gpt-oss 20B vs Qwen 3.6 27B
Comparing VRAM requirements, performance, and capabilities for running these models locally with Ollama.
Parameters
21B
Context
128K
VRAM Range
15–15 GB
Recommended
MXFP4 (15 GB)
ByOpenAI·LicenseApache 2.0
Parameters
27B
Context
256K
VRAM Range
20–62 GB
Recommended
Q4_K_M (20 GB)
ByAlibaba·LicenseApache 2.0
VRAM Requirements by Quantization
Side-by-side memory needs at each quality level.
| Quantization | gpt-oss 20B | Qwen 3.6 27B | Difference |
|---|---|---|---|
| Q4_K_M | — | 20 GB | — |
| Q8_0 | — | 34 GB | — |
Capabilities
Feature support comparison.
| Capability | gpt-oss 20B | Qwen 3.6 27B |
|---|---|---|
| text generation | Yes | Yes |
| code generation | Yes | Yes |
| reasoning | Yes | Yes |
| tool use | Yes | Yes |
| math | Yes | Yes |
| multilingual | — | Yes |
| vision | — | Yes |
| summarization | — | Yes |
Benchmark Scores
Higher is better. Scores from published evaluations.
| Benchmark | gpt-oss 20B | Qwen 3.6 27B |
|---|---|---|
| mmlu | 85.3 | — |
| swe-bench-verified | — | 77.2 |
| aime2026 | — | 94.1 |
| gpqa-diamond | — | 87.8 |
Hardware Compatibility
Can each model run at recommended quantization on common VRAM tiers?
| VRAM | gpt-oss 20B | Qwen 3.6 27B |
|---|---|---|
| 8 GB | No | No |
| 12 GB | Offload | No |
| 16 GB | Tight | Offload |
| 24 GB | Runs | Runs |
| 32 GB | Runs | Runs |
| 48 GB | Runs | Runs |
| 64 GB | Runs | Runs |
| 96 GB | Runs | Runs |
Run gpt-oss 20B
ollama run gpt-oss:20bRun Qwen 3.6 27B
ollama run qwen3.6:27b-q4_K_MCheck your exact hardware
Use the compatibility checker to see how each model performs on your specific GPU or Mac.