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 the US is $380 at eBay; used, it starts at $380 (asking price).
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the US, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| eBayMSI GeForce RTX 5050 Shadow 2X OC 8GB Graphics Card | New | $380 | In stock | 5 h ago | Buy |
| eBayMSI SHADOW GeForce RTX 5050 8GB GDDR6 PCI Express 5.0 Graphics Card RTX 5050 8G | used, asking price | $380 | In stock | 5 h ago | Buy |
| eBayMSI GeForce RTX 5050 8G SHADOW 2X OC NEW | New | $399 | In stock | 5 h ago | Buy |
| eBayNew MSI GeForce RTX 5050 OC 8GB GDDR6 Graphics Card G5050-8S2C Brand New Sealed | New | $399 | In stock | 5 h ago | Buy |
| eBayMSI SHADOW GeForce RTX 5050 8GB GDDR6 PCI Express 5.0 Graphics Card | used, asking price | $399 | In stock | 5 h ago | Buy |
| eBayZOTAC Gaming GeForce RTX 5050 288-1N792-200Z6 | used, asking price | $400 | In stock | 5 h ago | Buy |
| eBayGIGABYTE RTX 5050 8GB vram | used, asking price | $400 | In stock | 5 h ago | Buy |
| eBayASUS Prime GeForce RTX 5050 8GB GDDR6 OC Edition Gaming Graphics Card | used, asking price | $400+ $6 delivery | In stock | 5 h ago | Buy |
| eBayASUS Dual GeForce RTX 5050 8GB GDDR6 OC Edition Graphics Card | New | $410 | In stock | 5 h ago | Buy |
| eBayNEW Zotac GAMING GeForce RTX 5050 Twin Edge OC NVIDIA 8 GB GDDR6 GPU Video Card | New | $425 | In stock | 5 h ago | Buy |
| eBayGIGABYTE RTX 5050 GAMING OC 8GB GDDR6 Triple Fan DLSS 4.5 NEW | New | $425 | In stock | 5 h ago | Buy |
| eBayMSI GeForce RTX 5050 8G SHADOW 2X OC | used, asking price | $430 | In stock | 5 h ago | Buy |
| eBayASUS PRIME GEFORCE RTX 5050 8GB *NEW* SEALED GPU | New | $450+ $6 delivery | In stock | 5 h ago | Buy |
| eBayNEW MSI Geforce RTX 5050 8GB Shadow 2X OC Gaming Graphics Card | New | $520 | In stock | 5 h ago | Buy |
| eBayGIGABYTE GeForce RTX 5050 OC Low Profile 8G Graphics Card | New | $649 | In stock | 5 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 @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 the US?
- The best new price for the NVIDIA GeForce RTX 5050 in the US is $380 at eBay; used, it starts at $380 (asking price).
Speeds on this page are for 128k context. See the best hardware for local AI at every budget.