Model Detail

gpt-oss-120b is a large language model with 120B parameters released by OpenAI. The model is registered under the text-generation pipeline tag on Hugging Face, and supports text->text inputs, distributed under the permissive apache-2.0 license.

gpt-oss-120b has been evaluated across multiple task suites. On task-specific evaluations the model scores 26.0% resolved on SWE-Bench.

gpt-oss-120b is priced at $0.15/M input tokens and $0.6/M output tokens. Operationally the model offers a 131K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. At this input rate the model sits in the commodity tier and is suitable for high-volume workloads where per-call cost dominates the decision.

gpt-oss-120b ships with 120B parameters. The published knowledge cutoff is 2024-06-30, so newer events will not be reflected in zero-shot answers without retrieval. Total weight footprint is approximately 120.4 GB, which is the relevant figure when planning local-inference VRAM. The apache-2.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.

Downloads of gpt-oss-120b have moved -2.0% over the past 24 hours. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.

gpt-oss-120b is best fit for general-purpose chat and instruction-following workloads, and high-volume batch jobs where per-call cost dominates the budget. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.