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Model details

GPT OSS 120B

GPT OSS 120B is OpenAI's large-scale open-weight language model, released on August 5, 2025, as part of the GPT-OSS family that also includes the smaller 20B variant. It is built on a Mixture-of-Experts architecture with 117 billion total parameters and 128 experts, activating roughly 5.1 billion parameters per forward pass so that inference stays efficient despite the model's size. Native MXFP4 quantization lets it run on a single H100 GPU, making it practical for data-center deployments that need high-throughput reasoning without sprawling hardware requirements. The weights are published openly on Hugging Face under OpenAI's account, and the Apache 2.0 license allows organizations to self-host, fine-tune, modify, and commercialize the model locally or in the cloud.

The design targets high-reasoning, agentic, and general-purpose production use cases, with capabilities positioned on par with OpenAI's o4-mini tier. Configurable reasoning effort, full chain-of-thought access, and native tool use including function calling, browsing, and structured output generation make it well suited for complex multi-step workflows and agent systems. A 131K-token context window supports long-document reasoning and extended conversations, while text-in and text-out modalities keep the interface straightforward for integration into pipelines. Teams that need strong reasoning performance, the flexibility of open weights, and the ability to deploy on their own infrastructure will get the most from this model, especially in production environments where data control and customization matter.

AKI.IOgpt-oss-120bgpt-oss

Quick Info

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Provider
AKI.IO
Model key
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
$0.55

Limits

Output tokens
32,768 tokens
Context window
128,000 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

Abacus

Official sourceAnnouncement

OpenAI released gpt-oss-120b and gpt-oss-20b on August 5, 2025, as open-weight reasoning models licensed under Apache 2.0. The 120b variant is reported to achieve near-parity with OpenAI o4-mini on core reasoning benchmarks while running on a single 80 GB GPU. Training used reinforcement learning informed by OpenAI's o3 and frontier systems. Both gpt-oss models support the Responses API, Structured Outputs, configurable reasoning effort, and full chain-of-thought. They are built for agentic workflows with tool use such as web search and Python code execution. The release emphasized strong performance on Tau-Bench agentic evaluations and HealthBench, where gpt-oss models outperformed proprietary systems including o1 and GPT-4o.

Abacus

Coverage

Hugging Face welcomed GPT OSS as OpenAI's open-weights release on August 5, 2025, detailing that gpt-oss-120b is a 117B-parameter mixture-of-experts model using 4-bit MXFP4 quantization to keep active parameters and resource usage low. The large variant fits on a single H100 GPU, while gpt-oss-20b is a 21B-parameter MoE that runs within 16 GB of memory for consumer and on-device applications. The blog highlights the Apache 2.0 license paired with a minimal usage policy, framing the release as a meaningful step in OpenAI's open-source commitment. Both models target reasoning and agentic workloads, with the 120b version positioned for powerful inference and the 20b version targeted at edge deployment. Full chain-of-thought and customizable behavior support developer iteration.

Abacus

Official sourceDocumentation

OpenAI's official gpt-oss-120b and gpt-oss-20b model card, published August 5, 2025, documents the models as text-only open-weight releases under Apache 2.0. It describes compatibility with the Responses API and design for agentic workflows with strong instruction following, tool use, and adjustable reasoning effort. The card highlights full chain-of-thought availability and Structured Outputs support. The model card frames the release as a model card rather than system card because downstream stakeholders assemble the deployed systems. OpenAI ran scalable capability evaluations on gpt-oss-120b and confirmed the default model stays below High capability thresholds across the Preparedness Framework's tracked Biological and Chemical, Cyber, and AI Self-Improvement categories. Adversarial fine-tuning tests examined whether attackers could elevate those risks.

Abacus

Coverage

Hugging Face's official openai/gpt-oss-120b model card confirms OpenAI's 117B-parameter model with 5.1B active parameters, released on August 5, 2025 under the Apache 2.0 license for unrestricted commercial and fine-tuning use. The card stresses that both gpt-oss variants must be used with the harmony response format, since they were trained on it and will not behave correctly otherwise. Developers get configurable low/medium/high reasoning effort, full chain-of-thought access, and fine-tunable weights. The card lists native agentic capabilities including function calling, web browsing, Python code execution, and Structured Outputs, making the model suited to agentic workflows. MXFP4 post-training quantization of the MoE weights enables gpt-oss-120b inference on a single 80 GB GPU. The page also documents Transformers-based usage with an automatically applied harmony chat template, plus Transformers Serve for spinning up an OpenAI-compatible API endpoint for local deployment.

Abacus

CoverageBenchmark

OpenAI's gpt-oss-120b is an open-weight reasoning model released on August 5, 2025, under the Apache 2.0 license. The SemiAnalysis InferenceX profile confirms it is a 36-layer mixture-of-experts transformer with 117B total and 5.1B active parameters, 131K context, and a 201,088-token vocabulary. Notably, more than 90% of weights are natively quantized to MXFP4 at 4.25 bits, letting the full model fit on a single 80 GB GPU such as an NVIDIA H100 or AMD MI300X. The same profile details an attention design that alternates banded-window and fully dense layers, combined with Grouped Query Attention plus learned attention-sink biases in the softmax denominator. Positional encoding uses RoPE with YaRN context extension at factor 32, and experts are activated via a Top-4/128 gated SwiGLU MoE scheme. OpenAI positions gpt-oss-120b at near-parity with o4-mini on core reasoning and competitive results on Codeforces, MMLU, HLE, TauBench, AIME, and HealthBench.

QVAC

CoverageBenchmark

An arXiv preprint dated December 9, 2025 benchmarks OpenAI's GPT-OSS-120B and GPT-OSS-20B across ten financial NLP tasks, reporting 66.5% accuracy for the 120B variant against datasets such as Financial PhraseBank, FiQA-SA, and FLARE FINER-ORD. The evaluation introduces a Token Efficiency Score and tokens-per-second th The study finds a counter-intuitive efficiency paradox in which the smaller GPT-OSS-20B matches the 120B's accuracy at roughly 65.1% while delivering higher throughput and a 198.4 Token Efficiency Score, suggesting architectural and training innovations in GPT-OSS allow compact variants to compete with larger models li

Vercel AI Gateway

Coverage

Epoch AI's model registry entry for gpt-oss-120b confirms OpenAI as the creator and August 5, 2025 as the release date for this open-weights model. The page reports 1.2e11 parameters, training on NVIDIA H100 SXM5 80GB hardware, and roughly 4.9e24 FLOP of training compute. It assigns an Epoch Capability Index (ECI) scor The Epoch scorecard provides concrete benchmark deltas versus GPT-4.1, o3-mini, and Qwen3-Max across agent, conceptual reasoning, games, mathematics, science, and software engineering domains — for example, 96% on GPQA Diamond, 88% on Aider Polyglot, 93% on WeirdML v2, and 100% on OTIS Mock AIME 2024-2025. These figure

Neon

CoverageBenchmark

BenchLM.ai, a third-party benchmark aggregator, provides a capability snapshot for GPT-OSS 120B with data current as of September 4, 2026. The model was released August 5, 2025, features open weights and a 128K context window, and scores 49.3 out of 100, ranking 137 of 232 tracked models. Its strongest eligible categor The page also reports a speed of approximately 150 tokens per second with a 14.18-second time to first token, and notes that published weights can be self-hosted, though infrastructure cost varies and no comparable first-party API token rate is published. This aggregator-derived data provides a current independent tech

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