NVIDIA A100 80GB SXM4 vs NVIDIA L40S, AI & Machine Learning Comparison

NVIDIA A100 80GB SXM4
NVIDIA A100 80GB SXM4
vs
NVIDIA L40S
NVIDIA L40S

NVIDIA A100 80GB SXM4 wins 85 of 154 benchmarks, averaging 3.1% faster.

Both cards were measured first-party on our bench, same suite, same test rig.

What the numbers say

The gap is widest in MusicGen Small, where NVIDIA L40S leads by 228% (0.74 vs 2.43 x realtime); the closest fight is Phi-3.5-mini (0% apart); VRAM decides part of this one: NVIDIA A100 80GB SXM4 runs 155 of our 12 AI workloads while the other card runs 152, models that don't fit score zero.

Benchmark results head-to-head

BenchmarkNVIDIA A100 80GB SXM4NVIDIA L40SDifference
Qwen3 4B tok/s197212.05-7%
Llama 3.1 8B tok/s162.57135.51+20%
Qwen2.5-Coder 14B tok/s89.4574.6+20%
Qwen3 32B tok/s45.5334.44+32%
Llama 3.3 70B tok/s24.416.49+48%
Stable Diffusion XL images/min16.3617.02-4%
Z-Image Turbo images/min9.9758.325+20%
FLUX.1 dev images/min4.2643.836+11%
FLUX.1 Kontext dev images/min1.9931.693+18%
Qwen-Image-Edit images/min1.641.06+55%
LTX-Video (distilled) frames/s8.958.01+12%
Wan 2.2 5B (720p) frames/s0.660.49+35%
DeepSeek-R1 Distill Llama 8B tok/s159.37135.55+18%
DeepSeek-R1 Distill 1.5B tok/s327.66426.38-23%
DeepSeek-R1 Distill 14B tok/s8774.6+17%
DeepSeek-R1 Distill 7B tok/s162.96143.97+13%
Gemma 3 12B tok/s91.4580.92+13%
Gemma 3 4B tok/s176.94198.87-11%
Gemma 4 12B tok/s92.4380.82+14%
Llama 3.2 1B tok/s525.32618.87-15%
Llama 3.2 3B tok/s264.25270.85-2%
Mistral 7B v0.3 tok/s171.92144.74+19%
Mistral Small 24B tok/s61.3848.43+27%
Phi-4 14B tok/s95.2274.98+27%
Phi-4 Mini 3.8B tok/s239.17228.93+4%
Qwen2.5-Coder 7B tok/s164.6143.93+14%
Qwen3 0.6B tok/s428.39655.75-35%
Qwen3 1.7B tok/s343.58405.52-15%
Qwen3 14B tok/s90.6475.12+21%
Qwen3 30B A3B tok/s177.32213.66-17%
Qwen3 8B tok/s149.96130.27+15%
SmolLM3 3B tok/s249.76272.88-8%
TRELLIS Image-to-3D assets/hour488.7776.1-37%
Codestral 22B tok/s63.2650.06+26%
DeepSeek-R1 Distill 32B tok/s43.1134.6+25%
Devstral Small 24B tok/s61.6348.43+27%
Dolphin 2.9.1 Yi 1.5 34B tok/s43.4733.08+31%
Dolphin Mistral 24B Venice tok/s62.7248.43+30%
Dolphin X1 8B tok/s158.62135.48+17%
Dolphin 3.0 Llama 3.1 8B tok/s158.63135.55+17%
Dolphin 3.0 R1 Mistral 24B tok/s61.1748.4+26%
Gemma 3 27B tok/s48.4338.48+26%
Qwen2.5-Coder 32B tok/s43.3634.59+25%
Qwen3-Coder 30B A3B tok/s182.26219.04-17%
QwQ 32B tok/s43.2734.59+25%
StarCoder2 15B tok/s79.2266.88+18%
FLUX.1 Schnell images/min28.3926.24+8%
Z-Image Turbo (1024px) images/min18.6518.2+2%
BiRefNet images/min916.67863.81+6%
Depth Anything V2 Large images/min876.29959.33-9%
Depth Anything V2 Small images/min925.15970.61-5%
SAM ViT-Base images/min744.79998.79-25%
SAM ViT-Huge images/min145.7238.08-39%
Swin2SR 4x Upscaler images/min28.7234.14-16%
Florence-2 Base images/min126.4184.2-31%
Florence-2 Large images/min70.94106.54-33%
Qwen2.5 1.5B LoRA train tok/s8252.812120.1-32%
Qwen2.5 7B LoRA train tok/s3900.63736+4%
SmolLM2 1.7B LoRA train tok/s9750.812052.1-19%
TinyLlama 1.1B LoRA train tok/s9553.316408.1-42%
Stable Video Diffusion XT clips/min1.5361.166+32%
Wan 2.2 TI2V-5B (image to video) clips/min2.1561.606+34%
CogVideoX-5B I2V clips/min0.4680.383+22%
Qwen2.5 1.5B served serve tok/s4564.74686.8-3%
Qwen2.5 7B served serve tok/s2187.21406.8+55%
SmolLM2 1.7B served serve tok/s4351.43525.9+23%
TinyLlama 1.1B served serve tok/s5701.56278.4-9%
DeepSeek-R1-Distill-Llama-70B tok/s22.9916.49+39%
DeepSeek-R1-Distill-Qwen-32B-abliterated tok/s43.4834.43+26%
Kokoro TTS 82M x realtime110.17243.99-55%
Llama-3.3-70B-Instruct-abliterated tok/s22.9216.49+39%
Meta-Llama-3.1-70B tok/s22.9216.49+39%
MusicGen Small x realtime0.742.43-70%
Nemotron-3-Nano-30B-A3B tok/s204.06190.96+7%
Whisper large-v3 x realtime73.83193.2-62%
Qwen2.5-Coder 32B (Q3_K_M) tok/s31.9941.06-22%
AI21-Jamba-Reasoning-3B tok/s239.23258.41-7%
Olmo-3.1-32B-Think tok/s46.4934.11+36%
Codestral 22B (Q3_K_M) tok/s49.5259.53-17%
Dolphin-Mistral-24B-Venice-Edition tok/s65.7748.43+36%
DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored tok/s164.46134.78+22%
DeepSeek-Coder-V2-Lite tok/s213.91257.64-17%
DeepSeek-R1-0528-Qwen3-8B tok/s152.76130.23+17%
DeepSeek-R1 Distill 14B (Q3_K_M) tok/s67.1385.85-22%
dolphin-2.9-llama3-8b tok/s164.09134.94+22%
Dolphin X1 Trinity Nano 6B tok/s158.41246.45-36%
EVA-Qwen2.5-14B-v0.2 tok/s90.3574.63+21%
gemma-2-2b-it-abliterated tok/s244.41278.14-12%
gemma-2-2b tok/s244.52278.1-12%
gemma-2-9b tok/s108.6888.87+22%
Gemma 3 12B (Q3_K_M) tok/s71.8893.05-23%
gemma-3-1b tok/s324.08426.49-24%
gemma-3-270m tok/s617.58822.52-25%
GLM-4.7-Flash-REAP-23B-A3B tok/s112.75146.51-23%
GLM-4.7-Flash tok/s124.08157.89-21%
Josiefied-Qwen3-8B-abliterated-v1 tok/s152.29130.25+17%
gpt-oss-20b tok/s212.63233.82-9%
Hermes-3-Llama-3.2-3B tok/s269.13265.87+1%
Hermes-4-70B tok/s24.4716.45+49%
SmolLM3-3B tok/s254.6272.96-7%
Qwen3-Coder-Next-abliterated tok/s119.560n/a
KAT-Coder-V2.5-Dev tok/s146.38173.06-15%
L3-8B-Stheno-v3.2 tok/s164.51135.53+21%
Laguna-XS-2.1 tok/s00n/a
LFM2.5-1.2B tok/s576.95661.54-13%
LFM2.5-8B-A1B tok/s369.01394.48-6%
Llama-2-7B tok/s180.09150.35+20%
Llama-3.2-3B-Instruct-uncensored tok/s269.13271.01-1%
Meta-Llama-3.1-8B tok/s164.24135.46+21%
Phi-4-mini tok/s243.38229.28+6%
Mistral-7B-Instruct-v0.1 tok/s173.87144.82+20%
Mistral-7B-Instruct-v0.2 tok/s173.8144.82+20%
Mistral-7B-Instruct-v0.3 tok/s173.27144.68+20%
Mistral-Nemo-Instruct-2407 tok/s111.0789.72+24%
Mistral Small 24B (Q3_K_M) tok/s46.6358.21-20%
Nanbeige4.2-3B tok/s00n/a
NemoMix-Unleashed-12B tok/s110.9988.85+25%
Hermes-4-14B tok/s94.4875.1+26%
Ornith-1.0-35B tok/s138.8157.39-12%
Ornith-1.0-9B tok/s134.67114.57+18%
phi-2 tok/s235.55283.26-17%
Phi-3.5-mini tok/s229.46229.060%
Phi-4 14B (Q3_K_M) tok/s82.6889.18-7%
Qwen-AgentWorld-35B-A3B tok/s139.69156.98-11%
Qwen3-0.6B tok/s432.66656.26-34%
Qwen3-1.7B tok/s350.4405.3-14%
Qwen3-14B tok/s94.3575.01+26%
Qwen3-30B-A3B tok/s178.14214.05-17%
Qwen3-4B-Instruct-2507 tok/s199.39210.24-5%
Qwen3-8B tok/s152.8130.28+17%
Qwen3-Coder-Next tok/s118.620n/a
Qwen3-Next-80B-A3B-Thinking tok/s118.930n/a
Qwen1.5-0.5B tok/s540.32774.78-30%
Qwen2-1.5B tok/s333.79416.57-20%
Qwen2.5-0.5B tok/s571.49738.06-23%
Qwen2.5-1.5B tok/s335.29427.23-22%
Uncensored tok/s89.4374.31+20%
Qwen2.5-14B tok/s90.4674.62+21%
Qwen2.5-32B tok/s45.634.59+32%
Qwen2.5-3B tok/s248.47270.04-8%
Qwen2.5-7B tok/s166.92143.94+16%
Qwen2.5-Coder-0.5B tok/s562.59715.81-21%
Qwen2.5-Coder-1.5B tok/s333.87427.12-22%
Qwen2.5-Coder-14B-Instruct-abliterated tok/s90.2874.63+21%
Qwen2.5-Coder-3B tok/s248.7269.9-8%
Qwen2.5-Coder-7B-Instruct-abliterated tok/s166.84142.97+17%
Qwen3 30B A3B (Q3_K_M) tok/s146.72224.95-35%
Qwen3-4B-Instruct-2507 tok/s199.65212.05-6%
Qwen3-4B-Thinking-2507 tok/s199.71211.88-6%
Qwen3-Coder-Next tok/s120.710n/a
Qwen3-Next-80B-A3B-Thinking tok/s120.980n/a
Qwen3-Next-80B-A3B tok/s117.440n/a
SmolLM2-135M tok/s554.44916.56-40%
Cydonia-24B-v4.3 tok/s65.8248.43+36%

Whole-job comparison

How long each card takes to finish a complete pipeline, not just one model. NVIDIA A100 80GB SXM4 is faster on 14 of 17; NVIDIA L40S on 3.

WorkflowNVIDIA A100 80GB SXM4NVIDIA L40SDifferenceCost per run
50-image depth pass5 s6 sNVIDIA A100 80GB SXM4 1.22x faster$0.002 vs $0.001
30-minute podcast pass67 s75 sNVIDIA A100 80GB SXM4 1.12x faster$0.026 vs $0.017
500-image masking run3.5 min2.2 minNVIDIA L40S 1.62x faster$0.081 vs $0.028
24-frame storyboard3.7 min4.1 minNVIDIA A100 80GB SXM4 1.10x faster$0.085 vs $0.053
20-asset 3D game kit4 min2.9 minNVIDIA L40S 1.36x faster$0.092 vs $0.039
60-second AI short film4.7 min4.9 minNVIDIA A100 80GB SXM4 1.06x faster$0.108 vs $0.065
60-second AI short film, narrated4.9 min5.1 minNVIDIA A100 80GB SXM4 1.03x faster$0.114 vs $0.067
6-panel comic page6 min6.5 minNVIDIA A100 80GB SXM4 1.09x faster$0.139 vs $0.086
200-product catalogue cutout7.3 min6.2 minNVIDIA L40S 1.17x faster$0.169 vs $0.082
Character sheet, 12 poses7.6 min8.4 minNVIDIA A100 80GB SXM4 1.11x faster$0.175 vs $0.110
Full codebase review11.2 min13.5 minNVIDIA A100 80GB SXM4 1.20x faster$0.259 vs $0.177
10 short social clips15.1 min19.1 minNVIDIA A100 80GB SXM4 1.26x faster$0.350 vs $0.251
20 long-form articles19.1 min28.5 minNVIDIA A100 80GB SXM4 1.49x faster$0.443 vs $0.375
40-product photo shoot23.5 min26.7 minNVIDIA A100 80GB SXM4 1.14x faster$0.543 vs $0.352
40-product shoot, start to finish25 min28 minNVIDIA A100 80GB SXM4 1.12x faster$0.579 vs $0.369
100-photo restoration batch50.8 min59.6 minNVIDIA A100 80GB SXM4 1.17x faster$1.177 vs $0.784
100-photo restore and enlarge54.3 min62.5 minNVIDIA A100 80GB SXM4 1.15x faster$1.258 vs $0.823

Renting by the hour, NVIDIA L40S finishes 17 of 17 cheaper. The quicker card is not automatically the cheaper way to get the work done.

Cost to rent

CardPer hour
NVIDIA A100 80GB SXM4$1.390
NVIDIA L40S$0.790

NVIDIA L40S is 1.76x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.

Specifications compared

NVIDIA A100 80GB SXM4NVIDIA L40S
VRAM80GB48GB
ArchitectureAmpereAda Lovelace
Memory bandwidth2039 GB/s864 GB/s
Boost clock1,410 MHz2,520 MHz
TDP400 W350 W
Launch MSRP$17,000$7,500
Release2020-11-162023-08-08

FAQ

Which is better for ai & machine learning: NVIDIA A100 80GB SXM4 or NVIDIA L40S?
NVIDIA A100 80GB SXM4 performs better for ai & machine learning, winning 85 of 154 benchmarks in our suite with an average 3.1% advantage.
What are the main hardware differences between NVIDIA A100 80GB SXM4 and NVIDIA L40S?
NVIDIA A100 80GB SXM4 has 80GB VRAM and a 400W TDP, while NVIDIA L40S has 48GB VRAM and a 350W TDP.
Does VRAM matter more than speed between NVIDIA A100 80GB SXM4 and NVIDIA L40S?
For AI, yes, NVIDIA A100 80GB SXM4 fits 6 more of our 12 workloads than NVIDIA L40S. A model that exceeds VRAM doesn't run slower, it doesn't run at all, so the card that fits the model wins that workload outright.
Where is the biggest performance difference between NVIDIA A100 80GB SXM4 and NVIDIA L40S?
MusicGen Small: NVIDIA L40S leads by roughly 169% (0.74 vs 2.43 x realtime) in our testing.

NVIDIA A100 80GB SXM4 full review · NVIDIA L40S full review · All AI & Machine Learning rankings