6GB · AI Score 1.5/100 · anchored estimate vs 51 measured cards
1.5 AI Score Includes estimates
We have not run NVIDIA GeForce GTX 1660 on our bench. These figures are anchored estimates, interpolated per workload against the 51 GPUs we did measure (confidence: low). On Llama 3.1 8B (Q4_K_M) NVIDIA GeForce GTX 1660 should deliver about 36.1 tokens/sec. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 6GB. 10 of the 12 workloads won't fit on 6GB at the tested precision, Qwen2.5-Coder 14B, Qwen3 32B, Llama 3.3 70B, Stable Diffusion XL and others. We publish those as hard gates rather than quietly dropping to a smaller quant.
| Workload | Result | Telemetry | Data |
|---|---|---|---|
| Qwen3 4B | 54.1 tok/s | estimated | Est. |
| Llama 3.1 8B | 36.1 tok/s | estimated | Est. |
| Qwen2.5-Coder 14B | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Qwen3 32B | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Llama 3.3 70B | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Workload | Result | Telemetry | Data |
|---|---|---|---|
| Stable Diffusion XL | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Z-Image Turbo | ✕ Won't fit | VRAM-gated at this precision | Est. |
| FLUX.1 dev | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Workload | Result | Telemetry | Data |
|---|---|---|---|
| FLUX.1 Kontext dev | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Qwen-Image-Edit | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Workload | Result | Telemetry | Data |
|---|---|---|---|
| LTX-Video (distilled) | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Wan 2.2 5B (720p) | ✕ Won't fit | VRAM-gated at this precision | Est. |
| Architecture | Turing (TU116) |
| CUDA cores | 1,408 |
| VRAM | 6GB GDDR5 |
| Memory bus | 192-bit |
| Memory bandwidth | 192 GB/s |
| Boost clock | 1,785 MHz |
| TDP | 120 W |
| Process | 12nm |
| Interface | PCIe 3.0 x16 |
| Release date | 2019-03-14 |
| Launch MSRP | $219 |
NVIDIA GeForce GTX 1660 scores 1.5/100, #101 of 102. It ran 2 of 12; 10 exceeded its 6GB. Figures are anchored estimates, not measurements, we flag that on every row.
100% = this card, AI & Machine Learning headline metric (AI Score). #61 of 61 desktop cards in this vertical.
| GPU | Relative | % | AI Score |
|---|---|---|---|
| NVIDIA GeForce GTX 1070 Ti | 113% | 1.7 | |
| NVIDIA GeForce GTX 1660 Super | 113% | 1.7 | |
| NVIDIA GeForce RTX 2060 | 113% | 1.7 | |
| NVIDIA GeForce GTX 1660 Ti | 107% | 1.6 | |
| NVIDIA GeForce GTX 1660 | 100% | 1.5 |
Same card, other workloads: NVIDIA GeForce GTX 1660 Gaming benchmarks
← All AI & Machine Learning GPU rankings
| Transistors | 6,600 million |
| Die size | 284 mm² |
| Fabricated by | TSMC |
| Transistor density | 23.2 million per mm² |
Denser than 11% of the 76 cards we have silicon data for. Density is the clearest measure of what a process node bought: a card that gained it without growing the die got its speed from the fab rather than the architecture.
Silicon figures from Wikipedia (CC BY-SA 4.0). Benchmarks on this page are our own. Compare every chip.
Whole-job timings, composed from our measured per-model results on this card.
Can't run: 60-second AI short film (needs Qwen3 32B), 60-second AI short film, narrated (needs Qwen3 32B), 10 short social clips (needs Qwen3 32B), 40-product photo shoot (needs Stable Diffusion XL), 6-panel comic page (needs Qwen3 32B), 20 long-form articles (needs Llama 3.3 70B), Full codebase review (needs Qwen2.5-Coder 14B), Character sheet, 12 poses (needs FLUX.1 dev), 100-photo restoration batch (needs FLUX.1 Kontext dev), 24-frame storyboard (needs Qwen3 32B), 100-photo restore and enlarge (needs FLUX.1 Kontext dev), 40-product shoot, start to finish (needs Stable Diffusion XL), 20-asset 3D game kit (needs Stable Diffusion XL).