NVIDIA L40S 48GB: Specs & Local-AI Compatibility
48GB datacenter card — cost-effective mid-scale inference.
Specs
- Memory
- 48 GB
- Memory type
- GDDR6 ECC
- Bandwidth
- 864 GB/s
- Approx FP16
- 362 TFLOPS
- Architecture
- Ada Lovelace
- Process
- TSMC 4N
- Power
- 350 W
- Launch
- 2023
Models this chip can run
Open models graded for a single NVIDIA L40S 48GB, best fit first.
- Mixtral 8x7B (MoE)Mistral · ~47B · 32K ctx · Apache-2.0
Fits at Q4_K_M (~28GB) with ~14.2GB headroom — about 1 concurrent instance.
Q4_K_M · ~28GBRuns well - CodeLlama 34BCodeLlama · ~34B · 16K ctx · Llama Community License
Fits at Q8_0 (~37GB) with ~5.2GB headroom — about 1 concurrent instance.
Q8_0 · ~37GBRuns well - Qwen2.5 32BQwen · ~32B · 128K ctx · Apache-2.0
Fits at Q8_0 (~34GB) with ~8.2GB headroom — about 1 concurrent instance.
Q8_0 · ~34GBRuns well - Qwen3 32BQwen · ~32B · 128K ctx · Apache-2.0
Fits at Q8_0 (~34GB) with ~8.2GB headroom — about 1 concurrent instance.
Q8_0 · ~34GBRuns well - DeepSeek-R1 Distill 32BDeepSeek · ~32B · 128K ctx · MIT
Fits at Q8_0 (~34GB) with ~8.2GB headroom — about 1 concurrent instance.
Q8_0 · ~34GBRuns well - Qwen2.5-Coder 32BQwen · ~32B · 128K ctx · Apache-2.0
Fits at Q8_0 (~34GB) with ~8.2GB headroom — about 1 concurrent instance.
Q8_0 · ~34GBRuns well - Gemma 2 27BGemma · ~27B · 8K ctx · Gemma Terms of Use
Fits at Q8_0 (~29GB) with ~13.2GB headroom — about 1 concurrent instance.
Q8_0 · ~29GBRuns well - Gemma 3 27BGemma 3 · ~27B · 128K ctx · Gemma Terms of Use
Fits at Q8_0 (~29GB) with ~13.2GB headroom — about 1 concurrent instance.
Q8_0 · ~29GBRuns well
Devices built on this chip
Build a private AI Business OS on NVIDIA L40S 48GB
Run your own AI agents on hardware you control — private by design, no per-seat data leaving your premises. BrainOutput helps you pick the right machine and turn it into a working AI Business OS.
Explore the AI Business OS