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NVIDIA·Datacenter accelerator

NVIDIA L4 24GB: Specs & Local-AI Compatibility

Low-power 24GB inference card for efficient serving.

Specs

Memory
24 GB
Memory type
GDDR6
Bandwidth
300 GB/s
Approx FP16
30 TFLOPS
Architecture
Ada Lovelace
Process
TSMC 4N
Power
72 W
Launch
2023

Models this chip can run

Open models graded for a single NVIDIA L4 24GB, best fit first.

  • CodeLlama 13B
    CodeLlama · ~13B · 16K ctx · Llama Community License

    Fits at Q8_0 (~14GB) with ~7.1GB headroom — about 1 concurrent instance.

    Q8_0 · ~14GBRuns well
  • Gemma 3 12B
    Gemma 3 · ~12B · 128K ctx · Gemma Terms of Use

    Fits at Q8_0 (~13GB) with ~8.1GB headroom — about 1 concurrent instance.

    Q8_0 · ~13GBRuns well
  • Mistral Nemo 12B
    Mistral · ~12B · 128K ctx · Apache-2.0

    Fits at Q8_0 (~13GB) with ~8.1GB headroom — about 1 concurrent instance.

    Q8_0 · ~13GBRuns well
  • Gemma 2 9B
    Gemma · ~9B · 8K ctx · Gemma Terms of Use

    Fits at FP16 (~19GB) with ~2.1GB headroom — about 1 concurrent instance.

    FP16 · ~19GBRuns well
  • Llama 3.1 8B
    Llama · ~8B · 128K ctx · Llama Community License

    Fits at FP16 (~17GB) with ~4.1GB headroom — about 1 concurrent instance.

    FP16 · ~17GBRuns well
  • Qwen3 8B
    Qwen · ~8B · 128K ctx · Apache-2.0

    Fits at FP16 (~17GB) with ~4.1GB headroom — about 1 concurrent instance.

    FP16 · ~17GBRuns well
  • Granite 3 8B
    Granite · ~8B · 128K ctx · Apache-2.0

    Fits at FP16 (~17GB) with ~4.1GB headroom — about 1 concurrent instance.

    FP16 · ~17GBRuns well
  • DeepSeek-R1 Distill 8B
    DeepSeek · ~8B · 128K ctx · MIT

    Fits at FP16 (~17GB) with ~4.1GB headroom — about 1 concurrent instance.

    FP16 · ~17GBRuns well

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