TL;DR: Five of the six desktop RTX 50-series cards cap at 16GB or less, so VRAM — not the Blackwell badge — decides which model you can load. The RTX 5060 Ti 16GB is the cheapest path to 16GB; the RTX 5090 is the only card that breaks the 16GB ceiling. Everything between them is a bandwidth upgrade sold at a GDDR7-shortage premium.

	RTX 5060 Ti 16GB	RTX 5090 32GB	Used RTX 3090 24GB
Best for	Cheapest 16GB on-ramp	Only card past 16GB	Most VRAM per dollar
Street price (Jun 2026)	~$430–$480	$3,000+	~$1,050–$1,240
The catch	448 GB/s = slow on big models	4× the price for 2× the VRAM	No warranty, 350W heat

Honest take: For local LLMs specifically, only two 50-series cards are clean buys — the 5060 Ti 16GB at the bottom and the 5090 at the top. The 5070 / 5070 Ti / 5080 middle is squeezed by the memory shortage, and a used RTX 3090 gives you 24GB for less than a street 5070 Ti.

The one rule that orders the whole lineup

Local LLM inference is two different jobs, and they’re bound by two different specs.

Whether a model runs at all is set by VRAM. All of a model’s weights must sit in GPU memory at once. A 14B model at Q4_K_M needs roughly 9GB plus a couple gigabytes for the KV cache; a 30B-class model needs 18–22GB. Overflow even slightly and the runtime offloads layers to system RAM over PCIe, where tok/s collapses to single digits — often 1–4 tok/s, slower than you read.

How fast it runs is set by memory bandwidth. Single-stream generation is almost purely memory-bandwidth-bound, and the math is close to linear:

theoretical max tok/s ≈ memory bandwidth ÷ model weight size (GB)

That’s why the 50-series sorts cleanly into capacity tiers, and bandwidth only matters within a tier. Here’s the full desktop lineup as it actually exists in mid-2026:

GPU	VRAM	Bandwidth	Bus	MSRP	Street (Jun 2026)
RTX 5060	8GB GDDR7	448 GB/s	128-bit	$299	~$300
RTX 5060 Ti 16GB	16GB GDDR7	448 GB/s	128-bit	$429	~$430–$480
RTX 5070	12GB GDDR7	672 GB/s	192-bit	$549	$619–$659
RTX 5070 Ti	16GB GDDR7	896 GB/s	256-bit	$749	$900–$1,250
RTX 5080	16GB GDDR7	960 GB/s	256-bit	$999	~$1,360
RTX 5090	32GB GDDR7	1,792 GB/s	512-bit	$1,999	$3,000+

Two things jump out. The capacity ladder barely moves — 8, 12, 16, 16, 16, then a leap to 32. And the GDDR7 shortage has shoved street prices well above MSRP for everything from the 5070 Ti up; the 5070 Ti has spent much of 2026 selling between $900 and $1,250, and the 5080 sits near $1,360. The price ladder no longer tracks the performance ladder.

RTX 5060 8GB — the 7B-and-stop card

At 448 GB/s and ~$300, the RTX 5060 runs 7B–8B models well and nothing larger. Real Ollama numbers at Q4_K_M: Llama 3.1 8B around 30 tok/s, Mistral 7B ~33, Qwen2.5 7B ~35. That’s comfortably faster than reading speed (~7–10 tok/s), so chat and short code completions feel instant.

Best model: Qwen3 8B or Llama 3.1 8B at Q4_K_M. Both leave just enough headroom for a 4K–8K context window.

The problem is the 8GB wall. A 13B model overflows, FLUX.1 image generation won’t fit, and longer contexts push you into CPU offload. The 5060 isn’t a slow GPU — it shares the exact same 448 GB/s memory config as the 5060 Ti — it just runs out of room the week you outgrow 7B. Buy it for casual chat; skip it if you’re serious about local AI. Full breakdown in our RTX 5060 8GB guide.

RTX 5060 Ti 16GB — the value anchor of the lineup

Same 448 GB/s as the 5060, double the VRAM, ~$430. That extra 8GB is the whole point: you’re buying capacity, not speed. Our live Ollama 0.23.2 benchmark on a 5060 Ti 16GB measured Mistral 7B at 90.17 tok/s, DeepSeek-Coder 6.7B at 101.44 tok/s, and Llama2 13B at 53.44 tok/s — all at ~89% of the theoretical bandwidth-bound ceiling, exactly what the formula predicts.

Best model: Qwen3 14B Q4_K_M for the quality/speed balance, or an 8B at Q8 if you’d rather trade size for precision. A 13B model fits with real context headroom — the thing the 5060 can’t do.

This is the cheapest 16GB card NVIDIA sells, which makes it the default recommendation for anyone who wants to run mid-size models without a four-figure budget. Its only weakness is the modest 448 GB/s: on the same model it’s roughly half the speed of a 5070 Ti. You’re trading tok/s for dollars, and at $430 that’s a fair trade. Detailed numbers in the RTX 5060 Ti 16GB vs 8GB comparison.

RTX 5070 12GB — more bandwidth, wrong amount of VRAM

The RTX 5070 is the lineup’s most awkward card for AI. Its 672 GB/s is 50% more bandwidth than the 5060 Ti, so it’s genuinely faster: Qwen3 7B Q4 hits ~59 tok/s and Qwen3 14B Q4 at 16K context runs 40.6 tok/s. But 12GB sits below the cheaper 5060 Ti’s 16GB.

Best model: Qwen3 14B Q4_K_M — but watch context. At 16K context the 14B already fills the card; push to 32K and it overflows to system RAM, dropping from 40+ tok/s to 5–8. The 16GB 5060 Ti has 4GB of headroom there and never falls off the cliff.

So you pay $619–$659 (above its $549 MSRP) for more speed on a smaller set of models. Unless you specifically value bandwidth on 7B–14B work and never touch long context, the 5060 Ti 16GB is the smarter buy at lower cost. We made this exact case in RTX 5070 vs RTX 5060 Ti.

RTX 5070 Ti & 5080 16GB — the squeezed middle

These two share a profile: 16GB VRAM, 256-bit bus, near-1 TB/s bandwidth (896 GB/s on the 5070 Ti, 960 on the 5080). They run the same models as the 5060 Ti 16GB but roughly twice as fast, since bandwidth doubled. Estimating from that 2× scaling, expect 14B Q4 in the ~75–95 tok/s range and 7B Q4 well past 120 — the exact figure depends on runtime, quant, and context, so treat these as bandwidth-derived estimates rather than a single measured number.

Best model: Qwen3 14B Q4_K_M at high speed, or a 30B-class MoE such as Qwen3 30B-A3B at a tight IQ3 quant that squeezes into 16GB. The MoE only activates ~3B parameters per token, so when it fits, throughput is excellent.

The trouble is price. The 5080 costs about 39% more than the 5070 Ti for roughly 17% more performance, and both sell far above MSRP on the GDDR7 crunch. At $900–$1,360 street, you’re inside used-RTX-3090 territory — and the 3090 brings 24GB. For pure gaming the 5080 wins; for local LLMs, paying a 16GB card a 24GB-card price is a hard sell.

RTX 5090 32GB — the only card that changes the math

The RTX 5090 is the one 50-series card that breaks 16GB, and at 1,792 GB/s it has 77% more bandwidth than an RTX 4090. That combination is transformative for local AI. Measured Ollama numbers: Llama 3.2 8B Q4_K_M at 142 tok/s, Qwen 3.6 35B-A3B Q4 at 198 tok/s at 4K context, and Gemma 4 26B-A4B Q4_K_M at 241 tok/s — the MoE models fly because routing reads only the active experts.

Best model: Qwen 3.6 35B-A3B or Gemma 4 31B at Q4_K_M. Both fit natively in 32GB with full working context, and both are the strongest open-weight models a single consumer card can hold. A 30B dense model at Q4 also fits comfortably.

The one limit: 70B dense models still don’t fit at Q4 (they need ~40GB), so they spill to RAM or require Q3. And the price is brutal — $3,000+ street against a $1,999 MSRP. The 5090 is worth it only if you genuinely need 30B-class models locally and want them fast. If you do, nothing else in the consumer lineup competes.

The card NVIDIA doesn’t sell: used RTX 3090

No 50-series buying guide is honest without it. The used RTX 3090 — 24GB GDDR6X, 936 GB/s — sells for roughly $1,050–$1,240 in June 2026. That’s more VRAM than any 50-series card except the 5090, at less than a street 5070 Ti. It runs Qwen 3.6 35B-A3B at ~107 tok/s on Ollama (135 with a tuned llama.cpp config) — the 24GB model class the entire 16GB tier can’t touch. The downsides are real: no warranty, 350W of heat, and an older architecture with no FP4 support. But for VRAM-per-dollar on LLMs, it still beats most of the new stack. See our used RTX 3090 value analysis.

What to actually buy

• Casual chat, tight budget: RTX 5060 Ti 16GB. Cheapest 16GB, runs 14B comfortably. Skip the 8GB 5060 unless you’ll never go past 7B.
• Speed on 7B–14B, never long context: RTX 5070 Ti — but only if you find it near MSRP, which is rare in 2026.
• 30B-class models, fast, money no object: RTX 5090. The only card that does it natively.
• Most VRAM per dollar: used RTX 3090. The value pick for anyone who can live without a warranty.
• No GPU at all yet? Renting is cheaper to start. A cloud A100 or 4090 on RunPod runs ~$0.30–$0.80/hr — worth it until your usage clears the break-even on a $1,000+ card.

If your goal is coding specifically, the model matters as much as the card — see our sister site’s local coding model benchmarks on aicoderscope.com and the open-source setup walkthroughs on aifoss.dev. And for the full picture on whether to buy now or wait out the shortage, read NVIDIA skipping new consumer GPUs in 2026.

FAQ

Which RTX 50-series card is best for local LLMs? For most people, the RTX 5060 Ti 16GB — it’s the cheapest way to get 16GB of VRAM, which runs 14B models comfortably. If you need 30B-class models and have the budget, the RTX 5090 is the only 50-series card with enough VRAM (32GB) to run them natively.

Can the RTX 5090 run a 70B model? Not at Q4. A 70B model at Q4 needs about 40GB, more than the 5090’s 32GB, so weights spill to system RAM over PCIe and speed drops sharply. It runs 70B only at Q3 or smaller, or with offload. For 70B work you want multiple 24GB cards or a high-RAM Apple Silicon machine.

Why is the RTX 5070 12GB worse than the cheaper 5060 Ti 16GB for AI? The 5070 has more bandwidth (672 vs 448 GB/s) so it’s faster on models that fit, but its 12GB VRAM caps model size and long-context use below the 16GB 5060 Ti. For LLMs, capacity usually beats speed — you can’t run a model that doesn’t fit, no matter how fast the card is.

Is a used RTX 3090 still better value than a new 50-series card in 2026? For VRAM per dollar, yes. At ~$1,050–$1,240 it offers 24GB — more than every 50-series card except the 5090 — for less than a street-price 5070 Ti. The trade-offs are no warranty, higher power draw, and no FP4 support.

How many tokens per second do I actually need? Human reading speed is roughly 7–10 tok/s, so anything above ~15 tok/s feels real-time for chat. Agentic and coding workflows that call the model dozens of times per task benefit from higher throughput, which is where the 5090’s 140–240 tok/s on small-to-mid models pays off.

Sources

• GeForce RTX 50 series specifications — Wikipedia
• GeForce RTX 50 Series Graphics Cards — NVIDIA
• RTX 5090 specs: 32GB GDDR7, 1,792 GB/s — RunPod
• RTX 5090 local LLM benchmarks and context scaling — Hardware Corner
• RTX 5080 costs 39% more than 5070 Ti, runs 17% faster — TechTimes
• RTX 5070 Ti price tracker, June 2026 — BestValueGPU
• Used RTX 3090 price tracker, June 2026 — BestValueGPU
• GPU price tracking 2026 — Tom’s Hardware

Last updated June 30, 2026. Prices and specs change; verify current rates before purchasing. Tokens/sec figures vary with runtime, quantization, and context length — the RTX 5070 Ti / 5080 numbers are estimated from the bandwidth ratio against measured 5060 Ti and 5090 results.

Recommended Gear

• RTX 5060 Ti 16GB — cheapest 16GB card in the lineup; runs 14B models comfortably
• RTX 5090 — only 50-series card that runs 30B-class models natively (32GB)
• RTX 5060 — budget 7B–8B chat card; 8GB ceiling
• RTX 5070 — fastest 7B–14B option under 16GB, capped by 12GB VRAM
• Used RTX 3090 — 24GB at the best VRAM-per-dollar in 2026