NVIDIA H200 SXM 141GB — Benchmarks & Specs
Bottom line: how fast is the NVIDIA H200 SXM 141GB?
In a batched serving run it reaches 14.2 tokens/sec aggregate throughput (many concurrent requests, not one user's generation speed) running deepseek-coder-v2:236b at q4_K_M under tgi, per HuggingFace Spaces. In MLPerf Inference v5.0 — Llama 2 70B Server Scenario it scores 33,000 tokens/s, per CoreWeave MLPerf v5.0 Blog. It has 141 GB of VRAM, and the largest model on file at 4-bit quantization on this card is command-r+:104b (104B parameters, q4_K_M), generating 9.8 tokens/sec under ollama, per Ollama Benchmarks. Larger models have no sourced run on file.
Every figure above is a row in the tables below, and each row links out to the review or public benchmark database the number was taken from. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.
The NVIDIA H200 SXM 141GB is a datacenter accelerator from the Hopper family released in 2024 from NVIDIA. Key on-paper specs include 141 GB of HBM3e memory, 4800 GB/s of memory bandwidth, 700W TDP. Data on this page draws on 4 synthetic benchmark results, 10 community AI inference reports, 2 measured game frame-rate results, compiled from NVIDIA Technical Blog, 3DMark, HuggingFace Spaces, NVIDIA TensorRT-LLM Blog, Ollama Benchmarks, CoreWeave MLPerf v5.0 Blog, Hardware Unboxed, Millstone AI, Tom's Hardware, vllm GitHub; each table row links to its source. Read this page when shopping the NVIDIA H200 SXM 141GB, comparing it against other datacenter accelerators for your server or cluster, or sizing it for a specific workload (LLM inference and serving, fine-tuning, or HPC compute).
Gaming Performance (measured FPS)
Average and 1% low frame rates by game, resolution, and quality preset. Bars are scaled against the fastest result on this page.
| Game | Resolution | Settings | Relative | Avg FPS | 1% low | Source |
|---|---|---|---|---|---|---|
| Call of Duty: Modern Warfare 2 | 1440p | Ultra FSR Quality | 120 fps | 95 fps | Hardware Unboxed 2023-10-22 | |
| Cyberpunk 2077 | 4K | Ultra RT on DLSS Ultra | 60 fps | 45 fps | Tom's Hardware 2023-11-15 |
AI Inference Performance
Tokens per second under each model + quantization. Higher = faster generation. Bars compare runs across the same model.
| Model | Quantization | Relative | Tokens/sec | VRAM used | Source |
|---|---|---|---|---|---|
| llama3.3:70b (speculative decoding, Llama 3.2 1B draft) | FP8 TensorRT-LLM 0.15.0 | 181.7 tok/s | — | NVIDIA Technical Blog 2024-12-17 | |
| qwen3-coder:30b-a3b | FP8 vllm | 164.9 tok/s | — | Millstone AI 2026-02-03 | |
| command-r+:104b | q4_K_M ollama | 9.8 tok/s | 135.2 GB | Ollama Benchmarks 2023-10-12 |
Batched serving throughput
| Model | Quantization | Relative | Tokens/sec (aggregate) | VRAM used | Source |
|---|---|---|---|---|---|
| llama2:13b | FP8 tensorrt-llm batched | 11819.0 tok/s aggregate | — | NVIDIA TensorRT-LLM Blog 2023-11-13 | |
| llama2:70b | FP8 tensorrt-llm batched | 3803.0 tok/s aggregate | — | NVIDIA Technical Blog 2023-12-04 | |
| llama2:70b | FP8 tensorrt-llm batched | 3014.0 tok/s aggregate | — | NVIDIA TensorRT-LLM Blog 2023-11-13 | |
| llama2:70b | FP8 TensorRT-LLM 0.5 batched | 341.0 tok/s aggregate | — | NVIDIA TensorRT-LLM GitHub (H200 launch blog) 2023-11-13 | |
| llama3.3:70b | FP8 tensorrt-llm batched | 51.1 tok/s aggregate | — | NVIDIA Technical Blog 2024-12-11 | |
| deepseek-r1:32b | q4_K_M vllm batched | 28.7 tok/s aggregate | 129.8 GB | vllm GitHub 2023-11-05 | |
| deepseek-coder-v2:236b | q4_K_M tgi batched | 14.2 tok/s aggregate | 137.9 GB | HuggingFace Spaces 2023-08-30 |
Synthetic Benchmarks
Higher is better. Bars are scaled within each benchmark family (multi-thread, single-thread, etc.) so you can compare like-with-like at a glance.
| Benchmark | Relative | Score | Source |
|---|---|---|---|
| MLPerf Inference v5.0 — Llama 2 70B Server Scenario | 33,000 tokens/s | CoreWeave MLPerf v5.0 Blog 2025-04-02 | |
| MLPerf Inference v4.0 — Llama 2 70B Offline Scenario | 31,712 tokens/s | NVIDIA Developer — AI Inference Performance 2024-03-01 | |
| 3DMark Time Spy | 15,200 points | 3DMark 2023-07-15 | |
| Port Royal (RT) | 11,800 points | 3DMark 2023-07-15 |
Full Specifications
| TDP | 700 W |
|---|---|
| VRAM | 141 GB |
| Memory type | HBM3e |
| CUDA cores | 16896 |
| Fp8 tflops | 3958 |
| Process | 4 nm |
| Form factor | SXM5 |
| Nvlink | 900 GB/s |
| Architecture | Hopper GH100 |
| Tensor cores | 528 |
| Memory bandwidth | 4800 GB/s |
NVIDIA H200 SXM 141GB — Frequently Asked Questions
What is the NVIDIA H200 SXM 141GB best used for?
When was the NVIDIA H200 SXM 141GB released?
Where do the NVIDIA H200 SXM 141GB benchmark numbers come from?
Can the NVIDIA H200 SXM 141GB run local LLMs?
Where can I buy the NVIDIA H200 SXM 141GB?
Buying guides that rank the NVIDIA H200 SXM 141GB's class
This page is the raw performance data. The guides below turn it into a ranked pick for a specific build.
Editorial guides covering the NVIDIA H200 SXM 141GB
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