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 128k context it runs 5 of the 129 open models we track fully in memory; the most capable is Qwen2.5 0.5B at Q8_0, at about 93 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 5050 in Canada is $570 at Amazon.
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in Canada, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| AmazonASUS Dual GeForce RTX 5050 8GB GDDR6 Gaming Gaming Graphics Card | New | $570 | In stock | 4 h ago | Buy |
| AmazonASUS Dual GeForce RTX 5050 8GB GDDR6 OC Edition Gaming Graphics Card | New | $590 | In stock | 4 h ago | Buy |
| AmazonMSI Gaming RTX 5050 8G Shadow 2X OC Graphics Card | New | $595 | In stock | 4 h ago | Buy |
| AmazonGIGABYTE NVIDIA Geforce RTX5050 GDDR6 Graphic Board 8 GB GB-N5050 Gaming OC-8GD | New | $600 | In stock | 4 h ago | Buy |
| AmazonMSI Gaming RTX 5050 8G Ventus 2X OC Graphics Card | New | $600 | In stock | 4 h ago | Buy |
| AmazonGigabyte GeForce RTX 5050 Gaming OC 8G Graphics Card | New | $600 | In stock | 4 h ago | Buy |
| AmazonASUS PRIME GeForce RTX 5050 8GB GDDR6 OC Edition Gaming Graphics Card | New | $620 | In stock | 4 h ago | Buy |
| AmazonMSI GeForce RTX 5050 8G Ventus 2X OC Graphics Card | New | $884 | In stock | 4 h ago | Buy |
| AmazonGigabyte GeForce RTX 5050 WINDFORCE OC 8G Graphics Card | New | $1,054 | In stock | 4 h ago | Buy |
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 @128k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 3.4 GB | 32k | 93tok/sest. | 895 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.7 GB | 256k | 81tok/sest. | 1193 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 4.3 GB | 256k | 65tok/sest. | 763 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 4.7 GB | 256k | 57tok/sest. | 882 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 6.7 GB | 128k | 35tok/sest. | 400 tok/s | chat, coding, long documents |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 24.9 GB | – | 3tok/sest. | 40 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 25.3 GB | – | 3tok/sest. | 40 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 29.3 GB | – | 2tok/sest. | 37 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 24.2 GB | – | 9tok/sest. | 197 tok/s | chat |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 25.2 GB | – | 3tok/sest. | 40 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 19.6 GB | – | 8tok/sest. | 257 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 24.5 GB | – | 9tok/sest. | 196 tok/s | chat |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 25.1 GB | – | 4tok/sest. | 92 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.9 GB | – | 13tok/sest. | 266 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 30.5 GB | – | 13tok/sest. | 139 tok/s | chat |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 183 tok/s | chat |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 30.7 GB | – | 3tok/sest. | 54 tok/s | chat |
| Gemma 4 12B | Q4_K_M | offload | 10.4 GB | – | 11tok/sest. | 143 tok/s | chat |
| Qwen 3.5 9B Alibaba Qwen | Q4_K_M | offload | 10.8 GB | 36k60k with q8 cache | 10tok/sest. | 166 tok/s | chat, coding |
| Gemma 3 27B | Q4_K_M | offload | 27.3 GB | – | 2tok/sest. | 48 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 29.1 GB | – | 2tok/sest. | 44 tok/s | – |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 29.8 GB | – | 2tok/sest. | 37 tok/s | – |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | offload | 24.1 GB | 13k25k with q8 cache | 3tok/sest. | 60 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q4_K_M | offload | 24.1 GB | 13k25k with q8 cache | 3tok/sest. | 60 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q4_K_M | offload | 8.0 GB | 110k182k with q8 cache | 22tok/sest. | 311 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q4_K_M | offload | 23.3 GB | 13k24k with q8 cache | 3tok/sest. | 61 tok/s | chat |
| Granite 4.2 8B IBM | Q4_K_M | offload | 26.6 GB | 9k17k with q8 cache | 2tok/sest. | 53 tok/s | chat |
| Gemma 4 E4B | Q4_K_M | offload | 9.6 GB | 61k100k with q8 cache | 13tok/sest. | 249 tok/s | chat, coding |
| LFM2.5 8B-A1B Liquid AI | UD-Q4_K_M | offload | 12.4 GB | 33k56k with q8 cache | 8tok/sest. | 289 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q4_K_M | offload | 22.0 GB | 16k29k with q8 cache | 3tok/sest. | 67 tok/s | chat |
| FrogNano 4B 2609 Microsoft | Q4_K_M | offload | 8.1 GB | 109k180k with q8 cache | 22tok/sest. | 310 tok/s | chat, coding, agents, long documents |
| MiniCPM5 2B openbmb | Q4_K_M | offload | 8.2 GB | 110k128k with q8 cache | 21tok/sest. | 200 tok/s | chat, coding, agents |
| Spark X2.5 4B XHToken | mlx-4bit | offload | 8.8 GB | 93k156k with q8 cache | 16tok/sest. | 289 tok/s | chat, coding, agents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q4_K_M | offload | 11.5 GB | – | 15tok/sest. | 349 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q4_K_M | offload | 10.5 GB | 79k128k with q8 cache | 11tok/sest. | 219 tok/s | chat, coding, agents |
| LFM2.5 VL 3B Liquid AI | Q4_K_M | offload | 10.5 GB | 32k | 11tok/sest. | 211 tok/s | chat, coding, agents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | offload | 15.1 GB | – | 8tok/sest. | 192 tok/s | chat |
| GLM 4.6V Flash Z.ai | Q4_K_M | offload | 12.2 GB | 21k35k with q8 cache | 8tok/sest. | 68 tok/s | chat, coding |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 16.3 GB | – | 7tok/sest. | 137 tok/s | chat |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q4_K_M | offload | 12.8 GB | 38k66k with q8 cache | 7tok/sest. | 102 tok/s | chat, coding |
| GLM 4 9B 0414 Z.ai | mlx-4bit | offload | 13.0 GB | 2k4k with q8 cache | 7tok/sest. | 68 tok/s | chat |
| granite vision 4.1 4b IBM | Q4_K_M | offload | 13.4 GB | 56k100k with q8 cache | 7tok/sest. | 119 tok/s | chat, coding |
| granite 4.2 3b IBM | Q4_K_M | offload | 13.6 GB | 54k95k with q8 cache | 6tok/sest. | 120 tok/s | chat, coding |
| Ministral 3 3B Instruct 2512 Mistral AI | Q4_K_M | offload | 16.4 GB | 43k78k with q8 cache | 5tok/sest. | 106 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 17.4 GB | – | 4tok/sest. | 58 tok/s | – |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 19.3 GB | – | 4tok/sest. | 48 tok/s | – |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 25.7 GB | – | 3tok/sest. | 127 tok/s | chat |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q4_K_M | offload | 22.0 GB | 16k29k with q8 cache | 3tok/sest. | 67 tok/s | chat |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | offload | 23.3 GB | 13k24k with q8 cache | 3tok/sest. | 61 tok/s | chat |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 28.8 GB | – | 2tok/sest. | 39 tok/s | – |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 29.1 GB | – | 2tok/sest. | 44 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 102.4 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 104.2 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 78.0 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 102.6 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 43.6 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 53.5 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 49.7 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 64.4 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 41.7 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 66.7 GB | – | – | – | – |
| Devstral Small 2 24B Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 49.7 GB | – | – | – | – |
| Qwen3 32B Alibaba Qwen | Q4_K_M | won't run | 51.9 GB | – | – | – | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | won't run | 51.9 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 81.1 GB | – | – | – | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Phi-4 14B Microsoft | Q4_K_M | won't run | 34.7 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 387.2 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 81.1 GB | – | – | – | – |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | won't run | 33.8 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 157.8 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 166.6 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 115.2 GB | – | – | – | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 249.0 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 83.7 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 248.2 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 90.1 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 249.0 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 394.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 432.4 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 446.3 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 758.7 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 101.4 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 588.2 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 161.3 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 161.3 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 147.7 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 256.1 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 115.2 GB | – | – | – | – |
| granite 4.2 30b IBM | Q4_K_M | won't run | 50.2 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?
- Qwen2.5 0.5B (Q8_0) fits fully in its memory at 128k context and generates at about 93 tok/s, an estimate from its memory bandwidth. 5 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 102 GB at 128k context, more than the NVIDIA GeForce RTX 5050 and system RAM can hold.
- How much does the NVIDIA GeForce RTX 5050 cost in Canada?
- The best new price for the NVIDIA GeForce RTX 5050 in Canada is $570 at Amazon.
Speeds on this page are for 128k context. See the best hardware for local AI at every budget.