GeForce RTX 4060 Ti 16GB Price & Used Prices: Which Local LLMs Can It Run?
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The GeForce RTX 4060 Ti 16GB has 16GB of GDDR6 memory with 288 GB/s of bandwidth. The median asking price is about $1,327 on Amazon.jp. At 4-bit quantization and 8K context it fits a dense model of up to about 23B parameters, at roughly 14 tokens/s.
Amazon.jp
GeForce RTX 4060 Ti 16GB price history
Amazon.jp
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Full GeForce RTX 4060 Ti 16GB specifications
- Memory16 GB · GDDR6
- Bandwidth288 GB/s
- FP16 / BF1688.3 TFLOPS
- FP8 / INT8176.5 / 176.5 TOPS
- Bus width
- 128-bit
- Architecture
- Ada Lovelace (AD106)
- Cores
- 4,352
- Tensor cores
- 136
- Ecosystem
- CUDA
- Interface
- PCIe 4.0 x8
- NVLink
- Not supported
- Power
- 165 W
- Power connector
- 1× 8-pin / 16-pin 12VHPWR
- Type
- Consumer
- Launch date
- Jul 18, 2023
- MSRP
- $499
What LLMs can the GeForce RTX 4060 Ti 16GB run?
Models up to 50B parameters on a single GeForce RTX 4060 Ti 16GB, versions released since 2026 only
| Model | Size | Runs? | Speed t/s | Max context |
|---|---|---|---|---|
| 3.8 GB | Runs | 52.3 | 128K | |
| 4.1 GB | Runs | 48.1 | 256K | |
| 4.7 GB | Runs | 41.5 | 256K | |
| 10.5 GB | Runs | 81 | 256K | |
| 11.8 GB | Runs | 17.3 | 64K | |
| 9.8 GB | Runs | 20.7 | 93K | |
| 11.9 GB | Runs | 93.9 | 75K | |
| 11.8 GB | Runs | 16.7 | 41K | |
| 12.3 GB | Runs | 108.3 | 181K |
| Model | Size | Runs? | Speed t/s | Max context |
|---|---|---|---|---|
| 5 GB | Runs | 40.4 | 128K | |
| 5.7 GB | Runs | 35.3 | 256K | |
| 7.1 GB | Runs | 28.2 | 256K | |
| 16.9 GB | Needs RAM offload | 32.3 | 256K | |
| 16.8 GB | Too big | — | — | |
| 16.5 GB | Too big | — | — | |
| 18.3 GB | Needs RAM offload | 33.5 | 198K | |
| 18.3 GB | Too big | — | — | |
| 22.1 GB | Needs RAM offload | 44 | 256K |
| Model | Size | Runs? | Speed t/s | Max context |
|---|---|---|---|---|
| 8.2 GB | Runs | 25.1 | 128K | |
| 9.5 GB | Runs | 21.6 | 196K | |
| 12.7 GB | Runs | 16.2 | 183K | |
| 26.9 GB | Needs RAM offload | 21.5 | 256K | |
| 28.6 GB | Too big | — | — | |
| 29 GB | Too big | — | — | |
| 31.8 GB | Needs RAM offload | 20.8 | 198K | |
| 32.6 GB | Too big | — | — | |
| 36.9 GB | Needs RAM offload | 28.6 | 256K |
RunsFits fully in VRAM; speed is estimated from VRAM bandwidth.
Needs RAM offloadMoE only: expert weights sit in system RAM, so speed is estimated from 70 GB/s RAM bandwidth.
Too bigWon’t fit on one card at this quantization, even with RAM offload.
Dual, 4x and 8x GeForce RTX 4060 Ti 16GB for LLMs: which models fit?
Cards needed for 50B+ models released since 2026, with vLLM tensor parallelism at 32K context
| Model | Size | Cards | Total price | Total VRAM | Speed t/s | Total power |
|---|---|---|---|---|---|---|
| 78.9 GB | 8 cards | $10,618 | 128 GB | 53.9 | 1,320 W | |
| 96.8 GB | 8 cards | $10,618 | 128 GB | 39.4 | 1,320 W | |
| 108.7 GB | 8 cards | $10,618 | 128 GB | 29.6 | 1,320 W |
| Model | Size | Cards | Total price | Total VRAM | Speed t/s | Total power |
|---|---|---|---|---|---|---|
| 111.3 GB | 8 cards | $10,618 | 128 GB | 42 | 1,320 W |
At this quantization, even 8 × GeForce RTX 4060 Ti 16GB cannot hold any model over 50B.
Card counts are 1 / 2 / 4 / 8, each using 90% of its VRAM. Speed is based on one card’s bandwidth; price covers GPUs only. No NVLink; cards talk over PCIe. Whether it runs also depends on vLLM support.
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FAQ
How large a model can the GeForce RTX 4060 Ti 16GB run?
A single GeForce RTX 4060 Ti 16GB has 16GB of GDDR6 VRAM. At 4-bit quantization and 8K context it fits a dense model of up to about 23B parameters, or about 13B at 8-bit. MoE models can offload experts to system RAM to run larger ones, such as Qwen3.6 35B A3B (36B).
Can the GeForce RTX 4060 Ti 16GB run a 70B model?
Not on a single card. At 4-bit with an 8K context a 70B dense model needs about 43GB, more than the GeForce RTX 4060 Ti 16GB's 16GB. It runs if you split the layers across 3 cards with llama.cpp (48GB total).
What are the best LLMs to run on the GeForce RTX 4060 Ti 16GB?
Among models released in 2026, the largest dense model that fits entirely in VRAM at 4-bit is Gemma 4 12B, at an estimated 28.2 tokens/s. The full list is in the table above.
How many tokens per second does the GeForce RTX 4060 Ti 16GB get on LLMs?
Estimated from memory bandwidth at 4-bit and 8K context: 8B dense: about 38.6 tokens/s and 14B dense: about 22.8 tokens/s. MoE models read only the active parameters for each token, so they run much faster. Real-world results are usually 70%–100% of the estimate.
What LLMs can dual GeForce RTX 4060 Ti 16GB cards run?
With vLLM tensor parallelism at 4-bit and 32K context, two GeForce RTX 4060 Ti 16GB cards cannot fit any model of 50B or larger released in 2026. At 4-bit with 32K context the minimum is 8 cards, which fits Qwen3.8 Flash Next.
How much does a GeForce RTX 4060 Ti 16GB cost?
As of Sep 29, 2026: eBay median $700 (5 listings), Amazon.jp median $1,327 (3 listings), and Xianyu median $537 (3 listings). Figures are medians of live listings, refreshed every 6 hours.
Is the GeForce RTX 4060 Ti 16GB price going up or down?
As of Sep 29, 2026, the Amazon.jp median is down 16.4% over 7 days, down 16.4% over 30 days.
GeForce RTX 4060 Ti 16GB vs GeForce RTX 5060 Ti 16GB: which is better for LLMs?
The GeForce RTX 5060 Ti 16GB has 16GB of VRAM and 448 GB/s of bandwidth; the GeForce RTX 4060 Ti 16GB has 16GB and 288 GB/s. At the Amazon.jp median, the GeForce RTX 5060 Ti 16GB costs about $956, 28% less than the GeForce RTX 4060 Ti 16GB ($1,327). For 14B dense models at 4-bit, the GeForce RTX 4060 Ti 16GB is estimated at about 22.8 tokens/s and the GeForce RTX 5060 Ti 16GB at about 35.1 tokens/s.