Best AI Models for NVIDIA GeForce RTX 3080 Ti Laptop GPU (16 GB)

Runs 14B models well; 27–31B only just fits.

16 GB GDDR6512 GB/s47 TFLOPS FP16150 WAmpere 2022

16 GB GDDR6 at 16 Gbps (512 GB/s) on GA103 - fits ~13-14B Q4 models. Real performance depends on the chassis power limit.

What LLMs can the RTX 3080 Ti Laptop GPU run?

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 52.3 t/s	52.3 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 102 t/s	102 tok/s	Q4_K_M · 3.4 GB
3	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 110 t/s	110 tok/s	Q4_K_M · 13.1 GB
4	Phi 4Microsoft Q4_K_M · 12.5 GB · 35.0 t/s	35.0 tok/s	Q4_K_M · 12.5 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 40.4 t/s	40.4 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed	Coding Score	Quant · VRAM
1	GPT OSS 20BOpenAIHow to run → Q4_K_M · 13.1 GB · 110 t/s	110 tok/s		Q4_K_M · 13.1 GB
2	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 62.8 t/s	62.8 tok/s		Q4_K_M · 7.9 GB
3	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 52.3 t/s	52.3 tok/s	overall	Q4_K_M · 6.6 GB
4	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 40.4 t/s	40.4 tok/s		Q4_K_M · 9.0 GB
5	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 242 t/s	242 tok/s		Q4_K_M · 5.5 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 52.3 t/s	52.3 tok/s	Q4_K_M · 6.6 GB
2	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 110 t/s	110 tok/s	Q4_K_M · 13.1 GB
3	Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 60.3 t/s	60.3 tok/s	Q4_K_M · 7.6 GB
4	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 62.8 t/s	62.8 tok/s	Q4_K_M · 7.9 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 40.4 t/s	40.4 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 52.3 t/s	52.3 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 102 t/s	102 tok/s	Q4_K_M · 3.4 GB
3	Mistral Nemo Instruct 2407Mistral AI Q4_K_M · 11.0 GB · 41.2 t/s	41.2 tok/s	Q4_K_M · 11.0 GB
4	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 62.8 t/s	62.8 tok/s	Q4_K_M · 7.9 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 40.4 t/s	40.4 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed ↓	Quant · VRAM
1	GPT OSS 20BOpenAIHow to run → Q4_K_M · 13.1 GB · 110 t/s	110 tok/s	Q4_K_M · 13.1 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 102 t/s	102 tok/s	Q4_K_M · 3.4 GB
3	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 52.3 t/s	52.3 tok/s	Q4_K_M · 6.6 GB
4	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 40.4 t/s	40.4 tok/s	Q4_K_M · 9.0 GB
5	Phi 4Microsoft Q4_K_M · 12.5 GB · 35.0 t/s	35.0 tok/s	Q4_K_M · 12.5 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 52.3 t/s	52.3 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 102 t/s	102 tok/s	Q4_K_M · 3.4 GB
3	Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB · 41.4 t/s	41.4 tok/s	Q4_K_M · 10.9 GB
4	Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 117 t/s	117 tok/s	Q4_K_M · 5.0 GB
5	MiMo V2.6 Distill Qwen 9BXiaomi Q4_K_M · 6.5 GB · 53.6 t/s	53.6 tok/s	Q4_K_M · 6.5 GB

See all 309 models on the RTX 3080 Ti Laptop GPU →Best quant that fits · speeds estimated on this card

About the RTX 3080 Ti Laptop GPU

The RTX 3080 Ti Laptop GPU runs 14B models well. Ampere generation, released 2022.

GenerationAmperereleased 2022

RTX 3080 Ti Laptop GPU strengths and weaknesses

Strengths

Runs 35B MoE models: Qwen3.6 35B A3B at 119 tok/s in 15.7 GB
Low power draw: 150 W board power; a 300 W PSU is enough

Weaknesses

70B models don't fit: Llama 3.3 70B Instruct needs 51.3 GB at Q4 vs 16 GB here
No FP8 or NVFP4: Ampere predates both; use GGUF, AWQ or GPTQ builds

Similar GPUs

Cards people weigh against the RTX 3080 Ti Laptop GPU, each with the one reason it is worth a look.

About as fast, same 16 GBRX 7800 XTAMD · 16 GB · RDNA 3

same 16 GB$49958.9 tok/s

4 GB more for bigger modelsRX 7900 XTAMD · 20 GB · RDNA 3

▲ 4 GB$89975.5 tok/s

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

▲ 8 GB$99990.6 tok/s

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

▲ 8 GB91.6 tok/s

About as fast, same 16 GBRTX 5080 Laptop GPUNVIDIA · 16 GB · Blackwell

same 16 GB91.6 tok/s

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

▲ 8 GB$1,499rent $0.19/hr95.7 tok/s

RTX 3080 Ti Laptop GPU tokens per second by model size

Output speed depends on memory bandwidth (512 GB/s). Grey rows need more than 16 GB.

9BQwen3.5 9B · Q4_K_M · 6.6 GB
52.3tok/s
14BQwen3 14B · Q4_K_M · 11.9 GB
35.0tok/s
27–31BQwen3.8 27B · Q3_K_L · 15.4 GB tight · Q3_K_L
22.2tok/s
35B MoEQwen3.6 35B A3B · IQ3_S · 15.7 GB tight · IQ3_S
119tok/s
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 1073 models on the RTX 3080 Ti 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 3080 Ti Laptop GPU — ranked by Score, recency and Fit
Model	Quant	VRAM	Speed	Context	Fit
Huihui Qwen3 8B Abliterated v28.2BChatFunctions Q4_K_M·60.3 t/s	Q4_K_M	7.6 GB48%	60.3 t/s	41K	A84, Runs well
NVIDIA Nemotron Nano 12B v212.3BChatFunctions Q4_K_M·41.0 t/s	Q4_K_M	11.0 GB69%	41.0 t/s	—	A75, Runs well
InternVL2 2B2.2BVision Q4_K_M·227.9 t/s	Q4_K_M	3.3 GB20%	227.9 t/s	—	S100, Runs great
HunyuanOCR1.1BVision Q4_K_M·311.0 t/s	Q4_K_M	1.8 GB11%	311.0 t/s	131K	S100, Runs great
A.X 4.0 Light7.3BChatFunctions Q4_K_M·69.8 t/s	Q4_K_M	5.6 GB35%	69.8 t/s	16K	S86, Runs great
DeepSeek R1 Distill Qwen 14B14.8BChatReasoningFunctions Q4_K_M·34.8 t/s	Q4_K_M	12.4 GB77%	34.8 t/s	131K	A73, Runs well
Jina Ocr V13.4BVision Q4_K_M·309.6 t/s	Q4_K_M	3.3 GB21%	309.6 t/s	33K	S100, Runs great
Llamatron 8B V18.0BChat Q4_K_M·61.7 t/s	Q4_K_M	7.3 GB45%	61.7 t/s	131K	A84, Runs well
Qwen3.5 4B MiniFantasy MTP4.7BChatRoleplay FP16·34.0 t/s	FP16	10.0 GB62%	34.0 t/s	262K	A73, Runs well
MN VelvetCafe RP 12B12.2BChatRoleplay Q4_K_M·41.2 t/s	Q4_K_M	11.0 GB69%	41.2 t/s	131K	A75, Runs well
Kumru 2B2.4BChat Q4_K_M·180.9 t/s	Q4_K_M	2.2 GB14%	180.9 t/s	8K	S99, Runs great
Qwen3 4B4.0BChatFunctions Q4_K_M·114.8 t/s	Q4_K_M	4.2 GB26%	114.8 t/s	41K	S94, Runs great
Granite 4.1 8B8.8BChatFunctions Q4_K_M·56.3 t/s	Q4_K_M	8.3 GB52%	56.3 t/s	131K	A82, Runs well
Granite 4.0 350M352MChatFunctions Q4_K_M·583.9 t/s	Q4_K_M	1.0 GB6%	583.9 t/s	33K	S100, Runs great
Medgemma 1.5 4B IT4.3BVision Q4_K_M·117.2 t/s	Q4_K_M	5 GB31%	117.2 t/s	—	S94, Runs great

RTX 3080 Ti Laptop GPU specs, power and PSU

Specs

Architecture: Ampere
VRAM: 16 GB GDDR6
Memory bandwidth: 512.0 GB/s
FP16 (dense): 47.22 TFLOPS
CUDA cores: 7,424
Tensor cores: 232
Compute capability: 8.6
TDP: 150 W
Released: 2022-02-01

RTX 3080 Ti Laptop GPU FAQ

What is the largest model the RTX 3080 Ti Laptop GPU can run?

Gemma 4 26B A4B IT (25.8B) is the largest at 4-bit or better: at Q4_K_S it uses 15.5 GB of 16 GB, and runs at about 106 tok/s. At 3-bit, a bigger model fits too: Gemma 2 27B IT (27.2B) at IQ3_M, 15.0 GB.

Can the RTX 3080 Ti Laptop GPU run Qwen3.5 9B?

Yes. Qwen3.5 9B fits at Q4_K_M, using 6.6 GB of 16 GB, and it is the best model that runs well on this card.

Can the RTX 3080 Ti Laptop GPU run 70B models?

No. Llama 3.3 70B Instruct needs 51.3 GB at Q4, more than the 16 GB on this card.

How many tokens per second does the RTX 3080 Ti Laptop GPU give?

About 52.3 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 3.7 s on a 4K-token prompt.

What power supply does the RTX 3080 Ti Laptop GPU need?

Plan a 300 W PSU (2× the 150 W TDP).

Is 16 GB enough for coding and agents?

Yes for coding: GPT OSS 20B, the best of the 2 coding models that fit, runs at about 110 tok/s. For agents, not yet: no agent-scored model fits in less than 96 GB.

Is renting cheaper than buying an RTX 3080 Ti Laptop GPU?

An RTX 3090 (24 GB) rents from $0.19/hr. With regular daily use, owning pays off.

Best coding LLMs 16 GB VRAM 24 GB VRAM GPUs with 16 GB or more RTX 5090 RTX 3090 Ti