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

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

16 GB GDDR6448 GB/s42 TFLOPS FP16150 WAmpere 2021

16 GB variant of the laptop RTX 3080 (not all laptops with this GPU have 16 GB - check the spec sheet). 16 GB fits ~13-14B Q4 models; speed depends on the chassis power limit.

What LLMs can the RTX 3080 Laptop GPU 16GB run?

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 89.3 t/s	89.3 tok/s	Q4_K_M · 3.4 GB
3	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 97.9 t/s	97.9 tok/s	Q4_K_M · 13.1 GB
4	Phi 4Microsoft Q4_K_M · 12.5 GB · 30.6 t/s	30.6 tok/s	Q4_K_M · 12.5 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 35.4 t/s	35.4 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 · 97.9 t/s	97.9 tok/s		Q4_K_M · 13.1 GB
2	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 54.9 t/s	54.9 tok/s		Q4_K_M · 7.9 GB
3	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	overall	Q4_K_M · 6.6 GB
4	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 35.4 t/s	35.4 tok/s		Q4_K_M · 9.0 GB
5	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 221 t/s	221 tok/s		Q4_K_M · 5.5 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	Q4_K_M · 6.6 GB
2	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 97.9 t/s	97.9 tok/s	Q4_K_M · 13.1 GB
3	Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 52.8 t/s	52.8 tok/s	Q4_K_M · 7.6 GB
4	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 54.9 t/s	54.9 tok/s	Q4_K_M · 7.9 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 35.4 t/s	35.4 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 89.3 t/s	89.3 tok/s	Q4_K_M · 3.4 GB
3	Mistral Nemo Instruct 2407Mistral AI Q4_K_M · 11.0 GB · 36.1 t/s	36.1 tok/s	Q4_K_M · 11.0 GB
4	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 54.9 t/s	54.9 tok/s	Q4_K_M · 7.9 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 35.4 t/s	35.4 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed ↓	Quant · VRAM
1	GPT OSS 20BOpenAIHow to run → Q4_K_M · 13.1 GB · 97.9 t/s	97.9 tok/s	Q4_K_M · 13.1 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 89.3 t/s	89.3 tok/s	Q4_K_M · 3.4 GB
3	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	Q4_K_M · 6.6 GB
4	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 35.4 t/s	35.4 tok/s	Q4_K_M · 9.0 GB
5	Phi 4Microsoft Q4_K_M · 12.5 GB · 30.6 t/s	30.6 tok/s	Q4_K_M · 12.5 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 89.3 t/s	89.3 tok/s	Q4_K_M · 3.4 GB
3	Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB · 36.2 t/s	36.2 tok/s	Q4_K_M · 10.9 GB
4	Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 103 t/s	103 tok/s	Q4_K_M · 5.0 GB
5	MiMo V2.6 Distill Qwen 9BXiaomi Q4_K_M · 6.5 GB · 46.9 t/s	46.9 tok/s	Q4_K_M · 6.5 GB

See all 309 models on the RTX 3080 Laptop GPU 16GB →Best quant that fits · speeds estimated on this card

About the RTX 3080 Laptop GPU 16GB

The RTX 3080 Laptop GPU 16GB runs 14B models well. Ampere generation, released 2021.

GenerationAmperereleased 2021

RTX 3080 Laptop GPU 16GB strengths and weaknesses

Strengths

Runs 35B MoE models: Qwen3.6 35B A3B at 108 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 Laptop GPU 16GB, each with the one reason it is worth a look.

About as fast, same 16 GBA770 16GBIntel · 16 GB · Alchemist

same 16 GB$34944.0 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 $0.18/hr95.7 tok/s

RTX 3080 Laptop GPU 16GB tokens per second by model size

Output speed depends on memory bandwidth (448 GB/s). Grey rows need more than 16 GB.

9BQwen3.5 9B · Q4_K_M · 6.6 GB
45.8tok/s
14BQwen3 14B · Q4_K_M · 11.9 GB
30.7tok/s
27–31BQwen3.8 27B · Q3_K_L · 15.4 GB tight · Q3_K_L
19.4tok/s
35B MoEQwen3.6 35B A3B · IQ3_S · 15.7 GB tight · IQ3_S
108tok/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 Laptop GPU 16GB

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 Laptop GPU 16GB — ranked by Score, recency and Fit
Model	Quant	VRAM	Speed	Context	Fit
Granite Docling 258M258MVisionChatCodeMath Q4_K_M·582.4 t/s	Q4_K_M	0.6 GB4%	582.4 t/s	8K	S100, Runs great
Gemma 2 9B IT9.2BChat Q4_K_M·47.7 t/s	Q4_K_M	7.3 GB45%	47.7 t/s	8K	A79, Runs well
LFM2.5 8B A1B Base8.5BChat Q4_K_M·197.4 t/s	Q4_K_M	5.6 GB35%	197.4 t/s	128K	S100, Runs great
Zamba2 1.2B Instruct1.2BChat Q4_K_M·174.4 t/s	Q4_K_M	2.3 GB14%	174.4 t/s	4K	S98, Runs great
Tiny Dummy Qwen21MChat Q4_K_M·970.7 t/s	Q4_K_M	0.5 GB3%	970.7 t/s	33K	S100, Runs great
Qwen2.5 VL 3B Instruct3.8BVision Q4_K_M·110.7 t/s	Q4_K_M	3.2 GB20%	110.7 t/s	128K	S93, Runs great
DeepSeek v2 Lite Chat15.7BChat Q4_K_M·135.0 t/s	Q4_K_M	10.2 GB64%	135.0 t/s	164K	S96, Runs great
Qwen3 1.7B1.7BChat Q4_K_M·260.0 t/s	Q4_K_M	2.8 GB17%	260.0 t/s	—	S100, Runs great
Param 1 2.9B Instruct2.9BChat BF16·46.3 t/s	BF16	7.1 GB44%	46.3 t/s	8K	A78, Runs well
Hy MT2 30B A3B30.1BTranslationFunctions Q3_K_M·116.6 t/s	Q3_K_M	15.8 GB99%	116.6 t/s	262K	C44, Usable
Datarus R1 14B Preview14.8BChatReasoning Q4_K_M·30.5 t/s	Q4_K_M	12.4 GB77%	30.5 t/s	131K	A71, Runs well
Llama 3.2 Korean Bllossom 3B3.2BChat Q4_K_M·118.4 t/s	Q4_K_M	4.1 GB26%	118.4 t/s	131K	S95, Runs great
Qwen2.5 3B Instruct3.1BChatFunctions Q4_K_M·130.6 t/s	Q4_K_M	2.8 GB17%	130.6 t/s	33K	S95, Runs great
Holo4 35B A3B35.1BVisionFunctions Q3_K_S·121.8 t/s	Q3_K_S	15.8 GB99%	121.8 t/s	262K	C44, Usable
OlmOCR 2 7B 10258.3BVision Q4_K_M·54.0 t/s	Q4_K_M	6.2 GB39%	54.0 t/s	128K	A81, Runs well

RTX 3080 Laptop GPU 16GB specs, power and PSU

Specs

Architecture: Ampere
VRAM: 16 GB GDDR6
Memory bandwidth: 448.0 GB/s
FP16 (dense): 42.02 TFLOPS
CUDA cores: 6,144
Tensor cores: 192
Compute capability: 8.6
TDP: 150 W
Released: 2021-01-26

RTX 3080 Laptop GPU 16GB FAQ

What is the largest model the RTX 3080 Laptop GPU 16GB 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 95.1 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 Laptop GPU 16GB 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 Laptop GPU 16GB 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 Laptop GPU 16GB give?

About 45.8 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 4.2 s on a 4K-token prompt.

What power supply does the RTX 3080 Laptop GPU 16GB 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 98 tok/s. For agents, not yet: no agent-scored model fits in less than 96 GB.

Is renting cheaper than buying an RTX 3080 Laptop GPU 16GB?

An RTX 3090 (24 GB) rents from $0.18/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