Smaller alternatives
Models that need less memory than Qwen3 235B A22B Thinking 2507 and score about as well or better.
Qwen3 235B A22B Thinking 2507
MoE
Qwen · 235.1B (22B active) · Mixture of experts
Qwen3 235B A22B Thinking 2507 is a 235.1B model from Qwen with a 256K-token context. At Q4_K_M with an 8K context it needs about 134.2 GB; 169 GB leaves room for longer chats.
Mixture of experts
Parameters: 235.1B · Active: 22B
All 235.1B parameters load into memory, but only 22B 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 | 0.7 GB | 133.4 GB |
| 8K | 1.5 GB | 134.2 GB |
| 32K | 5.9 GB | 138.6 GB |
| 128K | 23.5 GB | 156.2 GB |
| 256K | 47 GB | 179.7 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 Qwen3 235B A22B Thinking 2507 grade A or S at Q4_K_M.
Can I run Qwen3 235B A22B Thinking 2507 locally?
Can I run Qwen3 235B A22B Thinking 2507 locally?
Yes, if your GPU or Mac has about 134.2 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 Qwen3 235B A22B Thinking 2507 need?
About 134.2 GB at Q4_K_M with an 8K context and 234.5 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.