RTX 5060 Ti 16GB LLM Performance
Local LLM Performance: 32.9 t/s average on 14B models at 16k context. Updated Benchmarks: March 2026.
32.9T/s
943T/s
Summary
In our 2026 testing, we identify the RTX 5060 Ti 16GB as the definitive "value king" for entry-level local LLM enthusiasts. With its 16GB of GDDR7 memory and 448 GB/s bandwidth, we were able to comfortably offload models up to 20B parameters, specifically maxing out the gpt-oss 20B with a 128k context window. While 30B parameter models remain out of reach for this single card, we find its $549 price point makes it the most logical building block for affordable dual-GPU setups.
Key Insights
Relative Performance (Token Generation)
Current Price in US
$549
Avg. Market Value
Current Pricing
Biggest LLMs You Can Run on This GPU
The models below represent the largest language models that fit fully in VRAM on this GPU using 4-bit quantization (GGUF). Benchmarks include token generation and prompt processing speeds measured at their maximum supported context length.
Note: Context values are grouped into standard tiers (4K, 16K, 32K, 64K, 128K). Models may support slightly higher context, but they remain in the lower tier unless they reach the next bracket.
RTX 5060 Ti 16GB local LLM Inference Performance vs Similar GPUs
Compare prompt ingestion and token generation speeds against similar GPUs across widely used local models and extended context lengths up to 256K.
Local LLM Benchmarks
Prompt processing (t/s) and token generation speed (t/s) across different open weight models and context lengths.
| Model | 4k Ctx | 16k Ctx | 32k Ctx | 64k Ctx | 128k Ctx | 256k Ctx |
|---|---|---|---|---|---|---|
| Qwen3 8B (Q4_K) | 2,965.1 | 1,447.9 | 915.1 | 529.8 | — | — |
| Qwen3 14B (Q4_K) | 1,743.0 | 942.6 | 621.0 | — | — | — |
| gpt-oss 20B (MXFP4) | 3,585.2 | 2,753.3 | 1,737.7 | 1,102.3 | 685.3 | — |
| Model | 4k Ctx | 16k Ctx | 32k Ctx | 64k Ctx | 128k Ctx | 256k Ctx |
|---|---|---|---|---|---|---|
| Qwen3 8B (Q4_K) | 69.2 | 51.4 | 38.9 | 25.8 | — | — |
| Qwen3 14B (Q4_K) | 41.1 | 32.9 | 25.9 | — | — | — |
| gpt-oss 20B (MXFP4) | 92.1 | 82.4 | 73.2 | 58.1 | 43.8 | — |
Frequently Asked Questions
Common questions about running LLMs on the RTX 5060 Ti 16GB.
What is the max model size the RTX 5060 Ti 16GB can run?
The card tops out at the 20B parameter range. We successfully ran gpt-oss 20B (MXFP4) with a full 128k context window, but 30B models and larger are out of reach for a single card.
How fast is generation on 14B models?
It performs well for its class. In our benchmarks using Qwen3 14B (Q4_K) at 16k context, we achieved a generation speed of 32.9 t/s and prompt processing of 942.6 t/s.
Is this a good card for a dual-GPU setup?
Yes. Due to its relatively low price of $549 and high VRAM capacity (16GB), it is an excellent choice for stacking two cards to achieve 32GB VRAM without the premium price of flagship GPUs.
What type of VRAM does the 5060 Ti use?
The card features 16GB of GDDR7 memory with a bandwidth of 448 GB/s.
Can the RTX 5060 Ti 16GB run 30B or 32B models?
No, the TX 5060 Ti 16GB cannot run 30B or 32B models fully in VRAM using typical 4-bit quantization due to its 16GB memory limit. However, if you lower the quantization to 3-bit, it may be possible to load the model, though the output quality will noticeably degrade.