OpenAI
GPT-OSS 20B
Frontier
8.1MDownloads4.7KLikesAug 2025Veröffentlicht128K TokenKontextApache 2.0Lizenz90 StarkQualität
GPT-OSS 20B (21B parameters) requires approximately 17.1 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 3.5999999046325684B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 20 GB of VRAM.
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Run
ollama run gpt-ossQuick specs
Parameters21B (3.6B active)
Architecturemoe (MoE)
Context128K tokens
Modalitytext
Min RAM8.2 GB
Rec. RAM12.8 GB (Q4_K_M)
LicenseApache 2.0
FamilyGPT-OSS
✓ Chat✓ Reasoning
About this model
- •OpenAI's first open-weight model under Apache 2.0 license
- •MoE architecture: 24 layers, 32 experts, top-4 routing per token
- •Configurable reasoning effort: low, medium, and high modes
- •Fits in 16GB VRAM with MXFP4 quantization
Verwandte Modelle
Schnellauswahl
Beste Hardware
Top-Empfehlungen für GPT-OSS 20B
Dieses Modell ausführen
Quantisierungsoptionen
VRAM-Schätzungen nach Quantisierungsstufe
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 8.2 GB | Low | — |
Q3_K_S | 3 | 10.3 GB | Low | — |
NVFP4 | 4 | 11.8 GB | Medium | — |
Q4_K_M | 4 | 12.8 GB | Medium | — |
Q5_K_M | 5 | 15.1 GB | High | — |
Q6_K | 6 | 17.2 GB | High | — |
Q8_0 | 8 | 22.5 GB | Very High | — |
F16 | 16 | 43.1 GB | Maximum | — |
Quality benchmarks
GPT-OSS 20B benchmark scores
Coding
SWE-bench Verified60.7%
HumanEval+—
Aider Polyglot—
LiveCodeBench74.6%
Reasoning
MMLU-Pro—
GPQA Diamond71.5%
MATH-500—
ARC Challenge—
Source: official · 2025-08-15
Hardware-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights12.8 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — GPT-OSS 20B
Siehe auch