NVIDIA · Ada Lovelace · 8 GB VRAM tier
Best AI Models for NVIDIA GeForce RTX 4060 Laptop GPU (8 GB)
Runs 7–9B models well; 14B doesn't fit in 8 GB.
8 GB GDDR6256 GB/s29 TFLOPS FP16115 WAda Lovelace 2023
8 GB on a 128-bit bus (256 GB/s): the practical ceiling is ~7-8B Q4 models. Speed varies with the chassis power limit.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 26.2 t/s | 26.2 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 51.0 t/s | 51.0 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 27.3 t/s | 27.3 tok/s | Q4_K_M · 7.3 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 58.6 t/s | 58.6 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 144 t/s | 144 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 · 26.2 t/s | 26.2 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 58.6 t/s | 58.6 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 33.3 t/s | 33.3 tok/s | Q4_K_M · 5.8 GB | |
| 4 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 27.3 t/s | 27.3 tok/s | overall | Q4_K_M · 7.3 GB |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 5.5 GB |
| # | Model | Speed | Long context Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 51.0 t/s | 51.0 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 26.2 t/s | 26.2 tok/s | Q4_K_M · 6.6 GB | |
| 3 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 5.5 GB | |
| 4 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 31.3 t/s | 31.3 tok/s | Q4_K_M · 5.6 GB | |
| 5 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 56.2 t/s | 56.2 tok/s | Q4_K_M · 4.3 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 51.0 t/s | 51.0 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 5.5 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 31.3 t/s | 31.3 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Q4_K_M · 6.5 GB · 26.8 t/s | 26.8 tok/s | Q4_K_M · 6.5 GB | |
| 5 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 26.2 t/s | 26.2 tok/s | Q4_K_M · 6.6 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 26.2 t/s | 26.2 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 51.0 t/s | 51.0 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 58.6 t/s | 58.6 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Q4_K_M · 6.5 GB · 26.8 t/s | 26.8 tok/s | Q4_K_M · 6.5 GB | |
| 5 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 130 t/s | 130 tok/s | Q4_K_M · 1.6 GB |
See all 218 models on the RTX 4060 Laptop GPU →Best quant that fits · speeds estimated on this card
The RTX 4060 Laptop GPU runs 7–9B models well. Ada Lovelace generation, released 2023.
GenerationAda Lovelacereleased 2023
RTX 4060 Laptop GPU strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 26.2 tok/s in 6.6 GB
- Low power draw: 115 W board power; a 250 W PSU is enough
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 6.0 s for the first token
Cards people weigh against the RTX 4060 Laptop GPU, each with the one reason it is worth a look.
About as fast, same 8 GBRTX 5050NVIDIA · 8 GB · Blackwell
same 8 GBabout $41032.7 tok/s
8 GB more for bigger modelsRTX 4080NVIDIA · 16 GB · Ada Lovelace▲ 8 GBabout $1,199rent $0.27/hr73.3 tok/s
8 GB more for bigger modelsRTX 4080 SUPERNVIDIA · 16 GB · Ada Lovelace▲ 8 GBabout $999rent $0.22/hr75.2 tok/s
2 GB more for bigger modelsRTX 3080NVIDIA · 10 GB · Ampere▲ 2 GBabout $699rent $0.11/hr77.7 tok/s
8 GB more for bigger modelsRTX 5080 Laptop GPUNVIDIA · 16 GB · Blackwell▲ 8 GB91.6 tok/s
Best value near the RTX 4060 Laptop GPURTX 5070 TiNVIDIA · 16 GB · Blackwell▲ 8 GBabout $1,170rent $0.19/hr91.6 tok/s
Output speed depends on memory bandwidth (256 GB/s). Grey rows need more than 8 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB26.2tok/s
- 14BQwen3 14B · not at 4-bitneeds 11.9 GB
- 27–31BQwen3.8 27B · not at 4-bitneeds 17.9 GB
- 35B MoEQwen3.6 35B A3B · not at 4-bitneeds 22.0 GB
- 70BLlama 3.3 70B Instruct · not at 4-bitneeds 51.3 GB
- 120B MoEGPT OSS 120B · not at 4-bitneeds 70.8 GB
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
All 842 models on the RTX 4060 Laptop GPU
Featured onlyBest quant that fits, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
Gemma 2 9BChat | Q3_K_M | 7.6 GB | 33.5 t/s | — | B49, Decent | |
Qwen 14BChat | IQ3_S | 7.9 GB | 25.1 t/s | 8K | C36, Usable | |
Mistral Nemo Instruct 2407ChatFunctions | IQ2_M | 7.8 GB | 34.3 t/s | 131K | B46, Decent | |
Phi 3 Medium 4k InstructChatCode | Q3_K_M | 8.0 GB | 22.1 t/s | 4K | C33, Usable | |
| IQ2_M | 7.8 GB | 34.3 t/s | 131K | B46, Decent | ||
Qwen3 14B BaseChat | IQ2_M | 8.0 GB | 29.6 t/s | 33K | C39, Usable | |
Qwen 14B ChatChat | IQ3_S | 7.9 GB | 25.1 t/s | 8K | C36, Usable | |
DeepSeek v2 LiteChat | Q2_K | 7.5 GB | 110.5 t/s | 164K | B62, Decent | |
| IQ2_S | 7.8 GB | 151.8 t/s | 131K | C44, Usable | ||
Qwen2.5 14B Instruct 1MChatFunctions | IQ2_XS | 8.0 GB | 32.4 t/s | 1010K | C42, Usable | |
Qwen2.5 14BChatFunctions | IQ2_XS | 8.0 GB | 32.4 t/s | 131K | C42, Usable | |
Phi 3.5 Mini InstructChatCode | IQ2_S | 7.9 GB | 72.3 t/s | 131K | C44, Usable | |
Phi 3 Medium 128k InstructChatCode | IQ2_XS | 7.8 GB | 33.9 t/s | 131K | C44, Usable | |
Phi 3 Mini 128k InstructChatCode | IQ2_S | 7.9 GB | 72.3 t/s | 131K | C44, Usable | |
DeepSeek Coder v2 Lite BaseChatCode | Q2_K | 7.5 GB | 110.5 t/s | 164K | B62, Decent |
Specs
- Architecture
- Ada Lovelace
- VRAM
- 8 GB GDDR6
- Memory bandwidth
- 256.0 GB/s
- FP16 (dense)
- 29.12 TFLOPS
- CUDA cores
- 3,072
- Tensor cores
- 96
- Compute capability
- 8.9
- TDP
- 115 W
- Released
- 2023-02-22
RTX 4060 Laptop GPU FAQ
What is the largest model the RTX 4060 Laptop GPU 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 26.2 tok/s.
Can the RTX 4060 Laptop GPU 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 4060 Laptop GPU give?
About 26.2 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 6.0 s on a 4K-token prompt.
What power supply does the RTX 4060 Laptop GPU need?
Plan a 250 W PSU (2× the 115 W TDP).
Is renting cheaper than buying an RTX 4060 Laptop GPU?
An RTX 5080 (16 GB) rents from $0.22/hr. With regular daily use, owning pays off.