Qwen3 235B-A22B Thinking 2507 on AMD Radeon RX 7600 XT
Can the AMD Radeon RX 7600 XT run Qwen3 235B-A22B Thinking 2507?
No, it doesn’t fit
No. Qwen3 235B-A22B Thinking 2507 needs about 97.0 GB even at Q2_K; the AMD Radeon RX 7600 XT has 16.0 GB usable.
Download Qwen3 235B-A22B Thinking 2507
Recommended: Q2_K. Every other quantization has its own download link in the table below.
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run qwen3:235b-thinkingQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q2_K files (opens in a new tab)
huggingface.co/unsloth/Qwen3-235B-A22B-Thinking-2507-GGUF (opens in a new tab)
ollama run hf.co/unsloth/Qwen3-235B-A22B-Thinking-2507-GGUFOriginal weights · Hugging Face
Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.
huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507 (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from Alibaba. The weights themselves download from Hugging Face.
github.com/QwenLM/Qwen3 (opens in a new tab)
git clone https://github.com/QwenLM/Qwen3How it’s rated
Match score
To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.
| Model quality | 8.6 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Match score | 8.6 / 100 |
Every quantization on the AMD Radeon RX 7600 XT
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 97.0 GB | 16.0 GB | — | Won't run | 63Good quality (B) · 63 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) |
Q3_K_M | 118 GB | 16.0 GB | — | Won't run | 76Great quality (A) · 76 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) |
Q4_K_M | 146 GB | 16.0 GB | — | Won't run | 86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) |
Q5_K_M | 170 GB | 16.0 GB | — | Won't run | 88Excellent quality (A+) · 88 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) |
Q6_K | 196 GB | 16.0 GB | — | Won't run | 90Excellent quality (A+) · 90 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) |
Q8_0 | 252 GB | 16.0 GB | — | Won't run | 91Excellent quality (A+) · 91 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) |
F16 | 473 GB | 16.0 GB | — | Won't run | 91Excellent quality (A+) · 91 of 100: how capable the model is at F16, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Hardware that can run it
-
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.
Apple M3 Ultra (256 GB)
-
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.
Apple M3 Ultra (512 GB)
-
76Great quality (A) · 76 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.
Apple M2 Ultra (192 GB)
-
63Good quality (B) · 63 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GB10 (128 GB)
-
63Good quality (B) · 63 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA RTX PRO 6000 Blackwell
-
63Good quality (B) · 63 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 Max (128 GB)
Models that do run on the AMD Radeon RX 7600 XT
- 77Great quality (A) · 77 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4B
- 73Great quality (A) · 73 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. Raon-1 mini Preview (30B-A4B)
- 70Great quality (A) · 70 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. gpt-oss 20B
- 69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)
- 78Great quality (A) · 78 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 12B
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.