microsoft/Phi-3-medium-4k-instruct
14B params · est. 8.4 GB Q4
NVIDIA L40S 48GB: likely fitNVIDIA A100 SXM4 80GB: likely fit
Head-to-head
NVIDIA L40S 48GB vs NVIDIA A100 SXM4 80GB
Dedicated comparison page for two real hardware profiles. This is built from your benchmark database, trust metadata, and buyer flow instead of generic spec-sheet comparisons.
Device profile
NVIDIA L40S 48GB
Compared here against NVIDIA A100 SXM4 80GB.
Curated Aggregate·2026-04-2948GB / $7.8k
Best LLM
175 tok/s
VRAM
48 GB
TDP
350 W
Rating
9.0
Device profile
NVIDIA A100 SXM4 80GB
Compared here against NVIDIA L40S 48GB.
Curated Aggregate·2025-05-0180GB / $15k
Best LLM
215 tok/s
VRAM
80 GB
TDP
400 W
Rating
9.0
Quick verdict
NVIDIA L40S 48GB scores 9.0 while NVIDIA A100 SXM4 80GB scores 9.0 on MyAIHardware's composite rating.
NVIDIA A100 SXM4 80GB wins VRAM capacity.
NVIDIA L40S 48GB is the lower-power path.
On shared workload evidence, Mistral 7B Q4 is benchmarked at 142 tok/s for NVIDIA L40S 48GB and 168 tok/s for NVIDIA A100 SXM4 80GB.
| Metric | NVIDIA L40S 48GB | NVIDIA A100 SXM4 80GB |
|---|---|---|
| MyAI rating | 9.0 | 9.0 |
| Best LLM | 175 tok/s | 215 tok/s |
| VRAM | 48 GB | 80 GB |
| TDP | 350 W | 400 W |
| MSRP | $7.8k | $15k |
| Workloads | 9 | 7 |
Shared benchmark rows
Mistral 7B Q4
Mistral 7B
NVIDIA L40S 48GB
142 tok/s
Q4_K_M / 48GB / 2024-06-18
NVIDIA A100 SXM4 80GB
168 tok/s
Q4_K_M / 80GB / 2024-04-15
Gemma 2 9B Q4
Gemma 2 9B
NVIDIA L40S 48GB
118 tok/s
Q4_K_M / 48GB / 2024-08-23
NVIDIA A100 SXM4 80GB
138 tok/s
Q4_K_M / 80GB / 2024-07-09
Qwen 2.5 14B Q4
Qwen 2.5 14B
NVIDIA L40S 48GB
92.0 tok/s
Q4_K_M / 48GB / 2024-11-15
NVIDIA A100 SXM4 80GB
108 tok/s
Q4_K_M / 80GB / 2024-10-30
Llama 3 70B Q4
Llama 3 70B Q4
NVIDIA L40S 48GB
22.0 tok/s
Q4_K_M / 48GB / 2024-08-07
NVIDIA A100 SXM4 80GB
48.0 tok/s
Q4_K_M / 80GB / 2024-08-28
External quality layer
Best open models likely to fit this class
This shortlist cross-references the external OpenEvals snapshot with an approximate Q4-class VRAM estimate. Use it to sanity-check whether the hardware you are comparing can host strong open models, not just benchmark toy workloads.
91.0
Qwen/Qwen2-72B
73B params · est. 43.6 GB Q4
NVIDIA L40S 48GB: likely fitNVIDIA A100 SXM4 80GB: likely fit
microsoft/Phi-3.5-mini-instruct
3.8B params · est. 2.3 GB Q4
NVIDIA L40S 48GB: likely fitNVIDIA A100 SXM4 80GB: likely fit
internlm/internlm2_5-7b-chat
7.7B params · est. 4.6 GB Q4
NVIDIA L40S 48GB: likely fitNVIDIA A100 SXM4 80GB: likely fit