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 64k context it runs 11 of the 129 open models we track fully in memory; the most capable is Qwen 3.5 4B at Q8_0, at about 30 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 @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.3 GB | 66k110k with q8 cache | 30tok/sest. | 435 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.3 GB | 32k | 149tok/sest. | 1557 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.6 GB | 256k | 121tok/sest. | 1765 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.2 GB | 256k | 88tok/sest. | 962 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 3.6 GB | 256k | 75tok/sest. | 1161 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 4.6 GB | 128k | 53tok/sest. | 645 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.2 GB | 89k128k with q8 cache | 36tok/sest. | 363 tok/s | chat, coding, agents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.2 GB | 93k156k with q8 cache | 36tok/sest. | 446 tok/s | chat, coding, agents |
| FrogNano 4B 2609 Microsoft | Q6_K | fits | 6.6 GB | 84k140k with q8 cache | 33tok/sest. | 435 tok/s | chat, coding, agents |
| LFM2.5 2.6B Liquid AI | Q6_K | fits | 6.9 GB | 71k125k with q8 cache | 32tok/sest. | 441 tok/s | chat, coding, agents |
| LFM2.5 VL 3B Liquid AI | Q6_K | fits | 6.9 GB | 32k | 32tok/sest. | 414 tok/s | chat, coding, agents |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 20.5 GB | – | 3tok/sest. | 52 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 20.9 GB | – | 3tok/sest. | 51 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 23.9 GB | – | 3tok/sest. | 45 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 22.6 GB | – | 13tok/sest. | 300 tok/s | chat |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 20.8 GB | – | 3tok/sest. | 51 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 17.9 GB | – | 11tok/sest. | 334 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.9 GB | – | 13tok/sest. | 299 tok/s | chat |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 21.4 GB | – | 6tok/sest. | 152 tok/s | – |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 48 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.1 GB | – | 15tok/sest. | 368 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.6 GB | – | 16tok/sest. | 223 tok/s | chat |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 13.4 GB | – | 13tok/sest. | 282 tok/s | chat |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.4 GB | – | 5tok/sest. | 105 tok/s | chat |
| Gemma 4 12B | Q4_K_M | offload | 9.0 GB | – | 15tok/sest. | 180 tok/s | chat |
| Qwen 3.5 9B Alibaba Qwen | Q4_K_M | offload | 8.4 GB | 36k60k with q8 cache | 18tok/sest. | 230 tok/s | chat, coding |
| Gemma 3 27B | Q4_K_M | offload | 21.9 GB | – | 3tok/sest. | 57 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 48 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 18.7 GB | – | 4tok/sest. | 74 tok/s | – |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 19.5 GB | – | 4tok/sest. | 64 tok/s | – |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | offload | 14.8 GB | 13k25k with q8 cache | 6tok/sest. | 112 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q4_K_M | offload | 14.8 GB | 13k25k with q8 cache | 6tok/sest. | 112 tok/s | chat |
| Phi-4 14B Microsoft | Q4_K_M | offload | 21.9 GB | – | 3tok/sest. | 62 tok/s | – |
| Ministral 3 8B Mistral AI | Q4_K_M | offload | 14.4 GB | 13k24k with q8 cache | 6tok/sest. | 112 tok/s | chat |
| Granite 4.2 8B IBM | Q4_K_M | offload | 16.2 GB | 9k17k with q8 cache | 5tok/sest. | 99 tok/s | chat |
| Gemma 4 E4B | Q4_K_M | offload | 7.5 GB | 61k100k with q8 cache | 28tok/sest. | 326 tok/s | chat, coding |
| LFM2.5 8B-A1B Liquid AI | UD-Q4_K_M | offload | 9.0 GB | 33k56k with q8 cache | 20tok/sest. | 616 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q4_K_M | offload | 13.7 GB | 16k29k with q8 cache | 6tok/sest. | 125 tok/s | chat |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q4_K_M | offload | 10.2 GB | – | 23tok/sest. | 531 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q4_K_M | offload | 8.0 GB | 56k100k with q8 cache | 21tok/sest. | 262 tok/s | chat, coding |
| granite 4.2 3b IBM | Q4_K_M | offload | 8.2 GB | 54k95k with q8 cache | 20tok/sest. | 266 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q4_K_M | offload | 8.9 GB | 38k66k with q8 cache | 15tok/sest. | 184 tok/s | chat, coding |
| GLM 4.6V Flash Z.ai | Q4_K_M | offload | 9.3 GB | 21k35k with q8 cache | 14tok/sest. | 121 tok/s | chat, coding |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | offload | 12.8 GB | – | 13tok/sest. | 324 tok/s | chat |
| Ministral 3 3B Instruct 2512 Mistral AI | Q4_K_M | offload | 9.6 GB | 43k78k with q8 cache | 13tok/sest. | 232 tok/s | chat, coding |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 14.0 GB | – | 12tok/sest. | 244 tok/s | chat |
| GLM 4 9B 0414 Z.ai | mlx-4bit | offload | 10.2 GB | 2k4k with q8 cache | 11tok/sest. | 120 tok/s | chat |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 20.4 GB | – | 6tok/sest. | 240 tok/s | chat |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q4_K_M | offload | 13.7 GB | 16k29k with q8 cache | 6tok/sest. | 125 tok/s | chat |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 14.5 GB | – | 6tok/sest. | 96 tok/s | – |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | offload | 14.4 GB | 13k24k with q8 cache | 6tok/sest. | 112 tok/s | chat |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 18.1 GB | – | 4tok/sest. | 54 tok/s | – |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 18.7 GB | – | 4tok/sest. | 74 tok/s | – |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 21.4 GB | – | 3tok/sest. | 56 tok/s | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 49 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 49 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 49 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 48 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 24.5 GB | – | 3tok/sest. | 49 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 96.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.1 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.1 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 86.7 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 41.7 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.6 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 47.8 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 61.8 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 39.9 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 54.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 47.8 GB | – | – | – | – |
| Qwen3 32B Alibaba Qwen | Q4_K_M | won't run | 35.5 GB | – | – | – | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | won't run | 35.6 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 60.7 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 382.5 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 60.7 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.1 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 160.9 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 92.8 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 225.7 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 71.8 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 224.9 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 78.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 225.7 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 388.9 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 426.5 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 440.4 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 752.9 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 81.0 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 583.5 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 145.4 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 145.4 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 131.8 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 248.3 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 92.8 GB | – | – | – | – |
| granite 4.2 30b IBM | Q4_K_M | won't run | 33.9 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 4B (Q8_0) fits fully in its memory at 64k context and generates at about 30 tok/s, an estimate from its memory bandwidth. 11 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 97 GB at 64k 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 64k context. See the best hardware for local AI at every budget.