Why is the RTX 3060 sometimes faster than the RTX 4060 Ti for LLMs?

Memory bandwidth. The RTX 3060 12GB uses a 192-bit memory bus achieving 360 GB/s. The RTX 4060 Ti uses a 128-bit bus achieving only 288 GB/s — 20% less. LLM token generation is bandwidth-bound: the GPU reads the full model weights from VRAM for each token. Narrower bus = fewer bytes per second = fewer tokens per second. NVIDIA prioritized power efficiency and die size over bus width for the 4060 series, which benefits gaming but hurts LLM inference.

Is the RTX 4090 still worth buying with the RTX 5090 available?

Yes, especially used. A used RTX 4090 at $1500-1700 offers 24 GB and 1008 GB/s — excellent for 7-32B models. The RTX 5090 at $2000 offers 32 GB and 1792 GB/s — better for everything. The 4090 makes sense if you want to save $300-500 and do not need the 5090's 32 GB for 70B models. Both are excellent; the 4090 is the value play, the 5090 is the performance play.

Should I buy an RTX 4080 for LLMs?

Probably not. At $700-900 used, a used RTX 3090 offers 24 GB (vs 16 GB) and higher bandwidth (936 vs 717 GB/s) for similar money. The 4080 is a great gaming card but a poor LLM value proposition due to its 16 GB VRAM ceiling at a 24 GB price point. If you find a 4080 at a steep discount ($500-600), it becomes more interesting.

Does the 40 series support NVFP4?

No. NVFP4 is exclusive to Blackwell architecture (RTX 50 series). The 40 series (Ada Lovelace) supports FP8 natively via tensor cores, which is a step down from NVFP4. For GGUF-based inference, this does not matter — GGUF quantization is integer-based and runs on the CUDA cores, not tensor cores.

What is the best 40 series card for LLMs under $600?

The RTX 4060 Ti 16GB ($450-500 new, $350-400 used) is the only 40 series card with more than 12 GB under $600. It runs 14B models at Q4 with comfortable context. For pure LLM value, a used RTX 3060 12GB ($200) or a stretch to a used RTX 3090 ($700-900) are better choices than any 40 series card in this price range.

NVIDIA RTX 40 Series for LLMs: Complete VRAM & Performance Guide

CanItRunJuly 1, 202610 min readHardware

The RTX 40 Series Lineup: Ada Lovelace for LLMs

NVIDIA's RTX 40 series (Ada Lovelace, 2022-2024) spans 8 GB to 24 GB of VRAM across consumer cards. For LLM inference, the key architectural features are: hardware-accelerated FP16 and FP8 via 4th-gen Tensor Cores, improved memory compression that slightly reduces effective VRAM usage compared to Ampere, and significantly better power efficiency (TSMC 4N process). However, one architectural regression matters for LLMs: NVIDIA narrowed memory bus widths across the lineup. The RTX 4060 and 4060 Ti use a 128-bit bus (vs 192-bit on the RTX 3060), capping bandwidth at 272-288 GB/s. This makes the 4060 Ti 16GB paradoxically slower for token generation than the older RTX 3060 12GB (360 GB/s on a 192-bit bus) — the 4060 Ti has more VRAM but generates tokens more slowly. The RTX 4070 and above use wider buses (192-bit for 4070, 256-bit for 4080/4090) with faster GDDR6X memory, restoring competitive bandwidth. The 4090's 384-bit bus with 21 Gbps GDDR6X achieves 1008 GB/s — the highest of any consumer GPU until the RTX 5090.

RTX 4060 (8 GB) and 4060 Ti (8/16 GB): Budget Lovelace

The RTX 4060 (8 GB, 272 GB/s, $300 new) is the entry-level 40 series card. It runs 7-8B models at Q4_K_M (~5 GB) comfortably with 4-8K context. The 8 GB ceiling means 14B models do not fit at usable quantization — Q2_K on a 14B technically fits the weights (~6 GB) but leaves almost no room for KV cache. For LLMs specifically, the RTX 4060 is a poor value: the older RTX 3060 12GB ($200 used) offers 50% more VRAM and higher bandwidth (360 vs 272 GB/s) for less money. The RTX 4060 Ti 8GB ($400) suffers the same VRAM limitation — faster core, same 8 GB ceiling, same LLM limitations as the $300 card. The RTX 4060 Ti 16GB ($450-500) is the only 40 series card under $600 that makes sense for LLMs. Sixteen gigabytes runs 7-8B at Q8_0 (~9 GB, near-lossless) and 14B at Q4_K_M (~9 GB) with comfortable context. The trade-off: bandwidth is only 288 GB/s, meaning token generation is about 20% slower than the RTX 3060 12GB (360 GB/s). You get more VRAM for larger models but slower generation. For LLM inference where model capacity matters more than speed, the 16 GB card is the right choice in the 4060 family. If you can find it used at $350-400, it becomes more compelling.

# RTX 4060 Ti 16GB: 14B models at Q4 (~9 GB)
ollama run qwen2.5:14b          # ~20 tok/s

# RTX 4060 8GB: 7-8B models at Q4 (~5 GB)
ollama run llama3.1:8b         # ~18 tok/s

# Note: RTX 3060 12GB is faster (360 GB/s)
# for same models due to wider memory bus

RTX 4070, 4070 Super, 4070 Ti, 4070 Ti Super

The RTX 4070 (12 GB, 504 GB/s, $550 new) fixes the bandwidth problem. The 192-bit bus with 21 Gbps GDDR6X delivers 504 GB/s — nearly double the 4060 Ti's 288 GB/s. Twelve gigabytes runs 7-8B at Q8_0 (~9 GB) and 14B at Q4_K_M (~9 GB) with 8K context. The RTX 4070 Super (12 GB, 504 GB/s) is a minor core upgrade with the same memory subsystem — identical LLM performance. The RTX 4070 Ti (12 GB, 504 GB/s) further increases core count but again uses the same memory — identical LLM performance to the base 4070. For inference, the 4070 and 4070 Ti are equivalent. The RTX 4070 Ti Super (16 GB, 672 GB/s, $800) is the meaningful upgrade. Sixteen gigabytes with 672 GB/s bandwidth makes it the best 40 series card for 14B models: Qwen 2.5 14B at Q5_K_M or Q8_0 with generous context at 30-40 tok/s. It can also attempt Mistral Small 22B at Q4 (~13 GB) with tight context. The 4070 Ti Super is the card to get if you want new 40 series with warranty and plan to run 14B models as your daily driver. However, a used RTX 3090 at the same $800 price gives you 24 GB VRAM (running 32B models) with 936 GB/s bandwidth — a dramatically better LLM card. The 4070 Ti Super only makes sense if buying used is unacceptable.

RTX 4080 (16 GB) and RTX 4090 (24 GB): The Flagships

The RTX 4080 (16 GB, 717 GB/s) was the odd card of the 40 series: excellent bandwidth from a 256-bit bus, but limited to 16 GB in a price bracket ($1000+) where 24 GB was expected. For LLMs, it runs 14B models at Q8_0 at high speed, and 20-22B at aggressive quantization. But for the price (even used), it makes little sense: a used RTX 3090 24GB costs less and runs larger models. The RTX 4090 (24 GB, 1008 GB/s, 384-bit bus) is the 40 series crown jewel. Twenty-four gigabytes runs 27-32B models at Q4_K_M (~17-20 GB) at 35-50 tok/s — fast enough that responses feel nearly instant. It is the speed king for the 7-32B model range. The 4090's 24 GB ceiling means 70B at Q4 (~40 GB) does not fit — the RTX 5090 (32 GB) partially addresses this. For two years, the 4090 defined the best possible single-card local LLM experience. In mid-2026, it remains excellent, though the 5090 now surpasses it. Used RTX 4090s ($1500-1700) offer strong value versus the 5090 at $2000. The 4090 is 40% slower than the 5090 for the same model, but it is still fast enough that most users would not notice the difference outside of agent workflows generating 10K+ tokens.

RTX 40 Series: Which Card for Which Model?

RTX 4060 8GB: 7-8B at Q4_K_M (~5 GB), 4-8K context. Does not run 14B practically. RTX 4060 Ti 16GB: 7-8B at Q8_0 (~9 GB), 14B at Q4_K_M (~9 GB), 8K context. Can attempt 22B at Q3 with limited context. RTX 4070 12GB: 7-8B at Q8_0 (~9 GB), 14B at Q4_K_M (~9 GB), 8-16K context with faster generation than 4060 Ti. RTX 4070 Ti Super 16GB: Everything the 4070 runs, plus 22B at Q4 (~13 GB), and generation is 30-40% faster. RTX 4080 16GB: Same models as 4070 Ti Super, but 7% faster generation. Not worth the premium over the 4070 Ti Super for LLMs. RTX 4090 24GB: 27-32B at Q4_K_M (~17-20 GB) at 35-50 tok/s. The ceiling for single-card 40 series LLM inference. Budget: used RTX 3060 12GB (~$200). Mid-range value: used RTX 3090 (~$800). New with warranty: RTX 4070 Ti Super 16GB (~$800). Best: RTX 4090 (~$1500 used). Skip for LLMs: RTX 4060 8GB, RTX 4070 Ti 12GB (price premium for zero VRAM gain over 4070), RTX 4080 16GB (used 3090 is cheaper and better).

Used 40 Series: When to Buy and When to Skip

The used 40 series market is maturing. RTX 4060 8GB ($200-250 used): skip for LLMs — RTX 3060 12GB is cheaper and better. RTX 4060 Ti 16GB ($350-400 used): reasonable if 16 GB in a new-ish card matters to you, but the bandwidth is low. RTX 4070 12GB ($350-400 used): good mid-range option with solid bandwidth and CUDA features. RTX 4070 Ti Super 16GB ($600-700 used): compelling at this price — 16 GB with 672 GB/s is a strong combination. RTX 4080 16GB ($700-900 used): skip — used RTX 3090 ($700-900) gives 24 GB. RTX 4090 24GB ($1500-1700 used): the best 24 GB card, worth the premium over 3090 ($800) if speed is critical. The overarching theme: every 40 series card below the 4090 is outclassed in LLM value by the used RTX 3090 ($700-900, 24 GB, 936 GB/s). The 40 series' efficiency improvements and newer features matter more for gaming. For LLMs, the 30 series — specifically the 3090 — dominates value.

Frequently asked questions

Why is the RTX 3060 sometimes faster than the RTX 4060 Ti for LLMs?: Memory bandwidth. The RTX 3060 12GB uses a 192-bit memory bus achieving 360 GB/s. The RTX 4060 Ti uses a 128-bit bus achieving only 288 GB/s — 20% less. LLM token generation is bandwidth-bound: the GPU reads the full model weights from VRAM for each token. Narrower bus = fewer bytes per second = fewer tokens per second. NVIDIA prioritized power efficiency and die size over bus width for the 4060 series, which benefits gaming but hurts LLM inference.
Is the RTX 4090 still worth buying with the RTX 5090 available?: Yes, especially used. A used RTX 4090 at $1500-1700 offers 24 GB and 1008 GB/s — excellent for 7-32B models. The RTX 5090 at $2000 offers 32 GB and 1792 GB/s — better for everything. The 4090 makes sense if you want to save $300-500 and do not need the 5090's 32 GB for 70B models. Both are excellent; the 4090 is the value play, the 5090 is the performance play.
Should I buy an RTX 4080 for LLMs?: Probably not. At $700-900 used, a used RTX 3090 offers 24 GB (vs 16 GB) and higher bandwidth (936 vs 717 GB/s) for similar money. The 4080 is a great gaming card but a poor LLM value proposition due to its 16 GB VRAM ceiling at a 24 GB price point. If you find a 4080 at a steep discount ($500-600), it becomes more interesting.
Does the 40 series support NVFP4?: No. NVFP4 is exclusive to Blackwell architecture (RTX 50 series). The 40 series (Ada Lovelace) supports FP8 natively via tensor cores, which is a step down from NVFP4. For GGUF-based inference, this does not matter — GGUF quantization is integer-based and runs on the CUDA cores, not tensor cores.
What is the best 40 series card for LLMs under $600?: The RTX 4060 Ti 16GB ($450-500 new, $350-400 used) is the only 40 series card with more than 12 GB under $600. It runs 14B models at Q4 with comfortable context. For pure LLM value, a used RTX 3060 12GB ($200) or a stretch to a used RTX 3090 ($700-900) are better choices than any 40 series card in this price range.