NVIDIA · Ada Lovelace · 12 GB VRAM tier

Best AI Models for NVIDIA GeForce RTX 4080 Laptop GPU (12 GB)

Runs 7–9B models well; 14B only just fits.

12 GB GDDR6432 GB/s68 TFLOPS FP16150 WAda Lovelace 2023

Laptop GPU is AD104 with 12 GB (the desktop 4080 has 16 GB). 12 GB fits ~13-14B Q4 with moderate context; speed depends on the chassis power limit.

What LLMs can the RTX 4080 Laptop GPU run?

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.2 t/s	44.2 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 86.1 t/s	86.1 tok/s	Q4_K_M · 3.4 GB
3	Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB · 34.9 t/s	34.9 tok/s	Q4_K_M · 10.9 GB
4	Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 46.0 t/s	46.0 tok/s	Q4_K_M · 7.3 GB
5	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 215 t/s	215 tok/s	Q4_K_M · 5.5 GB

#	Model	Speed	Coding Score	Quant · VRAM
1	Llama 3.1 8B InstructMetaHow to run → Q4_K_M · 7.9 GB · 53.0 t/s	53.0 tok/s		Q4_K_M · 7.9 GB
2	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 44.2 t/s	44.2 tok/s	overall	Q4_K_M · 6.6 GB
3	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 86.1 t/s	86.1 tok/s	overall	Q4_K_M · 3.4 GB
4	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.1 t/s	34.1 tok/s		Q4_K_M · 9.0 GB
5	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 215 t/s	215 tok/s		Q4_K_M · 5.5 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.2 t/s	44.2 tok/s	Q4_K_M · 6.6 GB
2	Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 50.9 t/s	50.9 tok/s	Q4_K_M · 7.6 GB
3	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 53.0 t/s	53.0 tok/s	Q4_K_M · 7.9 GB
4	Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 98.9 t/s	98.9 tok/s	Q4_K_M · 5.0 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.1 t/s	34.1 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.2 t/s	44.2 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 86.1 t/s	86.1 tok/s	Q4_K_M · 3.4 GB
3	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 53.0 t/s	53.0 tok/s	Q4_K_M · 7.9 GB
4	Mistral Nemo Instruct 2407Mistral AI Q4_K_M · 11.0 GB · 34.8 t/s	34.8 tok/s	Q4_K_M · 11.0 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.1 t/s	34.1 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed ↓	Quant · VRAM
1	Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 86.1 t/s	86.1 tok/s	Q4_K_M · 3.4 GB
2	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 215 t/s	215 tok/s	Q4_K_M · 5.5 GB
3	Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 50.9 t/s	50.9 tok/s	Q4_K_M · 7.6 GB
4	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 44.2 t/s	44.2 tok/s	Q4_K_M · 6.6 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.1 t/s	34.1 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.2 t/s	44.2 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 86.1 t/s	86.1 tok/s	Q4_K_M · 3.4 GB
3	Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB · 34.9 t/s	34.9 tok/s	Q4_K_M · 10.9 GB
4	Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 98.9 t/s	98.9 tok/s	Q4_K_M · 5.0 GB
5	MiMo V2.6 Distill Qwen 9BXiaomi Q4_K_M · 6.5 GB · 45.2 t/s	45.2 tok/s	Q4_K_M · 6.5 GB

See all 278 models on the RTX 4080 Laptop GPU →Best quant that fits · speeds estimated on this card

About the RTX 4080 Laptop GPU

The RTX 4080 Laptop GPU runs 7–9B models well. Ada Lovelace generation, released 2023.

GenerationAda Lovelacereleased 2023

RTX 4080 Laptop GPU strengths and weaknesses

Strengths

Runs 14B models: Qwen3 14B at 29.6 tok/s in 11.9 GB
Low power draw: 150 W board power; a 300 W PSU is enough

Weaknesses

27–31B models don't fit: Qwen3.8 27B needs 17.9 GB at Q4 vs 12 GB here
Little room for context: Qwen3 14B uses 11.9 of 12 GB, 0.1 GB left

Similar GPUs

Cards people weigh against the RTX 4080 Laptop GPU, each with the one reason it is worth a look.

4 GB more for bigger modelsA770 16GBIntel · 16 GB · Alchemist

▲ 4 GB$34944.0 tok/s

12 GB more for bigger modelsRX 7900 XTXAMD · 24 GB · RDNA 3

▲ 12 GB$99990.6 tok/s

12 GB more for bigger modelsRTX 5090 Laptop GPUNVIDIA · 24 GB · Blackwell

▲ 12 GB91.6 tok/s

About as fast, same 12 GBRTX 3080 TiNVIDIA · 12 GB · Ampere

same 12 GB$1,199rent $0.13/hr93.2 tok/s

About as fast, same 12 GBRTX 3080 12GBNVIDIA · 12 GB · Ampere

same 12 GB$79993.2 tok/s

12 GB more for bigger modelsRTX 3090NVIDIA · 24 GB · Ampere

▲ 12 GB$1,499rent $0.18/hr95.7 tok/s

RTX 4080 Laptop GPU tokens per second by model size

Output speed depends on memory bandwidth (432 GB/s). Grey rows need more than 12 GB.

9BQwen3.5 9B · Q4_K_M · 6.6 GB
44.2tok/s
14BQwen3 14B · Q4_K_M · 11.9 GB tight · Q4_K_M
29.6tok/s
27–31BQwen3.8 27B · not at 4-bit
needs 17.9 GB
35B MoEQwen3.6 35B A3B · not at 4-bit
needs 22.0 GB
70BLlama 3.3 70B Instruct · not at 4-bit
needs 51.3 GB
120B MoEGPT OSS 120B · not at 4-bit
needs 70.8 GB

Estimated speeds: Q4_K_M, 4K context, one user. How we estimate

All 977 models on the RTX 4080 Laptop GPU

Featured only

Best quant that fits, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with NVIDIA GeForce RTX 4080 Laptop GPU — ranked by Score, recency and Fit
Model	Quant	VRAM	Speed	Context	Fit
Qwen2.5 Omni 7B10.7BChat Q4_K_M·39.7 t/s	Q4_K_M	9.9 GB82%	39.7 t/s	—	A72, Runs well
Bloom 560M559MChat Q4_K_M·758.9 t/s	Q4_K_M	1.6 GB13%	758.9 t/s	—	S100, Runs great
GPT Neo 125M150MChat BF16·850.9 t/s	BF16	0.3 GB3%	850.9 t/s	2K	S100, Runs great
SmolLM2 135M Instruct135MChat Q4_K_M·653.0 t/s	Q4_K_M	0.6 GB5%	653.0 t/s	8K	S100, Runs great
Ornith 1.0 35B35.1BChatFunctions IQ2_S·149.4 t/s	IQ2_S	11.4 GB95%	149.4 t/s	262K	B62, Decent
NVIDIA Nemotron Nano 9B v2 Japanese8.9BChat Q4_K_M·46.5 t/s	Q4_K_M	6.0 GB50%	46.5 t/s	131K	A78, Runs well
Qwen3 Code Reasoning 4B4BChatCodeReasoning Q4_K_M·97.2 t/s	Q4_K_M	4.2 GB35%	97.2 t/s	262K	S91, Runs great
Clef27.4BVisionFunctions IQ2_M·28.1 t/s	IQ2_M	10.4 GB87%	28.1 t/s	262K	B60, Decent
Yi 1.5 6B Chat6.1BChat Q4_K_M·69.0 t/s	Q4_K_M	4.2 GB35%	69.0 t/s	4K	S86, Runs great
SILMA 9B Instruct v1.09.2BChat Q4_K_M·43.5 t/s	Q4_K_M	7.7 GB64%	43.5 t/s	8K	A77, Runs well
Granite 3.1 3B A800m Instruct3.3BChatFunctions Q4_K_M·246.5 t/s	Q4_K_M	3.4 GB28%	246.5 t/s	131K	S100, Runs great
Lucie 7B6.7BChat Q4_K_M·61.2 t/s	Q4_K_M	6.5 GB54%	61.2 t/s	32K	A84, Runs well
Qwen Base Invoicev1.01 1.5B1.5BChat Q4_K_M·219.4 t/s	Q4_K_M	1.7 GB14%	219.4 t/s	33K	S100, Runs great
MobileLLaMA 1.4B Chat1.4BChat Q4_K_M·182.3 t/s	Q4_K_M	1.5 GB13%	182.3 t/s	2K	S99, Runs great
Nidum Gemma 2B Uncensored2.5BChat Q4_K_M·152.6 t/s	Q4_K_M	1.9 GB16%	152.6 t/s	8K	S97, Runs great

RTX 4080 Laptop GPU specs, power and PSU

Specs

Architecture: Ada Lovelace
VRAM: 12 GB GDDR6
Memory bandwidth: 432.0 GB/s
FP16 (dense): 67.71 TFLOPS
CUDA cores: 7,424
Tensor cores: 232
Compute capability: 8.9
TDP: 150 W
Released: 2023-02-08

RTX 4080 Laptop GPU FAQ

What is the largest model the RTX 4080 Laptop GPU can run?

GPT OSS 20B (20.9B) is the largest at 4-bit or better: at IQ4_XS it uses 11.8 GB of 12 GB, and runs at about 104 tok/s.

Can the RTX 4080 Laptop GPU run Qwen3.5 9B?

Yes. Qwen3.5 9B fits at Q4_K_M, using 6.6 GB of 12 GB, and it is the best model that runs well on this card.

Can the RTX 4080 Laptop GPU run 27–31B models?

No. Qwen3.8 27B needs 17.9 GB at Q4, more than the 12 GB on this card.

How many tokens per second does the RTX 4080 Laptop GPU give?

About 44.2 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 2.6 s on a 4K-token prompt.

What power supply does the RTX 4080 Laptop GPU need?

Plan a 300 W PSU (2× the 150 W TDP).

Is 12 GB enough for coding and agents?

Yes for coding: Llama 3.1 8B Instruct, the only coding-scored model that fits, runs at about 53 tok/s. For agents, not yet: no agent-scored model fits in less than 96 GB.

Is renting cheaper than buying an RTX 4080 Laptop GPU?

An RTX 5080 (16 GB) rents from $0.23/hr. With regular daily use, owning pays off.

Best coding LLMs 12 GB VRAM 16 GB VRAM GPUs with 12 GB or more RTX 3090 Ti RTX 4090