7%, establishing new state-of-the-art results, and that prompt optimization matches or beats supervised fine-tuning while cutting serving costs by about 20%. Together

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