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Local LLM under $1,000

Under $1,000 (€893 incl. VAT) localLLMrig picks Phi-4 14B at Q4 as the largest model that fully fits somewhere. Global prices (USD), EUR available. Prices and tokens/s are estimates without a source.

This page is $1,000. The catalog compares against about €893 incl. VAT, an FX estimate.

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Three setups

Phi-4 14B · Q4 · 8,192 ctx

Estimated memory

10.7 GBestimate

8.2 GB weights · 1.7 GB KV cache · 0.8 GB overhead

You didn't pick a model. Inside this budget, this is the largest model that fully fits somewhere.

  1. 01 · Fastest

    Budget PC with RTX 3060 12GB

    Entry point for 8B and, just barely, 14B Q4. The card is mostly second-hand.

    $996€890

    inside budget · used

    estimate

    tok/s

    19.0

    estimate

    needed

    10.7 GB

    full fit

    usable

    10.8 GB

    VRAM

    Why this one

    • The model fits entirely in VRAM or unified memory. No CPU offload.
    • It fits, with little room left. A longer context can push it over.
    • The indicative price is inside your budget.
    • Second-hand or a previous generation. The price moves around.
    • Highest estimated speed in this shortlist.

    Parts

    • GeForce RTX 3060 12GB
    • Ryzen 5 5600 or similar
    • 32 GB DDR4
    • 1 TB SSD, PSU around 550W

  2. 02 · A step up

    PC with RTX 5090 32GB

    Highest bandwidth in a single card. 32 GB is plenty for 32B, still too tight for 70B Q4.

    $5,027€4,490

    over budget

    estimate

    tok/s

    80

    estimate

    needed

    10.7 GB

    full fit

    usable

    30.8 GB

    VRAM

    Why this one

    • The model fits entirely in VRAM or unified memory. No CPU offload.
    • Memory left for a longer context or a heavier quantisation.
    • Above your budget. Nothing fully fit inside the amount, or this is a faster step above it.
    • High memory bandwidth, so a higher tokens-per-second estimate.

    Parts

    • GeForce RTX 5090 32GB
    • Ryzen 7 9700X or similar
    • 96 GB DDR5
    • 1200W PSU, roomy case

  3. 03 · A step up

    Dual RTX 4090, 48 GB

    Same memory as two 3090s, higher bandwidth, a lot more money.

    $6,146€5,490

    over budget

    estimate

    tok/s

    73

    estimate

    needed

    10.7 GB

    full fit

    usable

    45.6 GB

    VRAM

    Why this one

    • The model fits entirely in VRAM or unified memory. No CPU offload.
    • Memory left for a longer context or a heavier quantisation.
    • Above your budget. Nothing fully fit inside the amount, or this is a faster step above it.
    • Two GPUs. Expect a heavier PSU and a llama.cpp split. Bandwidth does not fully double.
    • High memory bandwidth, so a higher tokens-per-second estimate.

    Parts

    • 2× GeForce RTX 4090 24GB
    • Ryzen 9 7950X or similar
    • 128 GB DDR5
    • 1600W PSU

Tokens per second are estimated from memory bandwidth, not from a measured benchmark. Global prices (USD), EUR available. EUR includes VAT. USD is an FX estimate. No shop source. Run llama-bench yourself before you buy.

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End of results

Common questions

What is the largest model that fully fits under $1,000?
In this dataset that is Phi-4 14B at Q4, with an estimated memory need of 10.7 GB at 8,192 tokens. That is an estimate. sourceUrl stays null.
Is a 70B model always included?
No. Llama 70B Q4 needs about 40 GB. At the lower amounts it does not fully fit. The page then shows a smaller model that does, or a fit above the budget when nothing inside it does.
Are the prices shop prices?
No. Every amount is indicative as of 14 October 2026 and has no shop source.
Local LLM under $1,000 · localLLMrig