NVIDIA · Pascal
Best AI Models for NVIDIA GeForce GTX 1060 6GB
Runs only small models well; 7–9B only just fits.
6 GB at 192 GB/s: ~7B at Q4 is tight. Pascal: no Tensor Cores and very slow FP16, so it runs GGUF (llama.cpp, Ollama) fine but not FP16 runtimes like vLLM; current CUDA 13 builds dropped Pascal — use CUDA 12 or Vulkan builds.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 43.9 t/s | 43.9 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB |
| # | Model | Speed | Reasoning Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 5.0 GB · 43.9 t/s | 43.9 tok/s | Q4_K_M · 5.0 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | overall | Q4_K_M · 3.4 GB |
| 3 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB |
| # | Model | Speed | Long context Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB | |
| 3 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 4 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB | |
| 5 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 97.5 t/s | 97.5 tok/s | Q4_K_M · 1.6 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 114 t/s | 114 tok/s | Q4_K_M · 5.5 GB | |
| 3 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 5 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 43.9 t/s | 43.9 tok/s | Q4_K_M · 5.0 GB | |
| 3 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 97.5 t/s | 97.5 tok/s | Q4_K_M · 1.6 GB | |
| 4 | LFM3 Omni 2BLiquid AI Q4_K_M · 2.4 GB · 73.4 t/s | 73.4 tok/s | Q4_K_M · 2.4 GB | |
| 5 | Cosmos Reason2 2BNVIDIA Q4_K_M · 3.5 GB · 77.5 t/s | 77.5 tok/s | Q4_K_M · 3.5 GB |
The GTX 1060 6GB is an entry card in the 6 GB class: it runs only small models well. It is power-hungry for its speed, and the best speed per dollar of the cards compared at ≈$70 used. Pascal generation, released 2016.
GTX 1060 6GB strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 22.6 tok/s in 5.8 GB
- Low power draw: 120 W board power; a 250 W PSU is enough
Weaknesses
- 14B models don't fit: Qwen3 14B needs 11.9 GB at Q4 vs 6 GB here
- Little room for context: Qwen3.5 9B uses 5.8 of 6 GB, 0.2 GB left
- Slow prompt reading: A 4K-token prompt on Qwen3.5 4B waits 19.4 s for the first token
- No FP8 or NVFP4: Pascal predates both; use GGUF, AWQ or GPTQ builds
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 GTX 1060 6GB 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 |
GTX 1060 6GB6 GB | about $249 | 22.6 | 9.1 | 18.8 |
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 |
|---|---|---|---|---|
GTX 1060 6GB6 GB | about $70 | 22.6 | 32.3 | 18.8 |
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 407012 GB | about $575 | 51.5 | 9.0 | 25.8 |
RTX 40608 GB | about $335 | 27.8 | 8.3 | 24.2 |
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 |
Cost per token: the GTX 1060 6GB against 6–12 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
- $0.20
- Power
- $0.22
Renting costs as much as buying after ≈600 hours (≈0.4 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 GTX 1060 6GB, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.
Output speed depends on memory bandwidth (192 GB/s). Grey rows need more than 6 GB.
- 22.6tok/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 738 models on the GTX 1060 6GB
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 |
|---|---|---|---|---|---|---|
Mamba 2.8B HFChat | Q4_K_M | 3.7 GB | 68.2 t/s | — | S85, Runs great | |
| Q4_K_M | 1.0 GB | 123.6 t/s | 2K | S95, Runs great | ||
Pythia 1BChat | Q4_K_M | 0.7 GB | 175.8 t/s | 2K | S99, Runs great | |
| Q4_K_M | 0.3 GB | 416.0 t/s | 2K | S100, Runs great | ||
Xglm 564MChat | Q4_K_M | 0.4 GB | 337.3 t/s | 2K | S100, Runs great | |
DialoGPT SmallChat | Q4_K_M | 0.1 GB | 1040.0 t/s | 1K | S100, Runs great | |
Tiny Qwen3ForCausalLMChatFunctions | Q4_K_M | 0.6 GB | 416.0 t/s | 41K | S100, Runs great | |
Openai GPTChat | Q4_K_M | 0.1 GB | 1560.0 t/s | 1K | S100, Runs great | |
Pythia 1.4BChat | Q4_K_M | 1 GB | 124.8 t/s | 2K | S95, Runs great | |
Llama 160MChat | Q4_K_M | 0.5 GB | 265.5 t/s | 2K | S100, Runs great | |
| Q4_K_M | 2.9 GB | 72.1 t/s | 8K | S86, Runs great | ||
Qehwa Pashto LlmChat | Q4_K_M | 5.8 GB | 25.0 t/s | 131K | C39, Usable | |
| Q4_K_M | 1.9 GB | 67.8 t/s | 8K | S85, Runs great | ||
GLM 4.6V FlashVisionFunctions | Q3_K_M | 6.0 GB | 23.1 t/s | 131K | C32, Usable | |
| Q4_K_M | 0.3 GB | 378.2 t/s | 2K | S100, Runs great |
Specs
- Architecture
- Pascal
- VRAM
- 6 GB GDDR5
- Memory bandwidth
- 192.0 GB/s
- FP16 (dense)
- 4.37 TFLOPS
- CUDA cores
- 1,280
- Tensor cores
- 0
- Compute capability
- 6.1
- TDP
- 120 W
- Released
- 2016-07-19
- MSRP
- $249
GTX 1060 6GB FAQ
Is the GTX 1060 6GB still worth it in 2026?
At ≈$70 used you get 32.3 tok/s per $100 on Qwen3.5 9B, which ranks 1st of the 8 cards compared here; it is also the 4th fastest out of 6 cards with 6 GB. It runs only small models well; 7–9B only just fits.
What is the largest model the GTX 1060 6GB can run?
Qwen2.5 7B Instruct (7.6B) is the largest at 4-bit or better: at Q4_K_M it uses 5.8 GB of 6 GB, and runs at about 25.0 tok/s. At 3-bit, a bigger model fits too: Gemma 2 9B IT (9.2B) at IQ3_M, 5.7 GB.
Can the GTX 1060 6GB run Qwen3.5 4B?
Yes. Qwen3.5 4B fits at Q4_K_M, using 3.4 GB of 6 GB, and it is the best model that runs well on this card.
Can the GTX 1060 6GB run 14B models?
No. Qwen3 14B needs 11.9 GB at Q4, more than the 6 GB on this card.
How many tokens per second does the GTX 1060 6GB give?
About 38.3 tok/s on Qwen3.5 4B at Q4_K_M, with the first token after 19.4 s on a 4K-token prompt.
What power supply does the GTX 1060 6GB need?
Plan a 250 W PSU (2× the 120 W TDP).
Is renting cheaper than buying a GTX 1060 6GB?
An RTX 3080 Ti (12 GB) rents from $0.12/hr. Renting costs as much as buying after ≈600 hours (≈0.4 years at 4 h a day).