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NVIDIA · Ada Lovelace · 2023

NVIDIA GeForce RTX 4060 Ti 16GB for local AI

Cheap used 16GB, but its 288 GB/s bus makes it slow for the capacity.

Updated · Speeds marked ~ are estimates; seemethodology

VRAM
16GB
Bandwidth
288 GB/s
Power
165W
Runs well
6 models

RTX 4060 Ti 16GB

Typically about $380 used

Check price at AmazonFind it used on eBay

Can the RTX 4060 Ti 16GB run LLMs?

The RTX 4060 Ti 16GB has 16GB of GDDR6 and 288 GB/s of memory bandwidth, which decides how big a model fits and how fast it generates text. It comfortably runs models up to about 15B parameters: the largest in our catalog is Phi-4 at Q5_K_M (13GB with 8K context, ~21 tokens/sec). Our top all-round pick for it is Qwen3.8 27B (Q3_K_M, ~17 tokens/sec). Llama 3.3 70B Instruct only runs with partial CPU offload, at about 1.3 tokens/sec with CPU offload.

Recommendations

Best models for the RTX 4060 Ti 16GB

  1. Best overall · also coding, reasoning, vision, largest that fits

    Qwen3.8 27B

    Q3_K_M · 15GB · ~17 tokens/sec

    Fits, tight

  2. Runner-up

    Qwen3.5 9B

    Q8_0 · 12GB · ~21 tokens/sec

    Runs well

  3. Fastest good model

    Gemma 4 26B A4B

    Q3_K_M · 14GB · ~63 tokens/sec

    Fits, tight
Read: the best LLMs to run on the RTX 4060 Ti 16GB

Compatibility

What runs on the RTX 4060 Ti 16GB

Every current model in our catalog, at the best quantization that fits in 16GB with 8K tokens of context. "Partial offload" means part of the model runs from system RAM (we assume 64GB), which is much slower.

Which open-weight models run on the NVIDIA GeForce RTX 4060 Ti 16GB, with the best quantization and estimated speed
ModelParametersBest quantMemorySpeedVerdict
Gemma 4 E4B8BQ8_010 GB~24 tok/sRuns well
Qwen3.5 9B9BQ8_012 GB~21 tok/sRuns well
Phi-414.7BQ5_K_M13 GB~21 tok/sRuns well
gpt-oss-20b20.9B (3.6B active)MXFP415 GB63 tok/sFits, tight
Gemma 4 26B A4B26B (3.8B active)Q3_K_M14 GB~63 tok/sFits, tight
Qwen3.8 27B27BQ3_K_M15 GB~17 tok/sFits, tight
Gemma 4 31B31BQ4_K_M22 GB~4.8 tok/sPartial offload
Qwen3.6 35B-A3B35B (3B active)Q4_K_M24 GB~37 tok/sPartial offload
GLM-4.5-Air106B (12B active)———Won't fitWhat it needs
Llama 4 Scout109B (17B active)———Won't fitWhat it needs
gpt-oss-120b117B (5.1B active)———Won't fitWhat it needs
Qwen3.5 122B-A10B122B (10B active)———Won't fitWhat it needs
DeepSeek V4 Flash284B (13B active)———Won't fitWhat it needs
GLM-5.3-Flash320B (18B active)———Won't fitWhat it needs
GLM-5.3744B (40B active)———Won't fitWhat it needs

Performance

RTX 4060 Ti 16GB vs. alternatives on Qwen3.8 27B

Generation speed in tokens per second for a single user. Token generation is limited mostly by memory bandwidth, which is why bandwidth predicts these results so well.

  1. RTX 5060 Ti 16GB

    Q3_K_M · 16GB

    ~26tok/s

  2. RTX 4060 Ti 16GB

    Q3_K_M · 16GB

    ~17tok/s

  3. RX 9060 XT 16GB

    Q3_K_M · 16GB

    ~15tok/s

Estimated (method)

Measured

RTX 4060 Ti 16GB benchmark results

ModelQuantRuntimeGenerationPromptSource
gpt-oss-20bMXFP4llama.cpp (CUDA)63 tok/s3275 tok/sHardware Corner: RTX 4060 Ti 16GB LLM Performance · March 2026
Qwen3 8BQ4_K_XLllama.cpp (CUDA)46 tok/s2675 tok/sHardware Corner: RTX 4060 Ti 16GB LLM Performance · March 2026
Qwen3 14BQ4_K_XLllama.cpp (CUDA)27 tok/s1645 tok/sHardware Corner: RTX 4060 Ti 16GB LLM Performance · March 2026

Our take

Should you buy the RTX 4060 Ti 16GB for AI?

The RTX 4060 Ti 16GB pairs 16GB of GDDR6 with a narrow 128-bit bus, giving only 288 GB/s. It can load the same 14B to 24B models as faster 16GB cards, but generates tokens noticeably slower. Used cards sold for about $380 to $470 in October 2026, which makes it one of the cheapest ways to get 16GB of CUDA memory. If you can stretch to a new RTX 5060 Ti 16GB, you get about 55 percent more bandwidth.

What we like

  • 16GB of CUDA memory at a low used price
  • 165W board power
  • Compact two-slot cards

Watch out for

  • Only 288 GB/s memory bandwidth
  • PCIe 4.0 x8 link is slower on older boards

Best for: Budget builds that need 16GB · Running 14B models at higher quality

Specifications

RTX 4060 Ti 16GB specs that matter for AI

Memory
16GB GDDR6
Memory bandwidth
288 GB/s
Memory bus
128-bit
Architecture
Ada Lovelace
Power
165W
Interface
PCIe 4.0 x8
Released
2023
Launch price
$499
Street price (used)
~$380 (2026-10)
Software
CUDA, Vulkan

Sources: NVIDIA GeForce RTX 4060 Ti and 4060 product page, NVIDIA: RTX 4060 Ti 16GB announcement and pricing

Cross-shop

Alternatives to the RTX 4060 Ti 16GB

NVIDIA2025
16GB

GDDR7 · 448 GB/s

RTX 5060 Ti 16GB

~$620

NVIDIA2021
12GB

GDDR6 · 360 GB/s

RTX 3060 12GB

~$270 used

AMD2025
16GB

GDDR6 · 320 GB/s

RX 9060 XT 16GB

~$470

Frequently asked questions

How much VRAM does the RTX 4060 Ti 16GB have?

The NVIDIA GeForce RTX 4060 Ti 16GB has 16GB of GDDR6 with 288 GB/s of memory bandwidth on a 128-bit bus.

What is the largest LLM the RTX 4060 Ti 16GB can run?

Fully in GPU memory, the largest model in our catalog that runs comfortably is Phi-4 (14.7B) at Q5_K_M, using about 13GB with 8K context at ~21 tokens/sec.

Can the RTX 4060 Ti 16GB run Llama 3.3 70B?

Only with partial CPU offload. At Q4_K_M the model needs about 47GB with 8K context, so part of it spills into system RAM and speed drops to about 1.3 tokens/sec with CPU offload. For usable 70B speeds you want 48GB of VRAM or more (for example two 24GB cards).

What is the best LLM to run on the RTX 4060 Ti 16GB?

Our top pick is Qwen3.8 27B at Q3_K_M, which fits in 16GB with room for 8K of context and runs at ~17 tokens/sec. See our full list of the best models for the RTX 4060 Ti 16GB for coding, reasoning, and vision picks.

Is the RTX 4060 Ti 16GB good for local AI in 2026?

Cheap used 16GB, but its 288 GB/s bus makes it slow for the capacity.