Alibaba (Qwen) · Apache 2.0
Qwen3.5
A full family from phone size (0.8B) to 122B, every size reading images. A strong pick for small machines.
How much memory it needs
The model file, plus memory for the conversation, plus about 1 GB for the app. Longer conversations need more.
| Size | Version | File | At 8K | At 32K | At 128K |
|---|---|---|---|---|---|
| 0.9B | MXFP4 | 0.5 GB | 1.8 GB | 2.1 GB | 3.3 GB |
| 2.3B | MXFP4 | 1.3 GB | 3.1 GB | 3.4 GB | 4.5 GB |
| 4.7B | Q4_K_M | 2.7 GB | 4.7 GB | 5.5 GB | 8.7 GB |
| Q8_0 | 4.5 GB | 6.4 GB | 7.2 GB | 10.4 GB | |
| 9.7B | Q4_K_M | 5.7 GB | 7.9 GB | 8.7 GB | 11.9 GB |
| Q8_0 | 9.5 GB | 11.7 GB | 12.5 GB | 15.7 GB | |
| 28B | Q4_K_M | 18.0 GB | 20.4 GB | 22.1 GB | 28.5 GB |
| Q8_0 | 29.1 GB | 31.6 GB | 33.2 GB | 39.6 GB | |
| 36B (3B active) | Q4_K_M | 22.0 GB | 24.1 GB | 24.6 GB | 26.6 GB |
| Q8_0 | 36.9 GB | 39.0 GB | 39.5 GB | 41.5 GB | |
| 125B (10B active) | Q4_K_M | 76.5 GB | 78.7 GB | 79.3 GB | 81.7 GB |
| Q8_0 | 130 GB | 132 GB | 133 GB | 135 GB |
Which computers run it
The best size for each machine at an 8K-token conversation. Speeds are estimates from memory bandwidth.
| Computer | Best version | Fit | Speed |
|---|---|---|---|
| Laptop or PC, no graphics card, 32 GB | 9.7B Q8_0 | Runs great | 5.5–8.5tok/sReadable |
| RTX 4060 · 8 GB | 4.7B Q8_0 | Runs well | 35–55tok/sFast |
| RTX 3060 · 12 GB | 9.7B Q4_K_M | Runs great | 35–55tok/sFast |
| RTX 5060 Ti · 16 GB | 9.7B Q8_0 | Runs great | 25–45tok/sSmooth |
| RTX 4090 · 24 GB | 28B Q4_K_M | Runs well | 30–50tok/sFast |
| RTX 5090 · 32 GB | 36B Q4_K_M | Runs well | 150–290tok/sFast |
| Mac with M4 · 16 GB | 9.7B Q4_K_M | Runs great | 12–20tok/sSmooth |
| Mac with M4 Pro · 48 GB | 36B Q4_K_M | Runs great | 40–90tok/sFast |
| Mac with M5 Max · 128 GB | 125B Q4_K_M | Runs great | 35–75tok/sFast |
| Ryzen AI Max+ 395 · 128 GB | 125B Q4_K_M | Runs well | 15–30tok/sSmooth |
| DGX Spark · 128 GB | 125B Q4_K_M | Runs great | 16–30tok/sSmooth |
| RTX PRO 6000 · 96 GB | 125B Q4_K_M | Runs well | 75–150tok/sFast |
| Mac Studio with M5 Ultra · 256 GB | 125B Q8_0 | Runs great | 25–50tok/sSmooth |
| Mac Studio with M3 Ultra · 512 GB | 125B Q8_0 | Runs great | 17–35tok/sSmooth |
Measured speeds
Real runs, not estimates. All measurements.
| Computer | Version | Prompt | Speed | Source |
|---|---|---|---|---|
| NVIDIA DGX Spark (GB10, 128 GB LPDDR5x) | Q8_0 | 512 | 51.33 tok/s | 2026-03-10 |
| Apple M5 Max (18-core CPU, 40-core GPU, 14-inch MacBook Pro, 128 GB) | MLX 4-bit | 4K | 65.9 tok/s | 2026-03-11 |
| NVIDIA GeForce RTX 5090 32 GB | MXFP4 | 256K | 97.3 tok/s | 2026-03 |
| NVIDIA GeForce RTX 3090 24 GB (used) | MXFP4 | 128K | 79.4 tok/s | 2026-03 |
| NVIDIA DGX Spark (GB10, 128 GB LPDDR5x) | Q4_K_M | 512 | 59.98 tok/s | 2026-03-30 |
What it is good and bad at
Good at
- A size for every machine, from 8 GB laptops to 128 GB
- Images and video in every size
- Small conversation memory thanks to its hybrid design
Not good at
- The small sizes (0.8B–4B) make more mistakes on hard questions
Start it
Install Ollama, then run one of these in a terminal. LM Studio users can search the same name in the app.
ollama run qwen3.5:4bollama run qwen3.5:9bollama run qwen3.5:27bollama run qwen3.5:35b-a3bollama run qwen3.5:122b-a10b