NVIDIA · Ada Lovelace · 8 GB VRAM tier
Best AI Models for NVIDIA GeForce RTX 4060 Ti 8GB
Runs 7–9B models well; 14B doesn't fit in 8 GB.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 29.4 t/s | 29.4 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 57.4 t/s | 57.4 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 30.7 t/s | 30.7 tok/s | Q4_K_M · 7.3 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 65.9 t/s | 65.9 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 158 t/s | 158 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 · 29.4 t/s | 29.4 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 65.9 t/s | 65.9 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 37.5 t/s | 37.5 tok/s | Q4_K_M · 5.8 GB | |
| 4 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 30.7 t/s | 30.7 tok/s | overall | Q4_K_M · 7.3 GB |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 158 t/s | 158 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 · 57.4 t/s | 57.4 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 29.4 t/s | 29.4 tok/s | Q4_K_M · 6.6 GB | |
| 3 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 158 t/s | 158 tok/s | Q4_K_M · 5.5 GB | |
| 4 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 35.2 t/s | 35.2 tok/s | Q4_K_M · 5.6 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 98.5 t/s | 98.5 tok/s | Q4_K_M · 2.5 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 57.4 t/s | 57.4 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 158 t/s | 158 tok/s | Q4_K_M · 5.5 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 35.2 t/s | 35.2 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Q4_K_M · 6.5 GB · 30.1 t/s | 30.1 tok/s | Q4_K_M · 6.5 GB | |
| 5 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 29.4 t/s | 29.4 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 · 29.4 t/s | 29.4 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 57.4 t/s | 57.4 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 65.9 t/s | 65.9 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Q4_K_M · 6.5 GB · 30.1 t/s | 30.1 tok/s | Q4_K_M · 6.5 GB | |
| 5 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 146 t/s | 146 tok/s | Q4_K_M · 1.6 GB |
The RTX 4060 Ti 8GB is an entry card in the 8 GB class: it runs 7–9B models well. It is power-hungry for its speed, and pricier per token than most of the cards compared at ≈$362 used. Ada Lovelace generation, released 2023.
RTX 4060 Ti 8GB strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 29.4 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
- Used prices still near MSRP: ≈$362 used vs its $399 MSRP
Speed per dollar and per watt
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 4060 Ti 8GB 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 50608 GBBest new value | about $460 | 45.8 | 10.0 | 31.6 |
RTX 507012 GB | about $840 | 68.7 | 8.2 | 27.5 |
RTX 4060 Ti 8GB8 GB | about $399 | 29.4 | 7.4 | 18.4 |
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 50608 GBBest used value | about $388 | 45.8 | 11.8 | 31.6 |
RTX 3060 12GB12 GB | about $329 | 36.8 | 11.2 | 21.6 |
RTX 507012 GB | about $736 | 68.7 | 9.3 | 27.5 |
RTX 407012 GB | about $575 | 51.5 | 9.0 | 25.8 |
RTX 40608 GB | about $335 | 27.8 | 8.3 | 24.2 |
RTX 4060 Ti 8GB8 GB | about $362 | 29.4 | 8.1 | 18.4 |
RTX 4070 SUPER12 GB | about $675 | 51.5 | 7.6 | 23.4 |
RTX 4070 Ti12 GB | about $722 | 51.5 | 7.1 | 18.1 |
Cost per token: the RTX 4060 Ti 8GB against 8–12 GB cards
On Qwen3.5 9B (9B params, Q4_K_M, 4K context). Speed, cost per token and power per token depend on the model.
- Card, used price
- $0.78
- Power
- $0.23
Renting costs as much as buying after ≈2,100 hours (≈1.4 years at 4 h a day).
Each dot is a card; hover or tap it for its numbers, click to open it. Cards without a price for the chosen basis are left out. How we calculate cost per token
Cards people weigh against the RTX 4060 Ti 8GB, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.
Output speed depends on memory bandwidth (288 GB/s). Grey rows need more than 8 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB29.4tok/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 822 models on the RTX 4060 Ti 8GB
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 |
|---|---|---|---|---|---|---|
Yi 6BChat | Q4_K_M | 4.2 GB | 46.0 t/s | 4K | A78, Runs well | |
| Q4_K_M | 7.3 GB | 34.7 t/s | 131K | B57, Decent | ||
Qwen2.5 0.5BChatFunctions | Q4_K_M | 0.8 GB | 301.9 t/s | 33K | S100, Runs great | |
| Q4_K_M | 7.6 GB | 33.9 t/s | 41K | B50, Decent | ||
Mellum 4B BaseChatCode | Q4_K_M | 5.7 GB | 53.9 t/s | 8K | A81, Runs well | |
| Q4_K_M | 1.7 GB | 146.3 t/s | 33K | S97, Runs great | ||
Llama 3.2 1BChat | Q4_K_M | 2.3 GB | 228.3 t/s | — | S100, Runs great | |
Nemotron Mini 4B InstructChatFunctions | Q4_K_M | 3.2 GB | 63.0 t/s | 4K | A84, Runs well | |
Glm 4 9B ChatChat | Q3_K_M | 7.7 GB | 37.1 t/s | 131K | B48, Decent | |
Qwen2.5 7BChatFunctions | Q4_K_M | 5.8 GB | 37.5 t/s | 131K | A74, Runs well | |
GPT OSS 20B RichardErkhov HeresyChatFunctions | IQ2_M | 7.6 GB | 107.8 t/s | 131K | B62, Decent | |
| IQ2_XXS | 7.5 GB | 107.6 t/s | 203K | B62, Decent | ||
SmolLM 1.7BChat | Q4_K_M | 1.7 GB | 108.2 t/s | 2K | S93, Runs great | |
Qwen2.5 Math 7B InstructChatMathFunctions | Q4_K_M | 5.1 GB | 37.5 t/s | 4K | A74, Runs well | |
SmolLM 360MChat | Q4_K_M | 0.6 GB | 312.0 t/s | 2K | S100, Runs great |
Specs
- Architecture
- Ada Lovelace
- VRAM
- 8 GB GDDR6
- Memory bandwidth
- 288.0 GB/s
- FP16 (dense)
- 44.10 TFLOPS
- CUDA cores
- 4,352
- Tensor cores
- 136
- Compute capability
- 8.9
- TDP
- 160 W
- Released
- 2023-05-24
- MSRP
- $399
RTX 4060 Ti 8GB FAQ
Is the RTX 4060 Ti 8GB still worth it in 2026?
At ≈$362 used you get 8.1 tok/s per $100 on Qwen3.5 9B, which ranks 6th of the 8 cards compared here; it is also the 7th fastest out of 12 cards with 8 GB. It runs 7–9B models well; 14B doesn't fit in 8 GB.
What is the largest model the RTX 4060 Ti 8GB 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 29.4 tok/s.
Can the RTX 4060 Ti 8GB 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 Ti 8GB give?
About 29.4 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 4.0 s on a 4K-token prompt.
What power supply does the RTX 4060 Ti 8GB need?
Plan a 350 W PSU (2× the 160 W TDP).
Is renting cheaper than buying an RTX 4060 Ti 8GB?
Rent from $0.18/hr. Renting costs as much as buying after ≈2,100 hours (≈1.4 years at 4 h a day).