What LLMs can a GeForce RTX 4080 Super run?

Your rig

GeForce RTX 4080 Super · 16 GB

32 GB system RAM · Ada Lovelace · 736 GB/s · 14.4 GB usable VRAM

Which one should I actually run?

Best models for your GeForce RTX 4080 Super

Updated 21 Aug 2026 5 new this week, 14 this month

What do you want to do? Each row is the best-ranked model on that use case's shortlist that fits at Q6_K and 128K. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

All General assistant Coding Reasoning & maths Writing Vision Agents & tool use Translation Low latency Long context

Recommendation	Model	Why	Quant · total	Tok/s est.
Best overall	Qwen3.5 9B Alibaba · Apache 2.0	The 8–12 GB default of 2026 — beats every older 8B, with vision.	Q6_K · 12.0 GB	60	Runs great Run
Best for coding	Qwen3.5 9B Alibaba · Apache 2.0	The best coding model for 8–12 GB cards.	Q6_K · 12.0 GB	60	Runs great Run
Best reasoning	Qwen3.5 9B Alibaba · Apache 2.0	Thinking mode on a 12 GB card — ahead of the 2025 R1 distills.	Q6_K · 12.0 GB	60	Runs great Run
Best for writing	Gemma 4 E4B Google · Apache 2.0	Readable prose on a laptop.	Q6_K · 8.5 GB	73	Runs great Run
Best vision	Qwen3.5 9B Alibaba · Apache 2.0	Vision on an 8–12 GB card.	Q6_K · 12.0 GB	60	Runs great Run
Best for agents	Qwen3.5 9B Alibaba · Apache 2.0	Tool use on 8–12 GB.	Q6_K · 12.0 GB	60	Runs great Run
Best translation	Qwen3.5 9B Alibaba · Apache 2.0	Strong CJK and European translation in 8–12 GB.	Q6_K · 12.0 GB	60	Runs great Run
Fastest good model	LFM2.5 8B-A1B Liquid AI · LFM Open License v1.0	1.5B active; designed for laptops without a GPU.	Q6_K · 8.5 GB	150	Runs great Run
Best long context	Qwen3.5 9B Alibaba · Apache 2.0	262K native in 8–12 GB.	Q6_K · 12.0 GB at 128K context	60	Runs great Run

Everything that fits

Runs great

17 of 76 · fits with headroom for a longer prompt

Model	Params	Quant	Weights	+KV 128K	Total	VRAM headroom	Tok/s	Runtime
Qwen3.5 9B	9.65B	Q6_K	7.4 GB	4.00 GB	12.0 GB	2.4 GB free	60	Ollama	Run
Ornith 1.5 9B New this week	9.41B	Q6_K	7.2 GB	4.00 GB	11.8 GB	2.6 GB free	62	Ollama	Run
LFM2.5 8B-A1B	8.47B MoE / 1.5B act	Q6_K	6.5 GB	1.46 GB	8.5 GB	5.9 GB free	150	Ollama	Run
Gemma 4 E4B	8.0B	Q6_K	6.1 GB	1.78 GB	8.5 GB	5.9 GB free	73	Ollama	Run
Ling 3.0 Tiny 7.9B-A1.3B New	7.9B MoE / 1.3B act	Q6_K	6.0 GB	0.84 GB	7.5 GB	6.9 GB free	173	llama.cpp	Run
Mistral 7B Instruct v0.3	7.25B	Q6_K	5.5 GB	4.00 GB	10.1 GB	4.3 GB free	80	Ollama	Run
Gemma 4 E2B	5.1B	Q6_K	3.9 GB	0.89 GB	5.4 GB	9.0 GB free	114	Ollama	Run
Qwen3.5 4B	4.66B	Q6_K	3.6 GB	4.00 GB	8.2 GB	6.2 GB free	125	Ollama	Run
Gemma 3 4B	4.3B	Q6_K	3.3 GB	3.11 GB	7.0 GB	7.4 GB free	136	Ollama	Run
Qwen3 4B	4.02B	Q6_K	3.1 GB	4.50 GB	8.2 GB	6.2 GB free	145	Ollama	Run
LFM2.5 2.6B New	2.7B	Q6_K	2.1 GB	2.00 GB	4.7 GB	9.7 GB free	216	llama.cpp	Run
Qwen3.5 2B	2.27B	Q6_K	1.7 GB	1.50 GB	3.8 GB	10.6 GB free	257	Ollama	Run
Qwen3 1.7B	1.72B	Q6_K	1.3 GB	3.50 GB	5.4 GB	9.0 GB free	339	Ollama	Run
Llama 3.2 1B Instruct	1.24B	Q6_K	0.9 GB	4.00 GB	5.5 GB	8.9 GB free	470	Ollama	Run
Gemma 3 1B	1.0B	Q6_K	0.8 GB	0.14 GB	1.5 GB	12.9 GB free	583	Ollama	Run
Qwen3.5 0.8B	0.87B	Q6_K	0.7 GB	1.50 GB	2.8 GB	11.6 GB free	671	Ollama	Run
Qwen3 0.6B	0.6B	Q6_K	0.5 GB	3.50 GB	4.6 GB	9.8 GB free	972	Ollama	Run

Runs — tight

4 models · fits at 128K, drop context or quant to go longer

Model	Params	Quant	Weights	+KV 128K	Total	VRAM headroom	Tok/s	Runtime
Fara 7B	8.29B	Q6_K	6.3 GB	6.84 GB	13.8 GB	0.6 GB free	70	llama.cpp	Run
DeepSeek-R1-Distill-Qwen 7B	7.62B	Q6_K	5.8 GB	7.00 GB	13.4 GB	1.0 GB free	77	llama.cpp	Run
Qwen2.5-Coder 7B	7.62B	Q6_K	5.8 GB	7.00 GB	13.4 GB	1.0 GB free	77	llama.cpp	Run
Granite 4.1 3B	3.4B	Q6_K	2.6 GB	10.00 GB	13.2 GB	1.2 GB free	172	llama.cpp	Run

Won't fit in VRAM

55 models · some are possible with CPU offload

Model	Params	Quant	Weights	+KV 128K	Total	Over budget	Tok/s	Runtime
Qwen3.6 35B-A3B	35.9B MoE / 3.3B act	Q6_K	27.4 GB	2.50 GB	30.5 GB	+16.1 GB	~8.9	llama.cpp	Why
Ornith 1.5 35B-A3B New this week	35.9B MoE / 3.3B act	Q6_K	27.4 GB	2.50 GB	30.5 GB	+16.1 GB	~8.9	llama.cpp	Why
LLM-jp 4 33B Thinking New this week	33.2B	Q6_K	25.4 GB	16.00 GB	42.0 GB	+27.6 GB	~1.4	llama.cpp	Why
Qwen3 32B	32.8B	Q6_K	25.0 GB	32.00 GB	57.6 GB	+43.2 GB	~1.5	llama.cpp	Why
DeepSeek-R1-Distill-Qwen 32B	32.8B	Q6_K	25.0 GB	32.00 GB	57.6 GB	+43.2 GB	~1.5	llama.cpp	Why
Qwen2.5-Coder 32B	32.8B	Q6_K	25.0 GB	32.00 GB	57.6 GB	+43.2 GB	~1.5	llama.cpp	Why
Olmo 3.1 32B Instruct	32.2B	Q6_K	24.6 GB	4.75 GB	29.9 GB	+15.5 GB	~2.2	llama.cpp	Why
Nemotron 3.5 Lightning 30B-A3B New	31.6B MoE / 3.2B act	Q6_K	24.1 GB	0.75 GB	25.5 GB	+11.1 GB	~11	llama.cpp	Why
Gemma 4 31B	31.3B	Q6_K	23.9 GB	20.78 GB	45.3 GB	+30.9 GB	~1.5	llama.cpp	Why
GLM-4.7-Flash 30B-A3B	31.2B MoE / 3B act	Q6_K	23.8 GB	6.61 GB	31.0 GB	+16.6 GB	~8.4	llama.cpp	Why
Qwen3 30B-A3B	30.5B MoE / 3.3B act	Q6_K	23.3 GB	12.00 GB	35.9 GB	+21.5 GB	~6.0	llama.cpp	Why
Qwen3 Coder 30B-A3B	30.5B MoE / 3.3B act	Q6_K	23.3 GB	12.00 GB	35.9 GB	+21.5 GB	~6.0	llama.cpp	Why
Muse Glimmer 30B New	29.8B	Q6_K	22.8 GB	1.70 GB	25.1 GB	+10.7 GB	~3.1	llama.cpp	Why
Granite 4.1 30B	28.9B	Q6_K	22.1 GB	32.00 GB	54.7 GB	+40.3 GB	~1.6	llama.cpp	Why
Qwen3.8 27B New this week	27.8B	Q6_K	21.2 GB	8.00 GB	29.8 GB	+15.4 GB	~2.3	llama.cpp	Why
Qwen3.6 27B	27.8B	Q6_K	21.2 GB	8.00 GB	29.8 GB	+15.4 GB	~2.3	llama.cpp	Why
Gemma 3 27B	27.4B	Q6_K	20.9 GB	10.41 GB	31.9 GB	+17.5 GB	~2.0	llama.cpp	Why
Gemma 4 26B-A4B	26.5B MoE / 3.8B act	Q6_K	20.2 GB	5.20 GB	26.0 GB	+11.6 GB	~7.9	llama.cpp	Why
Devstral Small 2 24B	24B	Q6_K	18.3 GB	20.00 GB	38.9 GB	+24.5 GB	~2.0	llama.cpp	Why
Mistral Small 3.2 24B	23.6B	Q6_K	18.0 GB	20.00 GB	38.6 GB	+24.2 GB	~2.0	llama.cpp	Why
gpt-oss 20B	20.9B MoE / 3.6B act	MXFP4	10.8 GB	3.00 GB	14.4 GB	+0.0 GB	~89	llama.cpp	Why
Qwen3 14B	14.8B	Q6_K	11.3 GB	20.00 GB	31.9 GB	+17.5 GB	~3.2	llama.cpp	Why
DeepSeek-R1-Distill-Qwen 14B	14.8B	Q6_K	11.3 GB	24.00 GB	35.9 GB	+21.5 GB	~3.2	llama.cpp	Why
Qwen2.5-Coder 14B	14.8B	Q6_K	11.3 GB	24.00 GB	35.9 GB	+21.5 GB	~3.2	llama.cpp	Why
Phi-4 14B	14.7B	Q6_K	11.2 GB	3.13 GB	15.0 GB	+0.6 GB	~26	llama.cpp	Why
Ministral 3 14B	13.9B	Q6_K	10.6 GB	20.00 GB	31.2 GB	+16.8 GB	~3.4	llama.cpp	Why
Gemma 3 12B	12.2B	Q6_K	9.3 GB	8.31 GB	18.2 GB	+3.8 GB	~8.5	llama.cpp	Why
Mistral NeMo 12B	12.2B	Q6_K	9.3 GB	20.00 GB	29.9 GB	+15.5 GB	~3.9	llama.cpp	Why
Gemma 4 12B	12B	Q6_K	9.2 GB	8.31 GB	18.1 GB	+3.7 GB	~8.8	llama.cpp	Why
Ministral 3 8B	8.92B	Q6_K	6.8 GB	17.00 GB	24.4 GB	+10.0 GB	~5.3	llama.cpp	Why
Granite 4.1 8B	8.79B	Q6_K	6.7 GB	20.00 GB	27.3 GB	+12.9 GB	~5.4	llama.cpp	Why
Qwen3 8B	8.19B	Q6_K	6.3 GB	18.00 GB	24.9 GB	+10.5 GB	~5.8	llama.cpp	Why
Llama 3.1 8B Instruct	8.03B	Q6_K	6.1 GB	16.00 GB	22.7 GB	+8.3 GB	~5.9	llama.cpp	Why
Olmo 3 7B Instruct	7.3B	Q6_K	5.6 GB	9.50 GB	15.7 GB	+1.3 GB	~22	llama.cpp	Why
Ministral 3 3B	3.85B	Q6_K	2.9 GB	13.00 GB	16.5 GB	+2.1 GB	~16	llama.cpp	Why
Phi-4-mini 3.8B	3.84B	Q6_K	2.9 GB	16.00 GB	19.5 GB	+5.1 GB	~12	llama.cpp	Why
Llama 3.2 3B Instruct	3.21B	Q6_K	2.5 GB	14.00 GB	17.1 GB	+2.7 GB	~15	llama.cpp	Why
Kimi K3 2.8T-A104B New	2780B MoE / 104B act	Q6_K	2123.0 GB	3.38 GB	2127.0 GB	+2112.6 GB	~0.2	llama.cpp	Why
Qwen3.8 2.4T-A95B New	2446B MoE / 95B act	Q6_K	1868.0 GB	11.50 GB	1880.1 GB	+1865.7 GB	~0.2	llama.cpp	Why
DeepSeek V4 Pro 1.6T-A49B New	1650B MoE / 49B act	Q6_K	1260.1 GB	8.58 GB	1269.3 GB	+1254.9 GB	~0.4	llama.cpp	Why
Kimi K2.6 1T-A32B	1027B MoE / 32B act	Q6_K	784.3 GB	8.58 GB	793.5 GB	+779.1 GB	~0.6	llama.cpp	Why
GLM-5.2 744B-A40B	753B MoE / 40B act	Q6_K	575.1 GB	10.97 GB	586.6 GB	+572.2 GB	~0.5	llama.cpp	Why
DeepSeek-R1 671B	671B MoE / 37B act	Q6_K	512.4 GB	8.58 GB	521.6 GB	+507.2 GB	~0.5	llama.cpp	Why
Qwen3.5 397B-A17B	403B MoE / 17B act	Q6_K	307.8 GB	3.75 GB	312.1 GB	+297.7 GB	~1.1	llama.cpp	Why
Ornith 1.5 397B-A17B New this week	397B MoE / 17B act	Q6_K	303.2 GB	3.75 GB	307.5 GB	+293.1 GB	~1.1	llama.cpp	Why
DeepSeek V4 Flash 284B-A13B New	284B MoE / 13B act	Q6_K	216.9 GB	6.05 GB	223.5 GB	+209.1 GB	~1.5	llama.cpp	Why
Qwen3 235B-A22B	235B MoE / 22B act	Q6_K	179.5 GB	23.50 GB	203.6 GB	+189.2 GB	~0.8	llama.cpp	Why
Qwen3.5 122B-A10B	125B MoE / 10B act	Q6_K	95.5 GB	3.00 GB	99.1 GB	+84.7 GB	~2.0	llama.cpp	Why
Nemotron 3 Super 120B-A12B	124B MoE / 12B act	Q6_K	94.7 GB	1.00 GB	96.3 GB	+81.9 GB	~1.7	llama.cpp	Why
Ling 3.0 Flash 124B-A5B New	124B MoE / 5.1B act	Q6_K	94.7 GB	0.98 GB	96.3 GB	+81.9 GB	~4.1	llama.cpp	Why
Mistral Small 4 119B-A6B	119B MoE / 6.5B act	Q6_K	90.9 GB	2.81 GB	94.3 GB	+79.9 GB	~3.2	llama.cpp	Why
gpt-oss 120B	117B MoE / 5.1B act	MXFP4	60.5 GB	4.50 GB	65.6 GB	+51.2 GB	~6.2	llama.cpp	Why
Llama 4 Scout 109B-A17B	109B MoE / 17B act	Q6_K	83.2 GB	7.13 GB	91.0 GB	+76.6 GB	~1.2	llama.cpp	Why
Llama 3.3 70B Instruct	70.6B	Q6_K	53.9 GB	40.00 GB	94.5 GB	+80.1 GB	~0.7	llama.cpp	Why
DeepSeek-R1-Distill-Llama 70B	70.6B	Q6_K	53.9 GB	40.00 GB	94.5 GB	+80.1 GB	~0.7	llama.cpp	Why

Totals = quantised weights + f16 KV cache at 128K tokens + 0.6 GB runtime overhead, against 14.4 GB usable VRAM (16 GB less display and driver reserve). Tokens per second are estimated from 736 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.