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 8k context it runs 38 of the 129 open models we track fully in memory; the most capable is gpt-oss 20B at MXFP4, at about 45 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 | 5 h ago | Buy |
| AmazonASUS Dual GeForce RTX 5050 8GB GDDR6 OC Edition Gaming Graphics Card | New | $590 | In stock | 5 h ago | Buy |
| AmazonMSI Gaming RTX 5050 8G Shadow 2X OC Graphics Card | New | $595 | In stock | 5 h ago | Buy |
| AmazonGIGABYTE NVIDIA Geforce RTX5050 GDDR6 Graphic Board 8 GB GB-N5050 Gaming OC-8GD | New | $600 | In stock | 5 h ago | Buy |
| AmazonMSI Gaming RTX 5050 8G Ventus 2X OC Graphics Card | New | $600 | In stock | 5 h ago | Buy |
| AmazonGigabyte GeForce RTX 5050 Gaming OC 8G Graphics Card | New | $600 | In stock | 5 h ago | Buy |
| AmazonASUS PRIME GeForce RTX 5050 8GB GDDR6 OC Edition Gaming Graphics Card | New | $620 | In stock | 5 h ago | Buy |
| AmazonMSI GeForce RTX 5050 8G Ventus 2X OC Graphics Card | New | $884 | In stock | 5 h ago | Buy |
| AmazonGigabyte GeForce RTX 5050 WINDFORCE OC 8G Graphics Card | New | $1,054 | In stock | 5 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 |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.6 GB | 82k128k with q8 cache | 45tok/sest. | 643 tok/s | chat, coding, agents |
| Gemma 4 12B | Q8_0 | fits | 13.4 GB | 73k122k with q8 cache | 15tok/sest. | 236 tok/s | chat |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.3 GB | 128k212k with q8 cache | 20tok/sest. | 299 tok/s | chat |
| Ministral 3 14B Mistral AI | Q6_K | fits | 12.7 GB | 20k37k with q8 cache | 16tok/sest. | 194 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q6_K | fits | 13.7 GB | 14k27k with q8 cache | 15tok/sest. | 180 tok/s | – |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.4 GB | 38k69k with q8 cache | 20tok/sest. | 315 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.4 GB | 38k40k with q8 cache | 20tok/sest. | 315 tok/s | chat |
| Phi-4 14B Microsoft | Q6_K | fits | 13.9 GB | 12k16k with q8 cache | 15tok/sest. | 181 tok/s | – |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.6 GB | 255k256k with q8 cache | 41tok/sest. | 601 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.6 GB | 38k69k with q8 cache | 20tok/sest. | 295 tok/s | chat |
| Granite 4.2 8B IBM | Q8_0 | fits | 11.1 GB | 30k56k with q8 cache | 19tok/sest. | 292 tok/s | chat |
| Gemma 4 E4B | Q8_0 | fits | 9.0 GB | 128k | 23tok/sest. | 362 tok/s | chat, coding |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 9.9 GB | 100k125k with q8 cache | 81tok/sest. | 2112 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q6_K | fits | 8.3 GB | 57k104k with q8 cache | 26tok/sest. | 326 tok/s | chat |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.7 GB | 32k | 314tok/sest. | 4421 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.0 GB | 256k | 213tok/sest. | 3042 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.6 GB | 256k | 128tok/sest. | 1248 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 3.0 GB | 256k | 101tok/sest. | 1603 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.1 GB | 128k | 93tok/sest. | 1392 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.0 GB | 128k | 65tok/sest. | 920 tok/s | chat, coding, agents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 4.3 GB | 128k | 59tok/sest. | 926 tok/s | chat, coding, agents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 4.3 GB | 32k | 59tok/sest. | 817 tok/s | chat, coding, agents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 4.3 GB | 263k441k with q8 cache | 58tok/sest. | 655 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | fits | 11.2 GB | 109k128k with q8 cache | 55tok/sest. | 858 tok/s | chat, coding |
| granite vision 4.1 4b IBM | Q8_0 | fits | 5.1 GB | 122k128k with q8 cache | 46tok/sest. | 613 tok/s | chat, coding |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 5.4 GB | 95k172k with q8 cache | 44tok/sest. | 628 tok/s | chat, coding |
| granite 4.2 3b IBM | Q8_0 | fits | 5.4 GB | 119k128k with q8 cache | 44tok/sest. | 659 tok/s | chat, coding |
| Kimi VL A3B Moonshot AI | mlx-6bit | fits | 14.3 GB | 23k37k with q8 cache | 43tok/sest. | 805 tok/s | chat, coding, agents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.3 GB | 83k125k with q8 cache | 42tok/sest. | 1018 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 5.7 GB | 251k256k with q8 cache | 40tok/sest. | 601 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 9.1 GB | 101k128k with q8 cache | 23tok/sest. | 351 tok/s | chat |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 9.1 GB | 32k | 23tok/sest. | 276 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 10.1 GB | 43k79k with q8 cache | 21tok/sest. | 326 tok/s | chat |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 10.6 GB | 38k69k with q8 cache | 20tok/sest. | 295 tok/s | chat |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 10.8 GB | 97k128k with q8 cache | 19tok/sest. | 255 tok/s | chat |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 12.4 GB | 60k64k with q8 cache | 16tok/sest. | 255 tok/s | chat |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q6_K | fits | 12.7 GB | 20k37k with q8 cache | 16tok/sest. | 194 tok/s | chat |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q6_K | fits | 13.9 GB | 12k22k with q8 cache | 14tok/sest. | 177 tok/s | – |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 17.1 GB | – | 8tok/sest. | 95 tok/s | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.4 GB | – | 12tok/sest. | 167 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 17.4 GB | – | 8tok/sest. | 94 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 19.6 GB | – | 6tok/sest. | 76 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 38.8 GB | – | 17tok/sest. | 221 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 21.6 GB | – | 31tok/sest. | 712 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 17.4 GB | – | 8tok/sest. | 94 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 16.9 GB | – | 30tok/sest. | 623 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 21.9 GB | – | 30tok/sest. | 707 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 18.6 GB | – | 22tok/sest. | 432 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 15.7 GB | 2k3k with q8 cache | 11tok/sest. | 112 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 22.9 GB | – | 26tok/sest. | 720 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 19.2 GB | – | 27tok/sest. | 549 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.2 GB | – | 26tok/sest. | 584 tok/s | chat, coding |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 21.6 GB | – | 5tok/sest. | 64 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 15.7 GB | 2k3k with q8 cache | 11tok/sest. | 112 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 17.6 GB | – | 8tok/sest. | 94 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 21.6 GB | – | 5tok/sest. | 67 tok/s | – |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 16.1 GB | – | 50tok/sest. | 1053 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 15.7 GB | 2k3k with q8 cache | 11tok/sest. | 114 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 15.7 GB | 2k3k with q8 cache | 11tok/sest. | 114 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 15.7 GB | 2k3k with q8 cache | 11tok/sest. | 114 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 15.7 GB | 2k3k with q8 cache | 11tok/sest. | 112 tok/s | – |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 17.4 GB | – | 8tok/sest. | 87 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 19.9 GB | – | 6tok/sest. | 79 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 21.0 GB | – | 5tok/sest. | 84 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 92.0 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 | 74.9 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 73.2 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.3 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 46.6 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 59.9 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 44.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 46.6 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 43.2 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 43.2 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 147.5 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 156.2 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 73.7 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 205.6 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 61.8 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 204.8 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 68.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 205.6 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 384.2 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 421.8 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 435.7 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 748.2 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 63.6 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 579.8 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 131.9 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 131.9 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 118.4 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 241.8 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 73.7 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?
- gpt-oss 20B (MXFP4) fits fully in its memory at 8k context and generates at about 45 tok/s, an estimate from its memory bandwidth. 38 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 92 GB at 8k 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 8k context. See the best hardware for local AI at every budget.