| # Benchmark Report: gpt-oss-20b (Q4_K_M) |
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| **Date:** 2026-06-04 |
| **Author:** WITCHEER |
| **Platform:** NVIDIA GeForce RTX 5090 Benchmark Rig (capsule) |
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| ## Model |
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| | Field | Value | |
| |-------|-------| |
| | Model | gpt-oss-20b | |
| | Parameters | 20.91 B (dense) | |
| | Quantization | Q4_K_M | |
| | File size | 10.83 GiB | |
| | Engine | llama.cpp (CUDA 12.8 (patched)) | |
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| ## Hardware |
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| | Component | Spec | |
| |-----------|------| |
| | GPU | NVIDIA GeForce RTX 5090 | |
| | CPU | AMD Ryzen 5 9600 | |
| | RAM | 64GB DDR5-5600 | |
| | OS | Ubuntu 26.04 LTS | |
| | CUDA | 12.8 (patched) | |
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| --- |
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| ## Quality Benchmarks |
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| All benchmarks use generative evaluation via llama-server chat completions. Multiple-choice tasks (MMLU, ARC, HellaSwag) use letter extraction instead of loglikelihood scoring -- results are internally consistent for model comparison but absolute scores may differ from logprob-based evaluations by 5-15%. |
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| ### Summary |
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| | Benchmark | Score | Metric | |
| |-----------|------:|--------| |
| | **MMLU** | **78.56%** | accuracy | |
| | **ARC-Challenge** | **94.62%** | accuracy | |
| | **HellaSwag** | **74.49%** | accuracy | |
| | **HumanEval** | **94.51%** | pass@1 | |
| | **GSM8K** | **94.77%** | exact_match | |
| |
| ### MMLU Breakdown by Category |
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| | Category | Score | Correct / Total | |
| |----------|------:|----------------:| |
| | Stem | 89.83% | 2,711 / 3,018 | |
| | Humanities | 77.45% | 2,456 / 3,171 | |
| | Social Sciences | 84.45% | 2,796 / 3,311 | |
| | Other | 67.55% | 3,068 / 4,542 | |
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| --- |
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| ## Speed Benchmarks |
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| Measured with `llama-bench`. All layers GPU-offloaded (`-ngl 99`). |
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| ### Prompt Processing (tokens/s) |
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| | Context Length | Speed | +/-sigma | |
| |---------------:|------:|---------:| |
| | 128 | 7,172 | 73.0 | |
| | 512 | 16,646 | 117.8 | |
| | 2048 | 13,456 | 36.4 | |
| | 4096 | 11,684 | 28.1 | |
| | 8192 | 9,408 | 22.7 | |
| | 16384 | 6,669 | 4.6 | |
| |
| ### Generation (tokens/s) |
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| | Metric | Speed | +/-sigma | |
| |--------|------:|---------:| |
| | tg128 | 367.4 | 0.9 | |
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| --- |
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| ## Methodology |
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| ### Evaluation Framework |
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| Custom generative evaluators built for this rig. All benchmarks run through llama-server's `/v1/chat/completions` endpoint. |
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| - **Scoring:** Generative evaluation (not loglikelihood) |
| - **Thinking:** disabled |
| - **MCQ scoring:** First valid letter extracted from response (A/B/C/D) |
| - **Sampling:** 50% of dataset used |
| - **Temperature:** 0 (deterministic) |
| - **Max tokens:** 2,048 |
| - **GPU offload:** All layers (`-ngl 99`) |
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| --- |
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| *Benchmarked by WITCHEER on the RTX 5090 Benchmark Rig. Source: [github.com/notwitcheer/llm-bench-rig/blob/main/reports/gpt-oss-20b-q4-k-m.md](https://github.com/notwitcheer/llm-bench-rig/blob/main/reports/gpt-oss-20b-q4-k-m.md). Dataset: [huggingface.co/datasets/witcheer/rtx-5090-benchmarks/blob/main/reports/gpt-oss-20b-q4-k-m.md](https://huggingface.co/datasets/witcheer/rtx-5090-benchmarks/blob/main/reports/gpt-oss-20b-q4-k-m.md).* |
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