gpt-oss vs Qwen
gpt-oss and Qwen side by side: model sizes, the VRAM you need, context window, abilities, licence and which one to pick.
Side by side
| gpt-oss | Qwen | |
|---|---|---|
| Type | Open-weight models | Open-weight models |
| Developer | OpenAI | Alibaba Cloud (Qwen team) |
| Newest model | gpt-oss-safeguard · Oct 2025 | Qwen3.8 · Aug 2026 |
| Sizes | 20B · 120B | 0.8B · 2B · 4B · 9B · 27B · 35B · 122B |
| Smallest VRAM (4-bit) | ~16 GB (gpt-oss-safeguard 20B) | ~2 GB (Qwen3.5 0.8B) |
| Context window | 128K tokens | 256K tokens |
| Abilities | Tool callingReasoning mode | Tool callingReasoning modeImage input |
| Licence | Apache 2.0 | Apache 2.0 |
| Run it | ollama run gpt-oss-safeguard:20b | ollama run qwen3.5:0.8b |
Which one should you pick?
- Qwen runs on smaller hardware: from ~2 GB of GPU memory, against ~16 GB.
- Qwen reads longer inputs: a 256K-token context window.
- Only Qwen has image input.
Pick gpt-oss if…
- you want OpenAI-style behaviour and tool calling, self-hosted
- you have a 16 GB GPU and need reasoning
- you want one 80 GB GPU to run a 120B-class model
Pick Qwen if…
- you want the best model for a given amount of VRAM
- you need a permissive Apache 2.0 licence
- you want image input in small models
VRAM and download size
Ollama's default 4-bit builds with an 8K context. Read GB as system RAM on a CPU-only machine or a Mac.
gpt-oss
| Model | Download | VRAM |
|---|---|---|
| gpt-oss-safeguard 20B | 14 GB | ~16 GB |
| gpt-oss 20B | 14 GB | ~16 GB |
| gpt-oss-safeguard 120B | 65 GB | ~72 GB |
| gpt-oss 120B | 65 GB | ~72 GB |
Qwen
| Model | Download | VRAM |
|---|---|---|
| Qwen3.5 0.8B | 1.3 GB | ~2 GB |
| Qwen3.5 2B | 2.6 GB | ~3.5 GB |
| Qwen3.5 4B | 4.1 GB | ~5.5 GB |
| Qwen3.5 9B | 9 GB | ~10.5 GB |
| Qwen3.8 27B | 18 GB | ~20.5 GB |
| Qwen3.6 27B | 18 GB | ~20.5 GB |
| Qwen3.5 27B | 21 GB | ~24 GB |
| Qwen3.6 35B | 23 GB | ~26 GB |
| Qwen3.5 35B | 24 GB | ~27 GB |
| Qwen3.5 122B | 81 GB | ~90 GB |
Frequently asked questions
Is gpt-oss better than Qwen?
It depends on the job and your hardware. Qwen runs on smaller hardware: from ~2 GB of GPU memory, against ~16 GB. Qwen reads longer inputs: a 256K-token context window. Only Qwen has image input. For quality, test both on your own prompts: benchmark rankings change with every release.
Which needs less VRAM, gpt-oss or Qwen?
gpt-oss starts at ~16 GB (14 GB download). Qwen starts at ~2 GB (1.3 GB download).
Can I use gpt-oss and Qwen commercially?
gpt-oss: Apache 2.0. Qwen: Apache 2.0. Check the exact licence of the model you deploy; custom licences can limit very large companies or certain uses.
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