Hardware
GeForce RTX 4090
GeForce RTX 4090 has 24 GB GDDR6X and 1008 GB/s. See which open models fit, at which quant, and roughly how fast. Figures below use the default memory (24 GB), 32 GB system RAM, and DDR5-5600 for anything that spills. Updated 2026-10-24.
Memory24 GB GDDR6X
Bandwidth1008 GB/s
Kindgpu
Year2022
NVIDIA GeForce RTX 40-series specifications. Bandwidth is the published peak. Source.
RSS for new models on this device
Models that fit
| Model | Verdict | Quant | Context | tok/s |
|---|---|---|---|---|
| GLM 4 32B 0414 32.6B | Tight fit | Q5_K_S | 4K | 24–33 |
| gemma 4 31B it 30.7B | Tight fit | Q5_K_S | 4K | 22–30 |
| Qwen3 32B 32.8B | Tight fit | UD-Q4_K_XL | 8K | 25–34 |
| Qwen3 VL 32B Instruct 32.8B | Tight fit | UD-Q4_K_XL | 8K | 25–34 |
| Qwen2.5 32B Instruct 32.8B | Tight fit | Q4_K_M | 8K | 25–34 |
| Qwen2.5 Coder 32B Instruct 32.8B | Tight fit | Q4_K_M | 8K | 25–34 |
| DeepSeek R1 Distill Qwen 32B 32.8B | Tight fit | Q4_K_M | 8K | 25–34 |
| Swift Qwen3.8 27B 27.3B | Tight fit | Q5_K_M | 8K | 27–36 |
| Qwen3.8 27B 27.3B | Tight fit | UD-Q6_K | 8K | 25–34 |
| gemma 3 27b it 27.0B | Tight fit | Q6_K | 4K | 23–31 |
| medgemma 27b text it 27.0B | Tight fit | Q6_K | 4K | 23–31 |
| Qwen3.6 27B 26.9B | Tight fit | Q6_K | 4K | 24–33 |
| Qwen3.5 27B 26.9B | Tight fit | Q6_K | 4K | 24–33 |
| Devstral Small 2 24B Instruct 2512 23.6B | Tight fit | UD-Q6_K_XL | 8K | 25–34 |
| Mistral Small 3.2 24B Instruct 2506 23.6B | Tight fit | UD-Q6_K_XL | 8K | 25–34 |
| Magistral Small 2509 23.6B | Tight fit | UD-Q6_K_XL | 8K | 25–34 |
| Qwen3.5 35B A3B 34.7B | Tight fit | UD-Q4_K_XL | 8K | 265–361 |
| Qwen3.6 35B A3B 34.7B | Tight fit | UD-Q4_K_XL | 8K | 264–359 |
| Tiel Coder 35B A3B 34.7B | Tight fit | UD-Q4_K_XL | 8K | 264–359 |
| GLM 4.7 Flash 29.9B | Tight fit | UD-Q5_K_XL | 8K | 110–150 |
| Kwaipilot KAT Coder V2.5 Dev 34.7B | Tight fit | Q4_K_M | 8K | 137–187 |
| Cyber Tiel Coder 35B A3B GGUF MTP 35.5B | Tight fit | Q4_K_M (est.) | 8K | 279–381 |
| Qwen3.8 35B A3B Distill 35.5B | Tight fit | Q4_K_M | 8K | 277–378 |
| Qwen3 Coder 30B A3B Instruct 30.5B | Tight fit | UD-Q5_K_XL | 8K | 188–257 |
| Qwen3 30B A3B Instruct 2507 30.5B | Tight fit | UD-Q5_K_XL | 8K | 188–257 |
| Qwen3 VL 30B A3B Instruct 30.5B | Tight fit | UD-Q5_K_XL | 8K | 188–257 |
| Qwen3 30B A3B Thinking 2507 30.5B | Tight fit | UD-Q5_K_XL | 8K | 188–257 |
| DeepSeek R1 Distill Llama 70B 70.6B | Tight fit | UD-IQ2_XXS | 8K | 25–34 |
| Llama 3.3 70B Instruct 70.6B | Tight fit | UD-IQ2_XXS | 8K | 25–34 |
| Hermes 4 70B 70.6B | Tight fit | UD-IQ2_XXS | 8K | 25–34 |
| bottlecapai ThinkingCap gemma 4 26B A4B it 25.2B | Tight fit | Q5_K_M | 8K | 107–146 |
| gemma 4 26B A4B it 25.2B | Tight fit | UD-Q5_K_XL | 8K | 103–141 |
| NVIDIA Nemotron 3.5 Lightning 30B A3B 32.9B | Tight fit | IQ4_NL | 8K | 234–319 |
| Qwen3 Coder Next 79.7B | Tight fit | UD-IQ1_M | 8K | 124–169 |
| Nemotron 3 Nano 30B A3B 31.6B | Tight fit | Q4_K_S | 8K | 219–299 |
| NVIDIA Nemotron 3 Nano Omni 30B A3B Reasoning 31.6B | Tight fit | UD-IQ4_XS | 8K | 242–330 |
| LFM2.5 24B A2B 24.0B | Tight fit | UD-Q6_K_XL | 8K | 222–303 |
| Qwen3 Next 80B A3B Thinking 79.7B | Tight fit | UD-IQ1_S | 2K | 524–715 |
| GLM 4.7 Flash REAP 23B A3B 23.0B | Tight fit | UD-Q6_K_XL | 8K | 180–245 |
| gpt oss 20b 20.9B | Runs great | UD-Q8_K_XL | 8K | 138–188 |
105 more models in the catalog do not fit this default profile, or ranked below the first 40 that do.
Example: Tight fit fully on your GeForce RTX 4090 at Q5_K_S, 4K context, about 24–33 tok/s. Weights 21.0 GB plus 0.24 GB of KV cache — 21.7 GB of 22.3 GB usable. Weights shown in the verdict use GiB (the same 1024³ counting as GPU memory).