NVIDIA RTX 5060 Ti 16GB

NVIDIA RTX 5060 Ti 16GB: Announced and launched the same day, April 16, 2025, the RTX 5060 Ti ships in two VRAM configurations cut from the identical GB206 die (4,608 CUDA cores, a 128-bit bus, 180W TGP) at $429 for this 16GB card and $379 for a separate 8GB SKU (NVIDIA's own GeForce RTX 5060 family spec page). Both variants share the exact same 448 GB/s bandwidth as the plain RTX 5060 one tier down: NVIDIA doubled this card's VRAM over the base 5060 by populating four 2GB GDDR7 modules on the same 128-bit bus rather than widening it, so the extra capacity buys zero extra throughput. Club386's launch review calls that tradeoff deliberate rather than a shortfall, noting the resulting 448 GB/s lands exactly on the 2020 RTX 3060 Ti's number despite two Blackwell architecture generations since. GamersNexus's launch review ("More Marketing BS") measured a real 13-27% average gain over the RTX 4060 Ti at 1440p, and was blunt that NVIDIA's own "50x faster than a GTX 1060" marketing claim doesn't hold up; their own testing put the real generational gap closer to 236%.

This site's calculator puts Llama 3.1 8B at Q4_K_M at 49.0 tok/s (6.66 GB, fits natively), the exact same number the 8GB RTX 5060 gets for the identical model and quant, since both cards share 448 GB/s of bandwidth; the extra 8GB here buys capacity, not speed, for anything that already fit on the smaller card. Qwen3 14B at its recommended Q5_K_M lands at 24.5 tok/s (13.31 GB, fits with headroom), exactly half the RTX 5070 Ti's 49.0 tok/s for the identical 13.31 GB build, tracking the RTX 5070 Ti's exactly-double 896 GB/s bandwidth almost perfectly. GPT-OSS 20B, a model OpenAI explicitly sized to fit a 16GB card, just clears this card's ~15.2 GB of usable VRAM at Q4_K_M (14.55 GB, 38.8 tok/s), under a gigabyte of headroom for context, matching hardware-corner.net's independent LLM benchmark of this exact card, which found it "tops out at the 20B parameter range" (their real MXFP4 build reports 92.1 tok/s at 4k context, falling to 43.8 tok/s at a full 128k window). What the extra 4GB over the RTX 5070 actually buys: Qwen 3.6 27B, which doesn't fit the 12GB RTX 5070 at any quantization (even Q2_K's 12.12 GB exceeds its ~11.4 GB usable budget), fits here at Q3_K_M (15.15 GB, 21.5 tok/s) or the more aggressive Q2_K (12.12 GB, 26.9 tok/s). Above that, 32B-class dense models don't fit natively on this card either: even NVFP4's 19.87 GB overshoots the usable budget, landing at a 6.5 tok/s offload result, so this 16GB's real ceiling is the 20-27B range, not 32B.

Full CUDA support, but like every desktop Blackwell card this reports compute capability 12.0 (sm_120), genuinely new hardware needing the CUDA 12.8 runtime, and NVIDIA's own engineering blog measured a ~27% LM Studio/llama.cpp speedup on the sibling RTX 5080 just from that runtime upgrade; a stale llama.cpp, Ollama, or PyTorch build may still not recognize this GPU. On value, Club386's launch review argues NVIDIA priced this card above its own trendline for gaming (the RTX 5070 delivers 34% more frame rate for only 28% more money) and suggests a fairer price nearer $410 than the actual $429. That comparison flips for local LLM work, where the RTX 5070's 12GB can't hold what this card's 16GB does (Qwen 3.6 27B, GPT-OSS 20B) at any price. This is genuinely the cheapest way into 16GB in the current Blackwell lineup: $320 less than the RTX 5070 Ti and $570 less than the RTX 5080 for identical capacity, trading less than half their bandwidth (448 vs 896/960 GB/s) to get there. NVIDIA also sells a separate 8GB RTX 5060 Ti SKU under the same name at a $50 lower MSRP: same GB206 die and identical 448 GB/s bandwidth, half the capacity, and a real cliff on anything above the 20B class.