Budget PC for Local AI, Programming & RDP – Is a 6GB GPU Enough? 💻

[Indianapolis]

Hey OneHackers!

I’m planning to build or buy a budget-friendly PC for:

• Running small AI models locally
• Programming and development
• RDP/remote desktop and virtual machines
• General multitasking

I’m not looking for a perfect or high-end setup—just the minimum specs that can do these tasks reasonably well. My budget is limited, and I’m also open to used components.

Would a 6GB NVIDIA GPU, such as an RTX 2060, be enough to start with local AI? Or should I save for an RTX 3060 12GB or another card?

What would you recommend for:

• CPU
• GPU and minimum VRAM
• RAM: 16GB or 32GB?
• Storage
• Power supply

Please share any affordable builds, used workstation options, or upgrade paths. Also, mention what kind of AI models your suggested setup could realistically run.

Thanks in advance!

[SRZ]

ᕙ(⇀‸↼‶)ᕗ 6 GB runs 7B, 12 GB runs 14B, and a 16 GB Tesla P100 costs $80 used — check your card, pick by memory per dollar, three used builds, deal alerts, buy once

A 6 GB RTX 2060 runs 7B models at 4-bit with a short memory. 12 GB is where 14B starts. A used 16 GB server card costs less than the 2060.

 🧮 FIT RULE   model size in billions × 0.6 GB = the 4-bit file, + 1–2 GB spare

   6 GB  ▓▓▓▓▓▓░░░░░░░░░░░░░░░░░░   7B at 4-bit            RTX 2060    $114–131
  12 GB  ▓▓▓▓▓▓▓▓▓▓▓▓░░░░░░░░░░░░   14B at 4-bit           RTX 3060    $194–295
  16 GB  ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓░░░░░░░░   14B roomy, 20B tight   Tesla P100  $77–80   ◀
  24 GB  ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓   30B at 4-bit           Tesla P40   $239–250

01 · Check your card

• localmodel.run — pick card + model → Yes / Tight / No, plus the ollama command.
• getlocalia.com — the 136 models that fit a 2060, and what 12 GB adds.
• willitrunai.com — 380 models ranked for 6 GB.
• modelfit.io — 3060 12 GB, 4060 8 GB, 4060 Ti 16 GB side by side.

Speed, measured by owners: llama.cpp scoreboard — RTX 3060 12 GB 75 words/s on a 7B · GTX 1660 6 GB 41 · Tesla P100 58 · Tesla P40 55. localscore.ai — RTX 3060: 52 words/s on Llama 3.1 8B, 26 on a 14B.

Card	Coding	Chat	Download
6 GB	Qwen2.5-Coder 7B	Gemma 3 4B · Qwen3 8B (tight)	4.7 · 3.3 · 5.2 GB
12 GB	Qwen2.5-Coder 14B · DeepSeek-Coder-V2 16B	Qwen3 14B · Gemma 3 12B	9.0 · 8.9 · 9.3 · 8.1 GB
16 GB	the 12 GB list with the full memory window	plus 20B-class at 4-bit	13 GB

On 6 GB: context 2–4K. Run ollama ps → 100% GPU = good. A CPU share = the model spilled into RAM.

02 · Pick the card by memory per dollar

• gpudojo.com — every card ranked by dollars per usable GB, used prices dated.
• secondhandsilicon.com · pcprice.watch — eBay sold prices, 7 countries.

Card	Memory	Used, Sep 2026	Runs
RTX 2060	6 GB	$114–131	7B at 4-bit
RTX 3060	12 GB	$194–295	14B at 4-bit, 7B full quality
Tesla P100	16 GB	$77–80	14B roomy, 30B tight
Tesla P40	24 GB	$239–250	30B at 4-bit

P100 and P40 are server cards: no fan, no monitor port. Add a $15 fan shroud. The monitor runs from the CPU’s graphics or the old card.

03 · Three used builds

Office tower + P100 — ex-office workstation (Xeon, 32 GB, big power supply) + Tesla P100. Runs 14B. Slot check: HP Z440 with the 700 W supply takes one 300 W card; Dell T5810 takes two 225 W cards on 685 W.

Ryzen + RTX 3060 12 GB — used B450 board, 6-core Ryzen, 32 GB DDR4, 1 TB NVMe, 650 W, RTX 3060. Runs 14B at 30 words/s, 7B at 75. The board takes the 16-core Ryzen 9 5950X later (ASUS support list).

The 2060 you named — same Ryzen base + RTX 2060 for $115–130. Runs 7B at 40–50 words/s. The 12 GB or 16 GB card drops into the same box later.

Where the towers are: Dell Refurbished · PC Server & Parts (T5820 chassis $135, ThinkStation P520 690 W $185) · Tech Supply Direct (16 → 32 GB ECC +$82) · Bargain Hardware · AfB · buerorechner24 (Precision 5810, 64 GB, 355 €) · Server Basket (HP Z440 ₹35,999).

Minimum per part: CPU any 6-core from the last six years · RAM 32 GB (16 boots; 32 holds the VMs and spilled layers) · SSD 1 TB NVMe · PSU 550 W for a 2060 or 3060 (NVIDIA’s own numbers), 650 W to buy once. Check the list in PCPartPicker, card length in fitmypc.net, wattage in Seasonic’s calculator.

04 · Let the deal come to you

• eBay saved search — every new “RTX 3060 12GB” listing pushed to your phone.
• PCPartPicker parametric alert — any 12 GB card under $200, one alert.
• r/buildapcsales on Telegram — every deal with the price, as posted.
• classifindr — Facebook Marketplace + Craigslist watch for a whole used PC under your number.

05 · Buy once

• AM4 board → Ryzen 2000 to 5000 on one socket (AMD’s grid). Intel: LGA1700 H610 takes 12th–14th gen; LGA1200 stops at 11th.
• 650 W today → a P40 or a 3090 next year with no new supply.
• Some cases take no card at all (0 mm). Check the case in sff.gg/db first.

Buy the 2060 today, you run 7B. Buy the P100 for less, you run 14B. Same box either way.

[Grace2077]

Your plan to start with a 6GB card makes sense for small local models, since it should handle 7B models at 4-bit for coding and chat if you keep the context short. For programming plus virtual machines, I would prioritize 32GB of system RAM over a faster CPU, because that headroom matters once a model spills out of VRAM. The RTX 3060 12GB looks like the better long-term buy if you can wait, since it opens up 14B models and gives you more room for longer prompts. A used workstation with a 650W power supply also fits your upgrade path well, as it leaves room for a larger card later without replacing the whole build. Thanks for laying out the budget and use cases so clearly, as that makes it much easier to judge what is enough rather than chasing a perfect setup.

[ai_daily_tools]

For the mix you described, I would treat 6GB as a solid starting point rather than a long-term answer. It should handle smaller local models and normal programming work fine, but the moment you add VMs and RDP on top, RAM matters just as much as the GPU. That is why the 32GB suggestion stood out to me, since running out of memory while multitasking is far more annoying than a slightly slower model. If I were building on a budget, I would start with the 6GB card, keep the upgrade path open, and only spend more once I actually hit a limit in daily use.