NVIDIA GeForce RTX 5050
8 GB · 320 GB/s · 130 W
In short
The NVIDIA GeForce RTX 5050 has 8 GB of GDDR6 memory with 320 GB/s of bandwidth, which sets how fast it generates text. At 32k context it runs 18 of the 129 open models we track fully in memory; the most capable is Qwen 3.5 9B at Q4_K_M, at about 29 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 5050 in the UK is £370 at eBay; used, it starts at £300 (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 |
|---|---|---|---|---|---|
| eBayMSI NVIDIA GeForce RTX 5050 8GB SHADOW 2X Gaming Graphics Card Expert Tested | used, asking price | £300 | In stock | 2 h ago | Buy |
| eBayASUS Dual GeForce RTX 5050 OC 8GB | used, asking price | £299+ £7 delivery | In stock | 2 h ago | Buy |
| eBayMSI GeForce RTX 5050 VENTUS 2X OC 8GB GDDR6 PCIe x16 DP HDMI | used, asking price | £350+ £6 delivery | In stock | 2 h ago | Buy |
| eBayPalit NVIDIA GeForce RTX 5050 STORMX OC 8GB GDDR6 Ray-Tracing Graphics Card | New | £370 | In stock | 2 h ago | Buy |
| eBayASUS PRIME NVIDIA GeForce RTX 5050 OC 8GB GDDR6 Ray-Tracing Graphics Card | New | £382 | In stock | 2 h ago | Buy |
| eBayMSI GeForce RTX 5050 8G GAMING OC Graphics Card RTX 5050 GPU | New | £398 | In stock | 2 h ago | Buy |
| eBayMSI NVIDIA GeForce RTX 5050 GAMING OC 8GB PCIe x16 DLSS 4 | New | £392+ £9 delivery | In stock | 2 h ago | Buy |
| eBayPNY NVIDIA GeForce RTX 5050 SINGLE FAN 8GB GDDR6 Ray-Tracing Graphics Card | New | £401 | In stock | 2 h ago | Buy |
| eBayASUS NVIDIA GeForce RTX 5050 | New | £394+ £9 delivery | In stock | 2 h ago | Buy |
| eBayASUS DUAL NVIDIA GeForce RTX 5050 8GB OC GDDR6 Ray-Tracing Graphics Card | New | £422 | In stock | 2 h ago | Buy |
| eBayAsus 90YV0N72-M0NA00 Dual -Rtx5050-O8G Nvidia | New | £612 | In stock | 2 h ago | Buy |
Price history
Lowest price shown each day over the last 90 days.
Not enough price history yet.
What it runs
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.5 9B Alibaba Qwen | Q4_K_M | fits | 7.2 GB | 36k60k with q8 cache | 29tok/sest. | 276 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.1 GB | 66k110k with q8 cache | 35tok/sest. | 517 tok/s | chat, coding |
| Gemma 4 E4B | Q5_K_M | fits | 6.9 GB | 46k77k with q8 cache | 31tok/sest. | 347 tok/s | chat, coding |
| LFM2.5 8B-A1B Liquid AI | MXFP4 | fits | 7.4 GB | 32k55k with q8 cache | 53tok/sest. | 1135 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.8 GB | 32k | 213tok/sest. | 2472 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.0 GB | 256k | 161tok/sest. | 2322 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.6 GB | 256k | 107tok/sest. | 1107 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 3.0 GB | 256k | 88tok/sest. | 1378 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.5 GB | 128k | 70tok/sest. | 930 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.7 GB | 89k128k with q8 cache | 49tok/sest. | 555 tok/s | chat, coding, agents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 4.9 GB | 93k156k with q8 cache | 46tok/sest. | 545 tok/s | chat, coding, agents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 5.4 GB | 62k108k with q8 cache | 41tok/sest. | 629 tok/s | chat, coding, agents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 5.4 GB | 32k | 41tok/sest. | 577 tok/s | chat, coding, agents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 6.2 GB | 63k104k with q8 cache | 35tok/sest. | 517 tok/s | chat, coding, agents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 6.8 GB | 39k70k with q8 cache | 32tok/sest. | 403 tok/s | chat, coding |
| Ministral 3 3B Instruct 2512 Mistral AI | Q6_K | fits | 6.8 GB | 37k68k with q8 cache | 31tok/sest. | 404 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q4_K_M | fits | 7.0 GB | 38k66k with q8 cache | 30tok/sest. | 272 tok/s | chat, coding |
| granite 4.2 3b IBM | Q8_0 | fits | 7.0 GB | 36k64k with q8 cache | 30tok/sest. | 422 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 18.4 GB | – | 4tok/sest. | 60 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 18.7 GB | – | 4tok/sest. | 59 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 21.2 GB | – | 3tok/sest. | 50 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 21.8 GB | – | 16tok/sest. | 401 tok/s | chat |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 18.6 GB | – | 4tok/sest. | 59 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 17.1 GB | – | 13tok/sest. | 389 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.1 GB | – | 16tok/sest. | 399 tok/s | chat |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 19.6 GB | – | 9tok/sest. | 217 tok/s | – |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 62 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 22.7 GB | – | 17tok/sest. | 451 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.2 GB | – | 18tok/sest. | 317 tok/s | chat |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 12.5 GB | – | 17tok/sest. | 376 tok/s | chat |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 21.2 GB | – | 8tok/sest. | 186 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 27.3 GB | – | 2tok/sest. | 33 tok/s | – |
| Gemma 4 12B | Q4_K_M | offload | 8.3 GB | – | 19tok/sest. | 205 tok/s | chat |
| Gemma 3 27B | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 62 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 62 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 27.4 GB | – | 2tok/sest. | 37 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 13.6 GB | – | 6tok/sest. | 109 tok/s | – |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 14.3 GB | – | 6tok/sest. | 96 tok/s | – |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | offload | 10.1 GB | 13k25k with q8 cache | 11tok/sest. | 188 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q4_K_M | offload | 10.1 GB | 13k25k with q8 cache | 11tok/sest. | 188 tok/s | chat |
| Phi-4 14B Microsoft | Q4_K_M | offload | 15.4 GB | – | 5tok/sest. | 93 tok/s | – |
| Ministral 3 8B Mistral AI | Q4_K_M | offload | 10.0 GB | 13k24k with q8 cache | 12tok/sest. | 182 tok/s | chat |
| Granite 4.2 8B IBM | Q4_K_M | offload | 11.0 GB | 9k17k with q8 cache | 9tok/sest. | 164 tok/s | chat |
| Llama 3.1 8B Meta | Q4_K_M | offload | 9.5 GB | 16k29k with q8 cache | 13tok/sest. | 206 tok/s | chat |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q4_K_M | offload | 9.6 GB | – | 31tok/sest. | 696 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q4_K_M | offload | 7.9 GB | 21k35k with q8 cache | 22tok/sest. | 181 tok/s | chat, coding |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | offload | 11.7 GB | – | 20tok/sest. | 470 tok/s | chat |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 12.9 GB | – | 17tok/sest. | 377 tok/s | chat |
| GLM 4 9B 0414 Z.ai | mlx-4bit | offload | 8.7 GB | 2k4k with q8 cache | 16tok/sest. | 180 tok/s | chat |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q4_K_M | offload | 9.5 GB | 16k29k with q8 cache | 13tok/sest. | 206 tok/s | chat |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | offload | 10.0 GB | 13k24k with q8 cache | 12tok/sest. | 182 tok/s | chat |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 17.7 GB | – | 11tok/sest. | 400 tok/s | chat |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 13.1 GB | – | 7tok/sest. | 136 tok/s | – |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 13.6 GB | – | 6tok/sest. | 109 tok/s | – |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 15.3 GB | – | 5tok/sest. | 87 tok/s | – |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 17.5 GB | – | 4tok/sest. | 59 tok/s | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 63 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 63 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 63 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 62 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 22.3 GB | – | 3tok/sest. | 56 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 25.7 GB | – | 3tok/sest. | 44 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 93.8 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.6 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 75.2 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 78.8 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 40.7 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.2 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 46.9 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 60.5 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 39.0 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 48.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 46.9 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 50.5 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 380.2 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 50.5 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 149.2 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 158.0 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 81.6 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 214.0 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 65.9 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 213.2 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 72.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 214.0 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 386.0 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 423.6 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 437.5 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 750.0 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 70.8 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 581.2 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 137.5 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 137.5 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 123.9 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 244.3 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 81.6 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 5050
- Memory
- 8 GB GDDR6
- Memory bus
- 128-bit
- Memory bandwidth
- 320 GB/s
- FP16 compute
- 13.169 TFLOPS
- Software
- CUDA
- Board power
- 130 W
- PCIe generation
- Gen 5
- PCIe lanes
- x8
Compare with
Questions
- How much memory does the NVIDIA GeForce RTX 5050 have for AI models?
- The NVIDIA GeForce RTX 5050 has 8 GB of GDDR6 memory with 320 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA GeForce RTX 5050 can run locally?
- Qwen 3.5 9B (Q4_K_M) fits fully in its memory at 32k context and generates at about 29 tok/s, an estimate from its memory bandwidth. 18 of the 129 models we track fit at that context.
- Can the NVIDIA GeForce RTX 5050 run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 94 GB at 32k context, more than the NVIDIA GeForce RTX 5050 and system RAM can hold.
- How much does the NVIDIA GeForce RTX 5050 cost in the UK?
- The best new price for the NVIDIA GeForce RTX 5050 in the UK is £370 at eBay; used, it starts at £300 (asking price).
Speeds on this page are for 32k context. See the best hardware for local AI at every budget.