Model Details
GPT OSS 120B High
Quick answer: GPT OSS 120B High is OpenAI's first publicly released open-weight model — a 120-billion parameter model available for download and self-hosted deployment. "High" refers to the full-precision, highest-capability tier of the OSS 120B family (vs lighter quantised variants). It brings GPT-5-era training methodology to an open weights format, enabling research, fine-tuning, and private deployment.
At a Glance
Where GPT OSS 120B High leads
- Open weights under Apache 2.0 — freely downloadable, self-hostable, and fine-tunable
- 120B parameters trained with OpenAI's RLHF and alignment methodology — highest quality open model from OpenAI
- No API rate limits, no per-token cost at inference — ideal for high-throughput or cost-sensitive private workloads
- Suitable for domain fine-tuning (legal, medical, finance) without API data-handling restrictions
Where it lags
- Requires significant GPU infrastructure: at FP16, ~240GB VRAM (e.g., 3–4× A100 80GB or H100 80GB)
- Capability ceiling below closed GPT-5.1 and GPT-5.2 — open weights trade some RLHF depth for accessibility
- No multimodal capabilities in the OSS release (text only)
Best for: enterprises needing on-premises deployment, researchers building fine-tuned domain models, and teams where data privacy restrictions preclude API-based inference.
What GPT OSS 120B High Is
GPT OSS 120B is OpenAI's strategic open-weight release, marking a reversal of the company's historically closed approach to model weights. The model was released in early 2026 as competitive pressure from open-weight leaders (Llama 4, Qwen 3, DeepSeek V3) intensified. "High" refers to the flagship full-precision variant within the OSS 120B family — OpenAI also offers quantised and smaller-parameter variants in the same release.
The model was trained using a similar data pipeline and RLHF approach as the closed GPT-5 family, with the weights released under Apache 2.0 to maximise adoption. For Benchgen users, GPT OSS 120B High is interesting both as a self-hosted evaluation target and as a fine-tuning base for domain-specific agent evaluation.
Specifications
| Field | Value |
|---|---|
| Organization | OpenAI |
| Parameters | 120 billion |
| Architecture | Transformer decoder |
| License | Apache 2.0 |
| Release date | March 2026 |
| Modality | Text |
| Min VRAM (FP16) | ~240GB (3–4× A100/H100 80GB) |
| HuggingFace | openai/gpt-oss-120b |
Pricing
GPT OSS 120B High weights are freely available under Apache 2.0. Self-hosted inference cost depends on hardware. OpenAI also provides hosted API access:
| Input (per 1M tokens) | Output (per 1M tokens) | |
|---|---|---|
| OpenAI API (hosted) | ~$0.40 | ~$1.60 |
GPT OSS 120B High vs Alternatives
| Model | Params | License | Context | SWE-bench Verified |
|---|---|---|---|---|
| GPT OSS 120B High | 120B | Apache 2.0 | 128K | TBD |
| Llama 4 Maverick | 400B MoE | Llama 4 | 1M | ~50% est. |
| Qwen3 235B A22B | 235B MoE | Apache 2.0 | 32K | ~55% est. |
| DeepSeek V3 | 685B MoE | MIT | 128K | ~42% |
(Scores are estimates pending Benchgen evaluations.)
Related Models & Benchmarks
- Compare: GPT-5 · Llama 4 Maverick · Qwen3 235B A22B
- Benchmarks: SWE-bench Verified · MMLU-Pro
Frequently Asked Questions
What is GPT OSS 120B High?
GPT OSS 120B High is OpenAI's first publicly released open-weight model — 120B parameters under Apache 2.0. "High" denotes the full-precision flagship tier of the OSS 120B family.Can I fine-tune GPT OSS 120B High?
Yes — the Apache 2.0 license permits fine-tuning, derivative model releases, and commercial use without restriction.What hardware is required?
At FP16, approximately 240GB VRAM — achievable with 3–4× A100 80GB or H100 80GB GPUs. Quantised variants (INT8, INT4) significantly reduce requirements.Specs based on OpenAI's GPT OSS 120B release. Last updated 2026-06-19.