NVIDIA A100 80GB SXM4 vs NVIDIA L4, AI & Machine Learning Comparison
NVIDIA A100 80GB SXM4 wins 148 of 155 benchmarks, averaging 161.9% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
What the numbers say
The gap is widest in Qwen2.5 7B served, where NVIDIA A100 80GB SXM4 leads by 365% (2187.2 vs 469.9 serve tok/s); the closest fight is Depth Anything V2 Small (1% apart); VRAM decides part of this one: NVIDIA A100 80GB SXM4 runs 155 of our 12 AI workloads while the other card runs 138, models that don't fit score zero.
Benchmark results head-to-head
| Benchmark | NVIDIA A100 80GB SXM4 | NVIDIA L4 | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 197 | 84 | +135% |
| Llama 3.1 8B tok/s | 162.57 | 50.45 | +222% |
| Qwen2.5-Coder 14B tok/s | 89.45 | 27.46 | +226% |
| Qwen3 32B tok/s | 45.53 | 12.42 | +267% |
| Llama 3.3 70B tok/s | 24.4 | 0 | n/a |
| Stable Diffusion XL images/min | 16.36 | 5.18 | +216% |
| Z-Image Turbo images/min | 9.975 | 2.475 | +303% |
| FLUX.1 dev images/min | 4.264 | 0 | n/a |
| FLUX.1 Kontext dev images/min | 1.993 | 0 | n/a |
| Qwen-Image-Edit images/min | 1.64 | 0 | n/a |
| Wan 2.2 5B (720p) frames/s | 0.66 | 0.15 | +340% |
| DeepSeek-R1 Distill Llama 8B tok/s | 159.37 | 50.39 | +216% |
| DeepSeek-R1 Distill 1.5B tok/s | 327.66 | 191.38 | +71% |
| DeepSeek-R1 Distill 14B tok/s | 87 | 27.39 | +218% |
| DeepSeek-R1 Distill 7B tok/s | 162.96 | 53.27 | +206% |
| Gemma 3 12B tok/s | 91.45 | 31.01 | +195% |
| Gemma 3 4B tok/s | 176.94 | 82.03 | +116% |
| Gemma 4 12B tok/s | 92.43 | 31.49 | +194% |
| Llama 3.2 1B tok/s | 525.32 | 259.48 | +102% |
| Llama 3.2 3B tok/s | 264.25 | 107.1 | +147% |
| Mistral 7B v0.3 tok/s | 171.92 | 54.02 | +218% |
| Mistral Small 24B tok/s | 61.38 | 17.33 | +254% |
| Phi-4 14B tok/s | 95.22 | 27.24 | +250% |
| Phi-4 Mini 3.8B tok/s | 239.17 | 88.48 | +170% |
| Qwen2.5-Coder 7B tok/s | 164.6 | 53.26 | +209% |
| Qwen3 0.6B tok/s | 428.39 | 357.79 | +20% |
| Qwen3 1.7B tok/s | 343.58 | 177.5 | +94% |
| Qwen3 14B tok/s | 90.64 | 27.61 | +228% |
| Qwen3 30B A3B tok/s | 177.32 | 96.15 | +84% |
| Qwen3 8B tok/s | 149.96 | 48.95 | +206% |
| SmolLM3 3B tok/s | 249.76 | 112.07 | +123% |
| TRELLIS Image-to-3D assets/hour | 488.7 | 284.8 | +72% |
| Codestral 22B tok/s | 63.26 | 18.14 | +249% |
| DeepSeek-R1 Distill 32B tok/s | 43.11 | 12.28 | +251% |
| Devstral Small 24B tok/s | 61.63 | 17.34 | +255% |
| Dolphin 2.9.1 Yi 1.5 34B tok/s | 43.47 | 11.92 | +265% |
| Dolphin Mistral 24B Venice tok/s | 62.72 | 17.34 | +262% |
| Dolphin X1 8B tok/s | 158.62 | 50.12 | +216% |
| Dolphin 3.0 Llama 3.1 8B tok/s | 158.63 | 50.24 | +216% |
| Dolphin 3.0 R1 Mistral 24B tok/s | 61.17 | 17.32 | +253% |
| Gemma 3 27B tok/s | 48.43 | 14.18 | +242% |
| Qwen2.5-Coder 32B tok/s | 43.36 | 12.29 | +253% |
| Qwen3-Coder 30B A3B tok/s | 182.26 | 99.14 | +84% |
| QwQ 32B tok/s | 43.27 | 12.28 | +252% |
| StarCoder2 15B tok/s | 79.22 | 24.4 | +225% |
| FLUX.1 Schnell images/min | 28.39 | 0 | n/a |
| Z-Image Turbo (1024px) images/min | 18.65 | 4.6 | +305% |
| Krea 2 Turbo images/min | 3.35 | 0 | n/a |
| BiRefNet images/min | 916.67 | 305.81 | +200% |
| Depth Anything V2 Large images/min | 876.29 | 770.37 | +14% |
| Depth Anything V2 Small images/min | 925.15 | 916.66 | +1% |
| SAM ViT-Base images/min | 744.79 | 315.89 | +136% |
| SAM ViT-Huge images/min | 145.7 | 70.46 | +107% |
| Swin2SR 4x Upscaler images/min | 28.72 | 18.23 | +58% |
| Florence-2 Base images/min | 126.4 | 174.65 | -28% |
| Florence-2 Large images/min | 70.94 | 93.77 | -24% |
| Qwen2.5 1.5B LoRA train tok/s | 8252.8 | 3720.9 | +122% |
| Qwen2.5 7B LoRA train tok/s | 3900.6 | 1063.9 | +267% |
| SmolLM2 1.7B LoRA train tok/s | 9750.8 | 3240.2 | +201% |
| TinyLlama 1.1B LoRA train tok/s | 9553.3 | 4756 | +101% |
| Stable Video Diffusion XT clips/min | 1.536 | 0 | n/a |
| Wan 2.2 TI2V-5B (image to video) clips/min | 2.156 | 0 | n/a |
| CogVideoX-5B I2V clips/min | 0.468 | 0 | n/a |
| Qwen2.5 1.5B served serve tok/s | 4564.7 | 1827 | +150% |
| Qwen2.5 7B served serve tok/s | 2187.2 | 469.9 | +365% |
| SmolLM2 1.7B served serve tok/s | 4351.4 | 1524.9 | +185% |
| TinyLlama 1.1B served serve tok/s | 5701.5 | 2584.3 | +121% |
| DeepSeek-R1-Distill-Llama-70B tok/s | 22.99 | 0 | n/a |
| DeepSeek-R1-Distill-Qwen-32B-abliterated tok/s | 43.48 | 12.26 | +255% |
| Kokoro TTS 82M x realtime | 110.17 | 97.35 | +13% |
| Llama-3.3-70B-Instruct-abliterated tok/s | 22.92 | 0 | n/a |
| Meta-Llama-3.1-70B tok/s | 22.92 | 0 | n/a |
| MusicGen Small x realtime | 0.74 | 1.01 | -27% |
| Nemotron-3-Nano-30B-A3B tok/s | 204.06 | 0 | n/a |
| Whisper large-v3 x realtime | 73.83 | 70.11 | +5% |
| Qwen2.5-Coder 32B (Q3_K_M) tok/s | 31.99 | 12.05 | +165% |
| AI21-Jamba-Reasoning-3B tok/s | 239.23 | 107.59 | +122% |
| Olmo-3.1-32B-Think tok/s | 46.49 | 12.27 | +279% |
| Codestral 22B (Q3_K_M) tok/s | 49.52 | 17.96 | +176% |
| Dolphin-Mistral-24B-Venice-Edition tok/s | 65.77 | 17.2 | +282% |
| DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored tok/s | 164.46 | 48.82 | +237% |
| DeepSeek-Coder-V2-Lite tok/s | 213.91 | 110.11 | +94% |
| DeepSeek-R1-0528-Qwen3-8B tok/s | 152.76 | 49.07 | +211% |
| DeepSeek-R1 Distill 14B (Q3_K_M) tok/s | 67.13 | 27.87 | +141% |
| dolphin-2.9-llama3-8b tok/s | 164.09 | 50.04 | +228% |
| Dolphin X1 Trinity Nano 6B tok/s | 158.41 | 166.6 | -5% |
| EVA-Qwen2.5-14B-v0.2 tok/s | 90.35 | 27.3 | +231% |
| gemma-2-2b-it-abliterated tok/s | 244.41 | 113 | +116% |
| gemma-2-2b tok/s | 244.52 | 114.17 | +114% |
| gemma-2-9b tok/s | 108.68 | 33.8 | +222% |
| Gemma 3 12B (Q3_K_M) tok/s | 71.88 | 32.29 | +123% |
| gemma-3-1b tok/s | 324.08 | 216.27 | +50% |
| gemma-3-270m tok/s | 617.58 | 493.31 | +25% |
| GLM-4.7-Flash-REAP-23B-A3B tok/s | 112.75 | 70.87 | +59% |
| GLM-4.7-Flash tok/s | 124.08 | 75.03 | +65% |
| Josiefied-Qwen3-8B-abliterated-v1 tok/s | 152.29 | 48.72 | +213% |
| gpt-oss-20b tok/s | 212.63 | 91.78 | +132% |
| Hermes-3-Llama-3.2-3B tok/s | 269.13 | 106.14 | +154% |
| Hermes-4-70B tok/s | 24.47 | 0 | n/a |
| SmolLM3-3B tok/s | 254.6 | 110.77 | +130% |
| Qwen3-Coder-Next-abliterated tok/s | 119.56 | 0 | n/a |
| KAT-Coder-V2.5-Dev tok/s | 146.38 | 79.01 | +85% |
| L3-8B-Stheno-v3.2 tok/s | 164.51 | 50.07 | +229% |
| Laguna-XS-2.1 tok/s | 0 | 0 | n/a |
| LFM2.5-1.2B tok/s | 576.95 | 278.53 | +107% |
| LFM2.5-8B-A1B tok/s | 369.01 | 170.2 | +117% |
| Llama-2-7B tok/s | 180.09 | 56.06 | +221% |
| Llama-3.2-3B-Instruct-uncensored tok/s | 269.13 | 101.16 | +166% |
| Meta-Llama-3.1-8B tok/s | 164.24 | 50.36 | +226% |
| Phi-4-mini tok/s | 243.38 | 87.21 | +179% |
| Mistral-7B-Instruct-v0.1 tok/s | 173.87 | 53.6 | +224% |
| Mistral-7B-Instruct-v0.2 tok/s | 173.8 | 53.31 | +226% |
| Mistral-7B-Instruct-v0.3 tok/s | 173.27 | 53.66 | +223% |
| Mistral-Nemo-Instruct-2407 tok/s | 111.07 | 33.01 | +236% |
| Mistral Small 24B (Q3_K_M) tok/s | 46.63 | 16.62 | +181% |
| Nanbeige4.2-3B tok/s | 0 | 0 | n/a |
| NemoMix-Unleashed-12B tok/s | 110.99 | 33.02 | +236% |
| Hermes-4-14B tok/s | 94.48 | 27.48 | +244% |
| Ornith-1.0-35B tok/s | 138.8 | 70.31 | +97% |
| Ornith-1.0-9B tok/s | 134.67 | 43.35 | +211% |
| phi-2 tok/s | 235.55 | 114.99 | +105% |
| Phi-3.5-mini tok/s | 229.46 | 90.56 | +153% |
| Phi-4 14B (Q3_K_M) tok/s | 82.68 | 27.86 | +197% |
| Qwen-AgentWorld-35B-A3B tok/s | 139.69 | 70.23 | +99% |
| Qwen3-0.6B tok/s | 432.66 | 356.93 | +21% |
| Qwen3-1.7B tok/s | 350.4 | 176.08 | +99% |
| Qwen3-14B tok/s | 94.35 | 27.48 | +243% |
| Qwen3-30B-A3B tok/s | 178.14 | 95.02 | +87% |
| Qwen3-4B-Instruct-2507 tok/s | 199.39 | 83.03 | +140% |
| Qwen3-8B tok/s | 152.8 | 48.34 | +216% |
| Qwen3-Coder-Next tok/s | 118.62 | 0 | n/a |
| Qwen3-Next-80B-A3B-Thinking tok/s | 118.93 | 0 | n/a |
| Qwen1.5-0.5B tok/s | 540.32 | 431.41 | +25% |
| Qwen2-1.5B tok/s | 333.79 | 189.18 | +76% |
| Qwen2.5-0.5B tok/s | 571.49 | 399.4 | +43% |
| Qwen2.5-1.5B tok/s | 335.29 | 191.39 | +75% |
| Uncensored tok/s | 89.43 | 27.29 | +228% |
| Qwen2.5-14B tok/s | 90.46 | 27.37 | +231% |
| Qwen2.5-32B tok/s | 45.6 | 12.24 | +273% |
| Qwen2.5-3B tok/s | 248.47 | 110.84 | +124% |
| Qwen2.5-72B tok/s | 23.95 | 0 | n/a |
| Qwen2.5-7B tok/s | 166.92 | 53.32 | +213% |
| Qwen2.5-Coder-0.5B tok/s | 562.59 | 397.1 | +42% |
| Qwen2.5-Coder-1.5B tok/s | 333.87 | 184.6 | +81% |
| Qwen2.5-Coder-14B-Instruct-abliterated tok/s | 90.28 | 27.29 | +231% |
| Qwen2.5-Coder-3B tok/s | 248.7 | 109.42 | +127% |
| Qwen2.5-Coder-7B-Instruct-abliterated tok/s | 166.84 | 53.02 | +215% |
| Qwen3 30B A3B (Q3_K_M) tok/s | 146.72 | 94.03 | +56% |
| Qwen3-4B-Instruct-2507 tok/s | 199.65 | 83.13 | +140% |
| Qwen3-4B-Thinking-2507 tok/s | 199.71 | 83.12 | +140% |
| Qwen3-Coder-Next tok/s | 120.71 | 0 | n/a |
| Qwen3-Next-80B-A3B-Thinking tok/s | 120.98 | 0 | n/a |
| Qwen3-Next-80B-A3B tok/s | 117.44 | 0 | n/a |
| SmolLM2-135M tok/s | 554.44 | 652.15 | -15% |
| Cydonia-24B-v4.3 tok/s | 65.82 | 17.3 | +280% |
Whole-job comparison
How long each card takes to finish a complete pipeline, not just one model. NVIDIA A100 80GB SXM4 is faster on 8 of 8; NVIDIA L4 on 0.
| Workflow | NVIDIA A100 80GB SXM4 | NVIDIA L4 | Difference | Cost per run |
|---|---|---|---|---|
| 50-image depth pass | 5 s | 17 s | NVIDIA A100 80GB SXM4 3.43x faster | $0.002 vs $0.002 |
| 30-minute podcast pass | 67 s | 2 min | NVIDIA A100 80GB SXM4 1.80x faster | $0.026 vs $0.015 |
| 500-image masking run | 3.5 min | 7.5 min | NVIDIA A100 80GB SXM4 2.14x faster | $0.081 vs $0.055 |
| 24-frame storyboard | 3.7 min | 12.2 min | NVIDIA A100 80GB SXM4 3.32x faster | $0.085 vs $0.089 |
| 20-asset 3D game kit | 4 min | 8.3 min | NVIDIA A100 80GB SXM4 2.09x faster | $0.092 vs $0.061 |
| 200-product catalogue cutout | 7.3 min | 12.1 min | NVIDIA A100 80GB SXM4 1.66x faster | $0.169 vs $0.089 |
| Full codebase review | 11.2 min | 36.4 min | NVIDIA A100 80GB SXM4 3.26x faster | $0.259 vs $0.267 |
| 10 short social clips | 15.1 min | 60.3 min | NVIDIA A100 80GB SXM4 3.99x faster | $0.350 vs $0.442 |
Renting by the hour, NVIDIA L4 finishes 4 of 8 cheaper. The quicker card is not automatically the cheaper way to get the work done.
Cost to rent
| Card | Per hour |
|---|---|
| NVIDIA A100 80GB SXM4 | $1.390 |
| NVIDIA L4 | $0.440 |
NVIDIA L4 is 3.16x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.
Specifications compared
| NVIDIA A100 80GB SXM4 | NVIDIA L4 | |
|---|---|---|
| VRAM | 80GB | 24GB |
| Architecture | Ampere | Ada Lovelace |
| Memory bandwidth | 2039 GB/s | 300 GB/s |
| Boost clock | 1,410 MHz | 2,040 MHz |
| TDP | 400 W | 72 W |
| Launch MSRP | $17,000 | $2,500 |
| Release | 2020-11-16 | 2023-03-21 |
FAQ
- Which is better for ai & machine learning: NVIDIA A100 80GB SXM4 or NVIDIA L4?
- NVIDIA A100 80GB SXM4 performs better for ai & machine learning, winning 148 of 155 benchmarks in our suite with an average 161.9% advantage.
- What are the main hardware differences between NVIDIA A100 80GB SXM4 and NVIDIA L4?
- NVIDIA A100 80GB SXM4 has 80GB VRAM and a 400W TDP, while NVIDIA L4 has 24GB VRAM and a 72W TDP.
- Does VRAM matter more than speed between NVIDIA A100 80GB SXM4 and NVIDIA L4?
- For AI, yes, NVIDIA A100 80GB SXM4 fits 22 more of our 12 workloads than NVIDIA L4. 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 L4?
- Qwen2.5 7B served: NVIDIA A100 80GB SXM4 leads by roughly 365% (2187.2 vs 469.9 serve tok/s) in our testing.
NVIDIA A100 80GB SXM4 full review · NVIDIA L4 full review · All AI & Machine Learning rankings