NVIDIA GeForce RTX 4090
24 GB · 1,008 GB/s · 450 W
Prices
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No retailer in this market lists it right now.
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 @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | UD-Q6_K | fits | 21.9 GB | 30k53k with q8 cache | 28tok/sest. | 1299 tok/s | chat, coding |
| Qwen 3.6 27B Alibaba Qwen | Q6_K | fits | 22.4 GB | 23k40k with q8 cache | 27tok/sest. | 1299 tok/s | chat |
| Gemma 4 31B | Q5_K_M | fits | 22.3 GB | 20k44k with q8 cache | 27tok/sest. | 1132 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q4_K_M | fits | 21.6 GB | 79k124k with q8 cache | 181tok/sest. | 11130 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q6_K | fits | 22.3 GB | 24k42k with q8 cache | 27tok/sest. | 1299 tok/s | chat, coding |
| Gemma 4 26B-A4B | UD-Q6_K | fits | 22.7 GB | 36k62k with q8 cache | 95tok/sest. | 8481 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | fits | 21.5 GB | 84k131k with q8 cache | 181tok/sest. | 11130 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q5_K_M | fits | 21.1 GB | 48k82k with q8 cache | 94tok/sest. | 6229 tok/s | chat, coding, agents |
| Devstral Small 2 24B Mistral AI | Q6_K | fits | 20.0 GB | 28k52k with q8 cache | 30tok/sest. | 1464 tok/s | chat, coding |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.2 GB | 128k | 142tok/sest. | 8056 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q5_K_M | fits | 21.7 GB | 24k44k with q8 cache | 128tok/sest. | 8052 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | fits | 21.2 GB | 16k30k with q8 cache | 29tok/sest. | 1002 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 13.0 GB | 256k | 48tok/sest. | 2955 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 9.9 GB | 256k | 64tok/sest. | 3742 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q6_K | fits | 20.0 GB | 28k52k with q8 cache | 30tok/sest. | 1464 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | fits | 21.2 GB | 16k30k with q8 cache | 28tok/sest. | 1047 tok/s | chat |
| Gemma 3 27B | Q6_K | fits | 22.4 GB | 19k38k with q8 cache | 27tok/sest. | 1316 tok/s | chat |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 15.4 GB | 57k104k with q8 cache | 40tok/sest. | 2429 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 16.6 GB | 40k | 37tok/sest. | 2257 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.0 GB | 99k128k with q8 cache | 63tok/sest. | 3950 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.0 GB | 40k | 63tok/sest. | 3950 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q8_0 | fits | 16.8 GB | 16k | 36tok/sest. | 2272 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.2 GB | 256k | 130tok/sest. | 7533 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.2 GB | 103k187k with q8 cache | 62tok/sest. | 3691 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 10.7 GB | 86k128k with q8 cache | 59tok/sest. | 3664 tok/s | chat, coding, agents |
| Gemma 4 E4B | Q8_0 | fits | 8.6 GB | 128k | 74tok/sest. | 4535 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 9.5 GB | 125k | 256tok/sest. | 26468 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 7.9 GB | 126k128k with q8 cache | 82tok/sest. | 4078 tok/s | chat, coding, long documents |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.0 GB | – | 18tok/sest. | 2563 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 46.2 GB | – | 23tok/sest. | 6067 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 38.4 GB | – | 28tok/sest. | 3418 tok/s | chat, coding |
| GLM 4.5 Air Z.ai | Q2_K | offload | 44.4 GB | – | 7tok/sest. | 1219 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 46.2 GB | – | 29tok/sest. | 7628 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 33.4 GB | – | 26tok/sest. | 9460 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 28.8 GB | – | 63tok/sest. | 9348 tok/s | chat, coding, long documents |
| Llama 3.3 70B Meta | Q4_K_M | offload | 42.8 GB | – | 2tok/sest. | 354 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 91.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.2 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 74.5 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 72.8 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 51.9 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 60.1 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 4090
- Memory
- 24 GB GDDR6X
- Memory bus
- 384-bit
- Memory bandwidth
- 1,008 GB/s
- FP16 compute
- 165 TFLOPS
- Software
- CUDA
- Board power
- 450 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16