NVIDIA H100 80GB HBM3 vs NVIDIA L4, AI & Machine Learning Comparison
NVIDIA H100 80GB HBM3 wins 153 of 156 benchmarks, averaging 334.2% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
What the numbers say
The gap is widest in Z-Image Turbo, where NVIDIA H100 80GB HBM3 leads by 794% (22.125 vs 2.475 images/min); the closest fight is Depth Anything V2 Small (18% apart); VRAM decides part of this one: NVIDIA H100 80GB HBM3 runs 156 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 H100 80GB HBM3 | NVIDIA L4 | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 310.26 | 84 | +269% |
| Llama 3.1 8B tok/s | 261.83 | 50.45 | +419% |
| Qwen2.5-Coder 14B tok/s | 144.84 | 27.46 | +427% |
| Qwen3 32B tok/s | 74.07 | 12.42 | +496% |
| Llama 3.3 70B tok/s | 41 | 0 | n/a |
| Stable Diffusion XL images/min | 34.58 | 5.18 | +568% |
| Z-Image Turbo images/min | 22.125 | 2.475 | +794% |
| FLUX.1 dev images/min | 9.064 | 0 | n/a |
| FLUX.1 Kontext dev images/min | 4.264 | 0 | n/a |
| Qwen-Image-Edit images/min | 3.68 | 0 | n/a |
| Wan 2.2 5B (720p) frames/s | 1.33 | 0.15 | +787% |
| DeepSeek-R1 Distill Llama 8B tok/s | 261.15 | 50.39 | +418% |
| DeepSeek-R1 Distill 1.5B tok/s | 537.32 | 191.38 | +181% |
| DeepSeek-R1 Distill 7B tok/s | 264.42 | 53.27 | +396% |
| Gemma 3 12B tok/s | 150.58 | 31.01 | +386% |
| Gemma 3 4B tok/s | 289.61 | 82.03 | +253% |
| Llama 3.2 1B tok/s | 880.64 | 259.48 | +239% |
| Llama 3.2 3B tok/s | 422.87 | 107.1 | +295% |
| Mistral 7B v0.3 tok/s | 275.85 | 54.02 | +411% |
| Phi-4 Mini 3.8B tok/s | 388.86 | 88.48 | +339% |
| Qwen2.5-Coder 7B tok/s | 263.91 | 53.26 | +396% |
| Qwen3 0.6B tok/s | 713.53 | 357.79 | +99% |
| Qwen3 1.7B tok/s | 556.48 | 177.5 | +214% |
| Qwen3 14B tok/s | 151.16 | 27.61 | +447% |
| Qwen3 8B tok/s | 244.22 | 48.95 | +399% |
| SmolLM3 3B tok/s | 397.99 | 112.07 | +255% |
| DeepSeek-R1 Distill 14B tok/s | 144.82 | 27.39 | +429% |
| Gemma 4 12B tok/s | 148.17 | 31.49 | +371% |
| Mistral Small 24B tok/s | 105.62 | 17.33 | +509% |
| Phi-4 14B tok/s | 165.17 | 27.24 | +506% |
| Qwen3 30B A3B tok/s | 283.78 | 96.15 | +195% |
| TRELLIS Image-to-3D assets/hour | 864 | 284.8 | +203% |
| Codestral 22B tok/s | 110.05 | 18.14 | +507% |
| DeepSeek-R1 Distill 32B tok/s | 75.8 | 12.28 | +517% |
| Devstral Small 24B tok/s | 107.79 | 17.34 | +522% |
| Dolphin 2.9.1 Yi 1.5 34B tok/s | 76.76 | 11.92 | +544% |
| Dolphin Mistral 24B Venice tok/s | 109.13 | 17.34 | +529% |
| Dolphin X1 8B tok/s | 266 | 50.12 | +431% |
| Dolphin 3.0 Llama 3.1 8B tok/s | 266.19 | 50.24 | +430% |
| Dolphin 3.0 R1 Mistral 24B tok/s | 107.83 | 17.32 | +523% |
| Gemma 3 27B tok/s | 84.77 | 14.18 | +498% |
| Qwen2.5-Coder 32B tok/s | 75.81 | 12.29 | +517% |
| Qwen3-Coder 30B A3B tok/s | 296.22 | 99.14 | +199% |
| QwQ 32B tok/s | 75.82 | 12.28 | +517% |
| StarCoder2 15B tok/s | 134.92 | 24.4 | +453% |
| FLUX.1 Schnell images/min | 58.36 | 0 | n/a |
| Z-Image Turbo (1024px) images/min | 39.42 | 4.6 | +757% |
| Krea 2 Turbo images/min | 6.85 | 0 | n/a |
| BiRefNet images/min | 1310.97 | 305.81 | +329% |
| Depth Anything V2 Large images/min | 918.71 | 770.37 | +19% |
| Depth Anything V2 Small images/min | 1081.54 | 916.66 | +18% |
| SAM ViT-Base images/min | 1431.27 | 315.89 | +353% |
| SAM ViT-Huge images/min | 320.64 | 70.46 | +355% |
| Swin2SR 4x Upscaler images/min | 25.48 | 18.23 | +40% |
| Kokoro TTS 82M x realtime | 222.02 | 97.35 | +128% |
| MusicGen Small x realtime | 2.47 | 1.01 | +145% |
| Whisper large-v3 x realtime | 181.47 | 70.11 | +159% |
| Florence-2 Base images/min | 249.62 | 174.65 | +43% |
| Florence-2 Large images/min | 156.15 | 93.77 | +67% |
| Qwen2.5 1.5B LoRA train tok/s | 16034.9 | 3720.9 | +331% |
| Qwen2.5 7B LoRA train tok/s | 8514.3 | 1063.9 | +700% |
| SmolLM2 1.7B LoRA train tok/s | 18910.3 | 3240.2 | +484% |
| TinyLlama 1.1B LoRA train tok/s | 17522 | 4756 | +268% |
| CogVideoX-5B I2V clips/min | 0.879 | 0 | n/a |
| Qwen2.5 1.5B served serve tok/s | 6794.8 | 1827 | +272% |
| Qwen2.5 7B served serve tok/s | 3601.1 | 469.9 | +666% |
| SmolLM2 1.7B served serve tok/s | 6509.9 | 1524.9 | +327% |
| TinyLlama 1.1B served serve tok/s | 8336.7 | 2584.3 | +223% |
| Stable Video Diffusion XT clips/min | 2.882 | 0 | n/a |
| Wan 2.2 TI2V-5B (image to video) clips/min | 4.126 | 0 | n/a |
| Qwen2.5 1.5B + 0.5B draft x vs solo | 0.725 | 0.968 | -25% |
| AI21-Jamba-Reasoning-3B tok/s | 363.09 | 107.59 | +237% |
| Olmo-3.1-32B-Think tok/s | 75.53 | 12.27 | +516% |
| Codestral 22B (Q3_K_M) tok/s | 87.21 | 17.96 | +386% |
| Dolphin-Mistral-24B-Venice-Edition tok/s | 105.63 | 17.2 | +514% |
| DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored tok/s | 262.76 | 48.82 | +438% |
| DeepSeek-Coder-V2-Lite tok/s | 309.14 | 110.11 | +181% |
| DeepSeek-R1-0528-Qwen3-8B tok/s | 245.26 | 49.07 | +400% |
| DeepSeek-R1-Distill-Llama-70B tok/s | 41.17 | 0 | n/a |
| DeepSeek-R1 Distill 14B (Q3_K_M) tok/s | 118.43 | 27.87 | +325% |
| DeepSeek-R1-Distill-Qwen-32B-abliterated tok/s | 73.48 | 12.26 | +499% |
| dolphin-2.9-llama3-8b tok/s | 262.47 | 50.04 | +425% |
| Dolphin X1 Trinity Nano 6B tok/s | 247.94 | 166.6 | +49% |
| EVA-Qwen2.5-14B-v0.2 tok/s | 145.15 | 27.3 | +432% |
| gemma-2-2b-it-abliterated tok/s | 392.65 | 113 | +247% |
| gemma-2-2b tok/s | 392.26 | 114.17 | +244% |
| gemma-2-9b tok/s | 174.7 | 33.8 | +417% |
| Gemma 3 12B (Q3_K_M) tok/s | 125.92 | 32.29 | +290% |
| gemma-3-1b tok/s | 504.17 | 216.27 | +133% |
| gemma-3-270m tok/s | 961.29 | 493.31 | +95% |
| GLM-4.7-Flash-REAP-23B-A3B tok/s | 168.41 | 70.87 | +138% |
| GLM-4.7-Flash tok/s | 186.05 | 75.03 | +148% |
| Josiefied-Qwen3-8B-abliterated-v1 tok/s | 245 | 48.72 | +403% |
| gpt-oss-20b tok/s | 346.8 | 91.78 | +278% |
| Hermes-3-Llama-3.2-3B tok/s | 423.72 | 106.14 | +299% |
| Hermes-4-70B tok/s | 41.2 | 0 | n/a |
| SmolLM3-3B tok/s | 399.14 | 110.77 | +260% |
| Qwen3-Coder-Next-abliterated tok/s | 190.32 | 0 | n/a |
| KAT-Coder-V2.5-Dev tok/s | 231.83 | 79.01 | +193% |
| L3-8B-Stheno-v3.2 tok/s | 261.83 | 50.07 | +423% |
| Laguna-XS-2.1 tok/s | 0 | 0 | n/a |
| LFM2.5-1.2B tok/s | 926.61 | 278.53 | +233% |
| LFM2.5-8B-A1B tok/s | 581.98 | 170.2 | +242% |
| Llama-2-7B tok/s | 284.62 | 56.06 | +408% |
| Llama-3.2-3B-Instruct-uncensored tok/s | 424.25 | 101.16 | +319% |
| Llama-3.3-70B-Instruct-abliterated tok/s | 41.15 | 0 | n/a |
| Meta-Llama-3.1-70B tok/s | 41.19 | 0 | n/a |
| Meta-Llama-3.1-8B tok/s | 261.7 | 50.36 | +420% |
| Phi-4-mini tok/s | 381.52 | 87.21 | +337% |
| Mistral-7B-Instruct-v0.1 tok/s | 276.29 | 53.6 | +415% |
| Mistral-7B-Instruct-v0.2 tok/s | 276.73 | 53.31 | +419% |
| Mistral-7B-Instruct-v0.3 tok/s | 276.61 | 53.66 | +415% |
| Mistral-Nemo-Instruct-2407 tok/s | 177.38 | 33.01 | +437% |
| Mistral Small 24B (Q3_K_M) tok/s | 84 | 16.62 | +405% |
| Nanbeige4.2-3B tok/s | 0 | 0 | n/a |
| NemoMix-Unleashed-12B tok/s | 177.28 | 33.02 | +437% |
| Nemotron-3-Nano-30B-A3B tok/s | 316.51 | 0 | n/a |
| Hermes-4-14B tok/s | 152 | 27.48 | +453% |
| Ornith-1.0-35B tok/s | 221.65 | 70.31 | +215% |
| Ornith-1.0-9B tok/s | 216.89 | 43.35 | +400% |
| phi-2 tok/s | 340.09 | 114.99 | +196% |
| Phi-3.5-mini tok/s | 345.07 | 90.56 | +281% |
| Phi-4 14B (Q3_K_M) tok/s | 138.87 | 27.86 | +398% |
| Qwen-AgentWorld-35B-A3B tok/s | 219.1 | 70.23 | +212% |
| Qwen3-0.6B tok/s | 710.97 | 356.93 | +99% |
| Qwen3-1.7B tok/s | 557.09 | 176.08 | +216% |
| Qwen3-14B tok/s | 152.2 | 27.48 | +454% |
| Qwen3-30B-A3B tok/s | 285.44 | 95.02 | +200% |
| Qwen3-4B-Instruct-2507 tok/s | 310.58 | 83.03 | +274% |
| Qwen3-8B tok/s | 244.2 | 48.34 | +405% |
| Qwen3-Coder-Next tok/s | 188.21 | 0 | n/a |
| Qwen3-Next-80B-A3B-Thinking tok/s | 188.14 | 0 | n/a |
| Qwen1.5-0.5B tok/s | 847.02 | 431.41 | +96% |
| Qwen2-1.5B tok/s | 536.52 | 189.18 | +184% |
| Qwen2.5-0.5B tok/s | 890 | 399.4 | +123% |
| Qwen2.5-1.5B tok/s | 537.24 | 191.39 | +181% |
| Uncensored tok/s | 144.92 | 27.29 | +431% |
| Qwen2.5-14B tok/s | 144.7 | 27.37 | +429% |
| Qwen2.5-32B tok/s | 73.5 | 12.24 | +500% |
| Qwen2.5-3B tok/s | 395.52 | 110.84 | +257% |
| Qwen2.5-72B tok/s | 40.78 | 0 | n/a |
| Qwen2.5-7B tok/s | 264.17 | 53.32 | +395% |
| Qwen2.5-Coder-0.5B tok/s | 892.81 | 397.1 | +125% |
| Qwen2.5-Coder-1.5B tok/s | 538.44 | 184.6 | +192% |
| Qwen2.5-Coder-14B-Instruct-abliterated tok/s | 145.01 | 27.29 | +431% |
| Qwen2.5-Coder 32B (Q3_K_M) tok/s | 58.05 | 12.05 | +382% |
| Qwen2.5-Coder-3B tok/s | 394 | 109.42 | +260% |
| Qwen2.5-Coder-7B-Instruct-abliterated tok/s | 264.24 | 53.02 | +398% |
| Qwen3 30B A3B (Q3_K_M) tok/s | 242.6 | 94.03 | +158% |
| Qwen3-4B-Instruct-2507 tok/s | 311.47 | 83.13 | +275% |
| Qwen3-4B-Thinking-2507 tok/s | 310.84 | 83.12 | +274% |
| Qwen3-Coder-Next tok/s | 193.79 | 0 | n/a |
| Qwen3-Next-80B-A3B-Thinking tok/s | 191.08 | 0 | n/a |
| Qwen3-Next-80B-A3B tok/s | 186.22 | 0 | n/a |
| SmolLM2-135M tok/s | 898.53 | 652.15 | +38% |
| Cydonia-24B-v4.3 tok/s | 105.49 | 17.3 | +510% |
Whole-job comparison
How long each card takes to finish a complete pipeline, not just one model. NVIDIA H100 80GB HBM3 is faster on 8 of 8; NVIDIA L4 on 0.
| Workflow | NVIDIA H100 80GB HBM3 | NVIDIA L4 | Difference | Cost per run |
|---|---|---|---|---|
| 50-image depth pass | 5 s | 17 s | NVIDIA H100 80GB HBM3 3.11x faster | $0.002 vs $0.002 |
| 30-minute podcast pass | 34 s | 2 min | NVIDIA H100 80GB HBM3 3.53x faster | $0.013 vs $0.015 |
| 500-image masking run | 1.6 min | 7.5 min | NVIDIA H100 80GB HBM3 4.62x faster | $0.036 vs $0.055 |
| 24-frame storyboard | 1.8 min | 12.2 min | NVIDIA H100 80GB HBM3 6.72x faster | $0.040 vs $0.089 |
| 20-asset 3D game kit | 2.2 min | 8.3 min | NVIDIA H100 80GB HBM3 3.82x faster | $0.049 vs $0.061 |
| Full codebase review | 6.9 min | 36.4 min | NVIDIA H100 80GB HBM3 5.27x faster | $0.154 vs $0.267 |
| 10 short social clips | 8 min | 60.3 min | NVIDIA H100 80GB HBM3 7.56x faster | $0.178 vs $0.442 |
| 200-product catalogue cutout | 8.1 min | 12.1 min | NVIDIA H100 80GB HBM3 1.48x faster | $0.181 vs $0.089 |
Renting by the hour, NVIDIA H100 80GB HBM3 finishes 7 of 8 cheaper. The quicker card is not automatically the cheaper way to get the work done.
Cost to rent
| Card | Per hour |
|---|---|
| NVIDIA H100 80GB HBM3 | $1.336 |
| NVIDIA L4 | $0.440 |
NVIDIA L4 is 3.04x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.
Specifications compared
| NVIDIA H100 80GB HBM3 | NVIDIA L4 | |
|---|---|---|
| VRAM | 80GB | 24GB |
| Architecture | Hopper | Ada Lovelace |
| Memory bandwidth | 3350 GB/s | 300 GB/s |
| Boost clock | 1,980 MHz | 2,040 MHz |
| TDP | 700 W | 72 W |
| Launch MSRP | $30,000 | $2,500 |
| Release | 2022-09-20 | 2023-03-21 |
FAQ
- Which is better for ai & machine learning: NVIDIA H100 80GB HBM3 or NVIDIA L4?
- NVIDIA H100 80GB HBM3 performs better for ai & machine learning, winning 153 of 156 benchmarks in our suite with an average 334.2% advantage.
- What are the main hardware differences between NVIDIA H100 80GB HBM3 and NVIDIA L4?
- NVIDIA H100 80GB HBM3 has 80GB VRAM and a 700W TDP, while NVIDIA L4 has 24GB VRAM and a 72W TDP.
- Does VRAM matter more than speed between NVIDIA H100 80GB HBM3 and NVIDIA L4?
- For AI, yes, NVIDIA H100 80GB HBM3 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 H100 80GB HBM3 and NVIDIA L4?
- Z-Image Turbo: NVIDIA H100 80GB HBM3 leads by roughly 794% (22.125 vs 2.475 images/min) in our testing.
NVIDIA H100 80GB HBM3 full review · NVIDIA L4 full review · All AI & Machine Learning rankings