GeForce RTX 4080 SUPER
NVIDIA GeForce RTX 4080 SUPER: 16 GB of memory at 736 GB/s. Below: the open models it can run, estimated at 16 GB with an 8K context. 16 GB of GDDR6X at 736 GB/s: quick with models up to about 24B at 4-bit, but the 16 GB capacity caps what you can load.
Last updated: 2026-10-14
Specifications
What it can run
Best-quality quantization that fits with a 8K context, and the estimated generation speed. Estimates, not benchmarks. See the methodology.
| Model | Params | Best quant | Memory | tok/s (est.) |
|---|---|---|---|---|
| Gemma 4 26B A4B IT | 25.2B (3.8B) | Q4_K_M | 15.7 GiB | 224 |
| Mistral Small 3.2 24B Instruct (2506) | 24B | Q4_K_M | 16.0 GiB | 35 |
| Magistral Small 1.2 (2509) | 24B | Q4_K_M | 16.0 GiB | 35 |
| Devstral Small 2 24B Instruct (2512) | 24B | Q4_K_M | 16.0 GiB | 35 |
| gpt-oss-20b | 21B (3.6B) | Q5_K_M | 15.3 GiB | 201 |
| Phi-4 (14B) | 14B | Q6_K | 13.3 GiB | 45 |
| Gemma 3 12B IT | 12B | Q8_0 | 13.8 GiB | 40 |
| Gemma 4 12B Unified IT | 11.95B | Q8_0 | 13.3 GiB | 41 |
| Qwen3.5-9B | 9B | Q8_0 | 10.1 GiB | 54 |
| Qwen3-8B | 8.2B | Q8_0 | 10.1 GiB | 59 |
| DeepSeek-R1-0528-Qwen3-8B | 8.19B | Q8_0 | 10.1 GiB | 59 |
| Llama 3.1 8B Instruct | 8B | Q8_0 | 9.8 GiB | 61 |
| Gemma 4 E4B IT | 8B | Q8_0 | 9.1 GiB | 61 |
| Llama 3.2 3B Instruct | 3.21B | FP16 | 7.7 GiB | 80 |
| Kimi K2.6 | 1000B (32B) | Doesn't fit | – | – |
| DeepSeek-R1-0528 (671B) | 671B (37B) | Doesn't fit | – | – |
| DeepSeek-V4-Flash | 284B (13B) | Doesn't fit | – | – |
| Qwen3.8-Flash-Next | 180B (6B) | Doesn't fit | – | – |
| Qwen3.5-122B-A10B | 122B (10B) | Doesn't fit | – | – |
| Mistral Small 4 119B (2603) | 119B (6.5B) | Doesn't fit | – | – |
| gpt-oss-120b | 117B (5.1B) | Doesn't fit | – | – |
| Llama 4 Scout 17B-16E Instruct | 109B (17B) | Doesn't fit | – | – |
| GLM-4.5-Air | 106B (12B) | Doesn't fit | – | – |
| Qwen3-Coder-Next (80B-A3B) | 80B (3B) | Doesn't fit | – | – |
| Llama 3.3 70B Instruct | 70B | Doesn't fit | – | – |
| Qwen3.5-35B-A3B | 35B (3B) | Doesn't fit | – | – |
| Qwen3.6-35B-A3B | 35B (3B) | Doesn't fit | – | – |
| Qwen3-32B | 32.8B | Doesn't fit | – | – |
| DeepSeek-R1-Distill-Qwen-32B | 32.76B | Doesn't fit | – | – |
| Gemma 4 31B IT | 30.7B | Doesn't fit | – | – |
| Qwen3-30B-A3B (2507) | 30.5B (3.3B) | Doesn't fit | – | – |
| Qwen3-Coder-30B-A3B-Instruct | 30.5B (3.3B) | Doesn't fit | – | – |
| GLM-4.7-Flash (30B-A3B) | 30B (3B) | Doesn't fit | – | – |
| Qwen3.5-27B | 27B | Doesn't fit | – | – |
| Qwen3.6-27B | 27B | Doesn't fit | – | – |
| Qwen3.8-27B | 27B | Doesn't fit | – | – |
| Gemma 3 27B IT | 27B | Doesn't fit | – | – |
Prices
No prices recorded for this device yet. All prices →
Frequently asked questions
Which LLMs can the GeForce RTX 4080 SUPER run?
With 16 GB and an 8K context, the largest models that fit include: Gemma 4 26B A4B IT, Mistral Small 3.2 24B Instruct (2506), Magistral Small 1.2 (2509), Devstral Small 2 24B Instruct (2512), gpt-oss-20b. See the full table below.
How fast is the GeForce RTX 4080 SUPER for local LLMs?
Generation speed is mostly set by memory bandwidth (736 GB/s). For Llama 3.1 8B Instruct at Q8_0, expect roughly 61 tokens/s; bigger models are slower.
Can the GeForce RTX 4080 SUPER run 70B models?
Llama 3.3 70B Instruct does not fit on the GeForce RTX 4080 SUPER (16 GB), even at Q4_K_M with an 8K context.