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NVIDIA·Datacenter accelerator

NVIDIA A100 40GB: Specs & Local-AI Compatibility

40GB HBM datacenter accelerator for training and serving.

Specs

Memory
40 GB
Memory type
HBM2e
Bandwidth
1,555 GB/s
Approx FP16
312 TFLOPS
Architecture
Ampere
Process
TSMC 7nm
Power
400 W
Launch
2020

Models this chip can run

Open models graded for a single NVIDIA A100 40GB, best fit first.

  • Mixtral 8x7B (MoE)
    Mistral · ~47B · 32K ctx · Apache-2.0

    Fits at Q4_K_M (~28GB) with ~7.2GB headroom — about 1 concurrent instance.

    Q4_K_M · ~28GBRuns well
  • CodeLlama 34B
    CodeLlama · ~34B · 16K ctx · Llama Community License

    Fits at Q4_K_M (~21GB) with ~14.2GB headroom — about 1 concurrent instance.

    Q4_K_M · ~21GBRuns well
  • Qwen2.5 32B
    Qwen · ~32B · 128K ctx · Apache-2.0

    Fits at Q8_0 (~34GB) with ~1.2GB headroom — about 1 concurrent instance.

    Q8_0 · ~34GBRuns well
  • Qwen3 32B
    Qwen · ~32B · 128K ctx · Apache-2.0

    Fits at Q8_0 (~34GB) with ~1.2GB headroom — about 1 concurrent instance.

    Q8_0 · ~34GBRuns well
  • DeepSeek-R1 Distill 32B
    DeepSeek · ~32B · 128K ctx · MIT

    Fits at Q8_0 (~34GB) with ~1.2GB headroom — about 1 concurrent instance.

    Q8_0 · ~34GBRuns well
  • Qwen2.5-Coder 32B
    Qwen · ~32B · 128K ctx · Apache-2.0

    Fits at Q8_0 (~34GB) with ~1.2GB headroom — about 1 concurrent instance.

    Q8_0 · ~34GBRuns well
  • Gemma 2 27B
    Gemma · ~27B · 8K ctx · Gemma Terms of Use

    Fits at Q8_0 (~29GB) with ~6.2GB headroom — about 1 concurrent instance.

    Q8_0 · ~29GBRuns well
  • Gemma 3 27B
    Gemma 3 · ~27B · 128K ctx · Gemma Terms of Use

    Fits at Q8_0 (~29GB) with ~6.2GB headroom — about 1 concurrent instance.

    Q8_0 · ~29GBRuns well

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