AMD Radeon RX 7600 XT
16 GB · 288 GB/s · 190 W
In short
The AMD Radeon RX 7600 XT has 16 GB of GDDR6 memory with 288 GB/s of bandwidth, which sets how fast it generates text. At 8k context it runs 52 of the 113 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q8_0, at about 5 tok/s (estimated). The AMD Radeon RX 7600 XT is not on sale new in the UK right now; used, it starts at £348 (asking price).
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the UK, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| eBayGIGABYTE Gaming OC Radeon RX 7600 XT 16GB GDDR6 PCIe HDMI/DP VR Ready | used, asking price | £348+ £7 delivery | In stock | 3 h ago | Buy |
What two of them run
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 29.0 GB | 27k48k with q8 cache | 5tok/sest. | 276 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 28.6 GB | 34k59k with q8 cache | 5tok/sest. | 276 tok/s | – |
| Gemma 4 31B | Q6_K | fits | 26.2 GB | 57k110k with q8 cache | 6tok/sest. | 240 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q6_K | fits | 30.4 GB | 8k13k with q8 cache | 34tok/sest. | 2361 tok/s | chat, coding, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 28.6 GB | 34k59k with q8 cache | 5tok/sest. | 276 tok/s | – |
| Gemma 4 26B-A4B | Q8_0 | fits | 26.7 GB | 153k245k with q8 cache | 21tok/sest. | 1799 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q6_K | fits | 28.4 GB | 85k133k with q8 cache | 36tok/sest. | 2361 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q6_K | fits | 24.8 GB | 106k183k with q8 cache | 21tok/sest. | 1321 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 25.9 GB | 35k64k with q8 cache | 6tok/sest. | 311 tok/s | – |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | fits | 29.4 GB | 78k107k with q8 cache | 49tok/sest. | 2244 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.8 GB | 128k | 36tok/sest. | 1709 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q6_K | fits | 25.5 GB | 57k102k with q8 cache | 29tok/sest. | 1708 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q6_K | fits | 28.4 GB | 15k29k with q8 cache | 6tok/sest. | 213 tok/s | – |
| Gemma 4 12B | Q8_0 | fits | 13.6 GB | 256k | 12tok/sest. | 627 tok/s | – |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.5 GB | 256k | 16tok/sest. | 794 tok/s | chat |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 25.9 GB | 35k64k with q8 cache | 6tok/sest. | 311 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q6_K | fits | 28.4 GB | 15k29k with q8 cache | 6tok/sest. | 222 tok/s | – |
| Gemma 3 27B | Q8_0 | fits | 29.1 GB | 23k45k with q8 cache | 5tok/sest. | 279 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 16.0 GB | 97k176k with q8 cache | 10tok/sest. | 515 tok/s | – |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 17.2 GB | 40k | 9tok/sest. | 479 tok/s | – |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.6 GB | 128k | 16tok/sest. | 838 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.6 GB | 40k | 16tok/sest. | 838 tok/s | chat |
| Phi-4 14B Microsoft | Q8_0 | fits | 17.4 GB | 16k | 9tok/sest. | 482 tok/s | – |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.8 GB | 256k | 33tok/sest. | 1598 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.8 GB | 149k256k with q8 cache | 16tok/sest. | 783 tok/s | chat |
| Granite 4.2 8B IBM | Q8_0 | fits | 11.3 GB | 125k128k with q8 cache | 15tok/sest. | 777 tok/s | – |
| Gemma 4 E4B | Q8_0 | fits | 9.2 GB | 128k | 19tok/sest. | 962 tok/s | chat |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 10.1 GB | 125k | 65tok/sest. | 5614 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q6_K | fits | 8.5 GB | 128k | 21tok/sest. | 865 tok/s | chat |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.9 GB | 32k | 251tok/sest. | 11750 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.2 GB | 256k | 170tok/sest. | 8084 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.8 GB | 256k | 102tok/sest. | 3316 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.3 GB | 128k | 74tok/sest. | 3698 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.2 GB | 128k | 52tok/sest. | 2445 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 4.5 GB | 128k | 47tok/sest. | 2461 tok/s | chat, coding, agents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 4.5 GB | 32k | 47tok/sest. | 2171 tok/s | chat, coding, agents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 5.3 GB | 128k | 37tok/sest. | 1628 tok/s | chat, coding |
| granite 4.2 3b IBM | Q8_0 | fits | 5.6 GB | 128k | 35tok/sest. | 1751 tok/s | chat, coding |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 25.7 GB | 63k113k with q8 cache | 34tok/sest. | 2948 tok/s | chat |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.5 GB | 128k | 34tok/sest. | 2705 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 18.2 GB | 128k | 27tok/sest. | 2281 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 9.3 GB | 128k | 19tok/sest. | 933 tok/s | chat |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 10.3 GB | 128k | 17tok/sest. | 865 tok/s | chat |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 10.8 GB | 149k256k with q8 cache | 16tok/sest. | 783 tok/s | chat |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 11.0 GB | 128k | 15tok/sest. | 677 tok/s | chat |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 12.6 GB | 64k | 13tok/sest. | 677 tok/s | – |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 17.5 GB | 74k128k with q8 cache | 9tok/sest. | 469 tok/s | – |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 25.9 GB | 35k64k with q8 cache | 6tok/sest. | 316 tok/s | – |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 25.9 GB | 35k40k with q8 cache | 6tok/sest. | 316 tok/s | – |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 25.9 GB | 35k40k with q8 cache | 6tok/sest. | 316 tok/s | – |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 25.9 GB | 35k64k with q8 cache | 6tok/sest. | 311 tok/s | – |
| granite 4.2 30b IBM | Q6_K | fits | 26.2 GB | 24k45k with q8 cache | 6tok/sest. | 251 tok/s | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.6 GB | – | 17tok/sest. | 615 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 46.8 GB | – | 21tok/sest. | 1442 tok/s | chat |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 52.5 GB | – | 9tok/sest. | 476 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.0 GB | – | 26tok/sest. | 822 tok/s | chat, coding |
| GLM 4.5 Air Z.ai | Q2_K | offload | 45.0 GB | – | 7tok/sest. | 291 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 46.8 GB | – | 27tok/sest. | 1814 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.0 GB | – | 23tok/sest. | 2296 tok/s | chat, coding, long documents |
| Llama 3.3 70B Meta | Q4_K_M | offload | 43.4 GB | – | 2tok/sest. | 84 tok/s | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | offload | 43.4 GB | – | 2tok/sest. | 84 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 92.2 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.8 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 75.1 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 73.4 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 60.1 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 378.5 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 379.0 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 378.5 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 379.4 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 379.4 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 147.7 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 156.4 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q8_0 | won't run | 127.8 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 62.0 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 68.4 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 205.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 422.0 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 435.9 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 748.4 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 580.0 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 580.5 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 580.5 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 580.5 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 132.1 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 132.1 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 118.6 GB | – | – | – | – |
| MiniMax M3 MiniMax | UD-Q4_K_M | won't run | 249.0 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 73.9 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Radeon RX 7600 XT
- Memory
- 16 GB GDDR6
- Memory bus
- 128-bit
- Memory bandwidth
- 288 GB/s
- FP16 compute
- 45 TFLOPS
- Software
- ROCm
- Board power
- 190 W
- PCIe generation
- Gen 4
- PCIe lanes
- x8
Compare with
Questions
- How much memory does the AMD Radeon RX 7600 XT have for AI models?
- The AMD Radeon RX 7600 XT has 16 GB of GDDR6 memory with 288 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the AMD Radeon RX 7600 XT can run locally?
- Qwen 3.8 27B (Q8_0) fits fully in its memory at 8k context and generates at about 5 tok/s, an estimate from its memory bandwidth. 52 of the 113 models we track fit at that context.
- Can the AMD Radeon RX 7600 XT run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 92 GB at 8k context, more than the AMD Radeon RX 7600 XT and system RAM can hold.
- How much does the AMD Radeon RX 7600 XT cost in the UK?
- The AMD Radeon RX 7600 XT is not on sale new in the UK right now; used, it starts at £348 (asking price).
Speeds on this page are for 8k context. See the best hardware for local AI at every budget.