Best AI Models for NVIDIA GeForce RTX 2060 SUPER (8 GB)

Runs 7–9B models well; 14B doesn't fit in 8 GB.

8 GB GDDR6448 GB/s29 TFLOPS FP16175 WTuring 2019

Turing 8 GB: Tensor Cores and flash-attention (cc 7.5), 448 GB/s; 8 GB fits ~7-8B models at Q4 with room for context.

What LLMs can the RTX 2060 SUPER 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	Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 47.7 t/s	47.7 tok/s	Q4_K_M · 7.3 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	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	Reasoning Score	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	Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 103 t/s	103 tok/s		Q4_K_M · 5.0 GB
3	Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 58.4 t/s	58.4 tok/s		Q4_K_M · 5.8 GB
4	Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 47.7 t/s	47.7 tok/s	overall	Q4_K_M · 7.3 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 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 89.3 t/s	89.3 tok/s	Q4_K_M · 3.4 GB
2	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	Q4_K_M · 6.6 GB
3	Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 54.7 t/s	54.7 tok/s	Q4_K_M · 5.6 GB
4	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 221 t/s	221 tok/s	Q4_K_M · 5.5 GB
5	Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 98.4 t/s	98.4 tok/s	Q4_K_M · 4.3 GB

#	Model	Speed ↓	Quant · VRAM
1	Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 89.3 t/s	89.3 tok/s	Q4_K_M · 3.4 GB
2	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 221 t/s	221 tok/s	Q4_K_M · 5.5 GB
3	Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 54.7 t/s	54.7 tok/s	Q4_K_M · 5.6 GB
4	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
5	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 45.8 t/s	45.8 tok/s	Q4_K_M · 6.6 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 4B ITGoogle Q4_K_M · 5.0 GB · 103 t/s	103 tok/s	Q4_K_M · 5.0 GB
4	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
5	LFM3 Omni 2BLiquid AI Q4_K_M · 2.4 GB · 171 t/s	171 tok/s	Q4_K_M · 2.4 GB

See all 218 models on the RTX 2060 SUPER →Best quant that fits · speeds estimated on this card

About the RTX 2060 SUPER

The RTX 2060 SUPER is a solid mid-range card in the 8 GB class: it runs 7–9B models well. It is more efficient per watt than most 8 GB cards, and the best speed per dollar of the cards compared at ≈$200 used. Turing generation, released 2019.

Speed in 8 GB#3448 GB/s

Per watt#30.26 tok/s per W on Qwen3.5 9B (9B params)

Per dollar#122.9 tok/s per $100 on Qwen3.5 9B (9B params)

GenerationTuringreleased 2019

RTX 2060 SUPER strengths and weaknesses

Strengths

Runs 7–9B models: Qwen3.5 9B at 45.8 tok/s in 6.6 GB

Weaknesses

14B models don't fit: Qwen3 14B needs 11.9 GB at Q4 vs 8 GB here
Little room for context: Qwen3.5 9B uses 6.6 of 8 GB, 1.4 GB left
Slow prompt reading: A 4K-token prompt on Qwen3.5 9B waits 6.1 s for the first token
No FP8 or NVFP4: Turing predates both; use GGUF, AWQ or GPTQ builds

Speed per dollar and per watt

NewUsed

On Qwen3.5 9B (9B params) at Q4_K_M. New prices are compared with new, used with used. The last two columns are the speed you get per $100 of price and per 100 W of board power; higher is better. The RTX 2060 SUPER has no new price, so the New view shows it at its MSRP.

Card	New price	tok/s	tok/s per $100	tok/s per 100 W
RTX 2060 SUPER8 GB	about $399	45.8	11.5	26.2
RTX 50608 GBBest new value	about $460	45.8	10.0	31.6
RTX 507012 GB	about $840	68.7	8.2	27.5
RTX 40608 GB	about $520	27.8	5.3	24.2

Card	Used price	tok/s	tok/s per $100	tok/s per 100 W
RTX 2060 SUPER8 GB	about $200	45.8	22.9	26.2
RTX 3060 12GB12 GB	about $329	36.8	11.2	21.6
RTX 50608 GBBest used value	about $430	45.8	10.7	31.6
RTX 507012 GB	about $736	68.7	9.3	27.5
RTX 407012 GB	about $575	51.5	9.0	25.8
RTX 4070 SUPER12 GB	about $675	51.5	7.6	23.4
RTX 4060 Ti 8GB8 GB	about $400	29.4	7.4	18.4
RTX 4070 Ti12 GB	about $722	51.5	7.1	18.1

Similar GPUs

Cards people weigh against the RTX 2060 SUPER, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.

4 GB more and 12% fasterRTX 4070NVIDIA · 12 GB · Ada Lovelace

▲ 12% speed▲ 4 GB$599rent $0.12/hr

4 GB more and 50% fasterRTX 5070NVIDIA · 12 GB · Blackwell

▲ 50% speed▲ 4 GB$840rent $0.15/hr

Same 8 GB, new with warrantyRTX 5060NVIDIA · 8 GB · Blackwell

same speedsame 8 GB$460

4 GB more, but slowerRTX 3060 12GBNVIDIA · 12 GB · Ampere

▼ 20% speed▲ 4 GB$329rent $0.06/hr

12% slower, same 8 GBA580Intel · 8 GB · Alchemist

▼ 12% speedsame 8 GB$179

8 GB more and 60% fasterRTX 4080NVIDIA · 16 GB · Ada Lovelace

▲ 60% speed▲ 8 GB$1,199rent $0.24/hr

RTX 2060 SUPER tokens per second by model size

Output speed depends on memory bandwidth (448 GB/s). Grey rows need more than 8 GB.

9BQwen3.5 9B · Q4_K_M · 6.6 GB
45.8tok/s
14BQwen3 14B · not at 4-bit
needs 11.9 GB
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 842 models on the RTX 2060 SUPER

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 2060 SUPER — ranked by Score, recency and Fit
Model	Quant	VRAM	Speed	Context	Fit
Lucie 7B6.7BChat Q4_K_M·63.4 t/s	Q4_K_M	6.5 GB81%	63.4 t/s	32K	A83, Runs well
L3 8B Stheno V3.28.0BChat Q4_K_M·54.0 t/s	Q4_K_M	6.2 GB78%	54.0 t/s	8K	A81, Runs well
Phi 4 Mini Reasoning3.8BChatMathCodeReasoningFunctions Q4_K_M·101.5 t/s	Q4_K_M	4.8 GB59%	101.5 t/s	131K	S92, Runs great
Mamba 2.8B HF2.8BChat Q4_K_M·159.1 t/s	Q4_K_M	3.7 GB47%	159.1 t/s	—	S97, Runs great
Nidum Gemma 2B Uncensored2.5BChat Q4_K_M·158.3 t/s	Q4_K_M	1.9 GB24%	158.3 t/s	8K	S97, Runs great
Qwen Base Invoicev1.01 1.5B1.5BChat Q4_K_M·227.5 t/s	Q4_K_M	1.7 GB21%	227.5 t/s	33K	S100, Runs great
SmolLM2 1.7B Instruct1.7BChat Q4_K_M·168.3 t/s	Q4_K_M	2.9 GB37%	168.3 t/s	8K	S98, Runs great
MobileLLaMA 1.4B Chat1.4BChat Q4_K_M·189.1 t/s	Q4_K_M	1.5 GB19%	189.1 t/s	2K	S99, Runs great
Mamba 1.4B HF1.4BChat Q4_K_M·320.0 t/s	Q4_K_M	2.5 GB31%	320.0 t/s	—	S100, Runs great
MiniCPM 2B Sft BF162BChat Q4_K_M·129.4 t/s	Q4_K_M	3 GB38%	129.4 t/s	4K	S95, Runs great
Opt 350M350MChat FP16·378.2 t/s	FP16	0.8 GB10%	378.2 t/s	2K	S100, Runs great
TinyStories 1M1MChat BF16·29120.0 t/s	BF16	0.0 GB0%	29120.0 t/s	2K	S100, Runs great
Gemma 4 12B Agentic Fable5 Composer2.5 v2 3.5x Tau212.0BChatFunctionsReasoning Q3_K_M·42.3 t/s	Q3_K_M	7.7 GB96%	42.3 t/s	262K	B51, Decent
Qwen2 VL 7B Instruct8.3BVision Q4_K_M·54.0 t/s	Q4_K_M	6.2 GB78%	54.0 t/s	33K	A81, Runs well
Gpt2 Medium380MChat Q4_K_M·1164.8 t/s	Q4_K_M	0.3 GB3%	1164.8 t/s	1K	S100, Runs great

RTX 2060 SUPER specs, power and PSU

Specs

Architecture: Turing
VRAM: 8 GB GDDR6
Memory bandwidth: 448.0 GB/s
FP16 (dense): 28.72 TFLOPS
CUDA cores: 2,176
Tensor cores: 272
Compute capability: 7.5
TDP: 175 W
Released: 2019-07-09
MSRP: $399

RTX 2060 SUPER FAQ

Is the RTX 2060 SUPER still worth it in 2026?

At ≈$200 used you get 22.9 tok/s per $100 on Qwen3.5 9B, which ranks 1st of the 8 cards compared here; it is also the 3rd fastest out of 19 cards with 8 GB. It runs 7–9B models well; 14B doesn't fit in 8 GB.

What is the largest model the RTX 2060 SUPER can run?

Qwen3.5 9B (9.7B) is the largest at 4-bit or better: at Q4_K_M it uses 6.6 GB of 8 GB, and runs at about 45.8 tok/s.

Can the RTX 2060 SUPER run 14B models?

No. Qwen3 14B needs 11.9 GB at Q4, more than the 8 GB on this card.

How many tokens per second does the RTX 2060 SUPER give?

About 45.8 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 6.1 s on a 4K-token prompt.

What power supply does the RTX 2060 SUPER need?

Plan a 350 W PSU (2× the 175 W TDP).

Is renting cheaper than buying an RTX 2060 SUPER?

An RTX 3090 (24 GB) rents from $0.18/hr. Renting costs as much as buying after ≈1,100 hours (≈0.8 years at 4 h a day).

Best coding LLMs 8 GB VRAM 12 GB VRAM GPUs with 8 GB or more RTX 5080 RTX 3080 Ti