Smaller alternatives
Models that need less memory than gpt-oss 20b and score about as well or better.
gpt-oss 20b
MoE
OpenAI · 20.9B (3.6B active) · Mixture of experts
gpt-oss 20b is a 20.9B model from OpenAI with a 128K-token context. At Q4_K_M with an 8K context it needs about 11.3 GB; 16 GB leaves room for longer chats.
Mixture of experts
Parameters: 20.9B · Active: 3.6B
All 20.9B parameters load into memory, but only 3.6B work on each token, so it runs at the speed of a much smaller model.
Quantization options
| Quant | Bits | Memory | Quality | On your hardware |
|---|---|---|---|---|
| Q2_K | 3.16 | — | Noticeably worse | … |
| Q3_K_M | 4 | — | Some loss | … |
| Q4_K_M | 4.89 | — | Good | … |
| Q5_K_M | 5.7 | — | Good | … |
| Q6_K | 6.56 | — | Near original | … |
| Q8_0 | 8.5 | — | Near original | … |
| F16 | 16 | — | Original | … |
Memory by context length
At Q4_K_M. The context cache grows with every token the model keeps in mind.
| Context | Context cache | Total |
|---|---|---|
| 4K | 0.1 GB | 11.2 GB |
| 8K | 0.2 GB | 11.3 GB |
| 32K | 0.8 GB | 11.9 GB |
| 128K | 3 GB | 14.1 GB |
Next steps
Compare it with
Scored models of a similar size, side by side on your device.
Least hardware that runs it well
Desktop devices with the least memory that give gpt-oss 20b grade A or S at Q4_K_M.
Can I run gpt-oss 20b locally?
Can I run gpt-oss 20b locally?
Yes, if your GPU or Mac has about 11.3 GB free for it at Q4_K_M. Open this page on that computer to see the grade for your exact hardware, then start it with llama.cpp, Ollama or LM Studio.
How much memory does gpt-oss 20b need?
About 11.3 GB at Q4_K_M with an 8K context and 11.8 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.