> ## Documentation Index
> Fetch the complete documentation index at: https://lmsysorg-dsv4-1.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Qwen-Image-Edit-2511

export const QwenImageEditDeployment = () => {
  const config = {
    modelFamily: 'Qwen-Image-Edit',
    options: {
      hardware: {
        name: 'hardware',
        title: 'Hardware Platform',
        items: [{
          id: 'b200',
          label: 'B200',
          default: true
        }, {
          id: 'b300',
          label: 'B300',
          default: false
        }, {
          id: 'h200',
          label: 'H200',
          default: false
        }, {
          id: 'h100',
          label: 'H100',
          default: false
        }, {
          id: 'mi300x',
          label: 'MI300X',
          default: false
        }, {
          id: 'mi325x',
          label: 'MI325X',
          default: false
        }, {
          id: 'mi355x',
          label: 'MI355X',
          default: false
        }]
      }
    },
    generateCommand: function (values) {
      return `sglang serve \\
  --model-path Qwen/Qwen-Image-Edit-2511 \\
  --ulysses-degree=1 \\
  --ring-degree=1`;
    }
  };
  if (!config || !config.options) {
    return <div>Error: Invalid configuration provided</div>;
  }
  const getInitialState = () => {
    const initialState = {};
    Object.entries(config.options).forEach(([key, option]) => {
      if (option.type === 'checkbox') {
        initialState[key] = (option.items || []).filter(item => item.default).map(item => item.id);
        return;
      }
      if (option.type === 'text') {
        initialState[key] = option.default || '';
        return;
      }
      let items = option.items || [];
      if (option.getDynamicItems) {
        const defaultValues = {};
        Object.entries(config.options).forEach(([innerKey, innerOption]) => {
          if (innerOption.type === 'checkbox') {
            defaultValues[innerKey] = (innerOption.items || []).filter(item => item.default).map(item => item.id);
          } else if (innerOption.type === 'text') {
            defaultValues[innerKey] = innerOption.default || '';
          } else if (innerOption.items && innerOption.items.length > 0) {
            const defaultItem = innerOption.items.find(item => item.default);
            defaultValues[innerKey] = defaultItem ? defaultItem.id : innerOption.items[0].id;
          }
        });
        items = option.getDynamicItems(defaultValues);
      }
      const defaultItem = items && items.find(item => item.default);
      initialState[key] = defaultItem ? defaultItem.id : items && items[0] ? items[0].id : '';
    });
    return initialState;
  };
  const [values, setValues] = useState(getInitialState);
  const [isDark, setIsDark] = useState(false);
  useEffect(() => {
    const checkDarkMode = () => {
      const html = document.documentElement;
      const isDarkMode = html.classList.contains('dark') || html.getAttribute('data-theme') === 'dark' || html.style.colorScheme === 'dark';
      setIsDark(isDarkMode);
    };
    checkDarkMode();
    const observer = new MutationObserver(checkDarkMode);
    observer.observe(document.documentElement, {
      attributes: true,
      attributeFilter: ['class', 'data-theme', 'style']
    });
    return () => observer.disconnect();
  }, []);
  const handleRadioChange = (optionName, value) => {
    setValues(prev => ({
      ...prev,
      [optionName]: value
    }));
  };
  const handleCheckboxChange = (optionName, itemId, isChecked) => {
    setValues(prev => {
      const currentValues = prev[optionName] || [];
      if (isChecked) {
        return {
          ...prev,
          [optionName]: [...currentValues, itemId]
        };
      }
      return {
        ...prev,
        [optionName]: currentValues.filter(id => id !== itemId)
      };
    });
  };
  const handleTextChange = (optionName, value) => {
    setValues(prev => ({
      ...prev,
      [optionName]: value
    }));
  };
  const command = config.generateCommand ? config.generateCommand.call(config, values) : '';
  const containerStyle = {
    maxWidth: '900px',
    margin: '0 auto',
    display: 'flex',
    flexDirection: 'column',
    gap: '4px'
  };
  const cardStyle = {
    padding: '8px 12px',
    border: `1px solid ${isDark ? '#374151' : '#e5e7eb'}`,
    borderLeft: `3px solid ${isDark ? '#E85D4D' : '#D45D44'}`,
    borderRadius: '4px',
    display: 'flex',
    alignItems: 'center',
    gap: '12px',
    background: isDark ? '#1f2937' : '#fff'
  };
  const titleStyle = {
    fontSize: '13px',
    fontWeight: '600',
    minWidth: '140px',
    flexShrink: 0,
    color: isDark ? '#e5e7eb' : 'inherit'
  };
  const itemsStyle = {
    display: 'flex',
    rowGap: '2px',
    columnGap: '6px',
    flexWrap: 'wrap',
    alignItems: 'center',
    flex: 1
  };
  const labelBaseStyle = {
    padding: '4px 10px',
    border: `1px solid ${isDark ? '#9ca3af' : '#d1d5db'}`,
    borderRadius: '3px',
    cursor: 'pointer',
    display: 'inline-flex',
    flexDirection: 'column',
    alignItems: 'center',
    justifyContent: 'center',
    fontWeight: '500',
    fontSize: '13px',
    transition: 'all 0.2s',
    userSelect: 'none',
    minWidth: '45px',
    textAlign: 'center',
    flex: 1,
    background: isDark ? '#374151' : '#fff',
    color: isDark ? '#e5e7eb' : 'inherit'
  };
  const checkedStyle = {
    background: '#D45D44',
    color: 'white',
    borderColor: '#D45D44'
  };
  const disabledStyle = {
    cursor: 'not-allowed',
    opacity: 0.5
  };
  const subtitleStyle = {
    display: 'block',
    fontSize: '9px',
    marginTop: '1px',
    lineHeight: '1.1',
    opacity: 0.7
  };
  const textInputStyle = {
    flex: 1,
    padding: '8px 10px',
    borderRadius: '4px',
    border: `1px solid ${isDark ? '#4b5563' : '#d1d5db'}`,
    background: isDark ? '#111827' : '#fff',
    color: isDark ? '#e5e7eb' : '#111827',
    fontSize: '13px'
  };
  const commandDisplayStyle = {
    flex: 1,
    padding: '12px 16px',
    background: isDark ? '#111827' : '#f5f5f5',
    borderRadius: '6px',
    fontFamily: "'Menlo', 'Monaco', 'Courier New', monospace",
    fontSize: '12px',
    lineHeight: '1.5',
    color: isDark ? '#e5e7eb' : '#374151',
    whiteSpace: 'pre-wrap',
    overflowX: 'auto',
    margin: 0,
    border: `1px solid ${isDark ? '#374151' : '#e5e7eb'}`
  };
  return <div style={containerStyle} className="not-prose">
      {Object.entries(config.options).map(([key, option]) => {
    if (option.condition && !option.condition(values)) {
      return null;
    }
    const items = option.getDynamicItems ? option.getDynamicItems(values) : option.items || [];
    return <div key={key} style={cardStyle}>
            <div style={titleStyle}>{option.title}</div>
            <div style={itemsStyle}>
              {option.type === 'text' ? <input type="text" value={values[option.name] || ''} placeholder={option.placeholder || ''} onChange={event => handleTextChange(option.name, event.target.value)} style={textInputStyle} /> : option.type === 'checkbox' ? (option.items || []).map(item => {
      const isChecked = (values[option.name] || []).includes(item.id);
      const isDisabled = item.required || typeof item.disabledWhen === 'function' && item.disabledWhen(values);
      return <label key={item.id} title={item.disabledReason || ''} style={{
        ...labelBaseStyle,
        ...isChecked ? checkedStyle : {},
        ...isDisabled ? disabledStyle : {}
      }}>
                      <input type="checkbox" checked={isChecked} disabled={isDisabled} onChange={event => handleCheckboxChange(option.name, item.id, event.target.checked)} style={{
        display: 'none'
      }} />
                      {item.label}
                      {item.subtitle && <small style={{
        ...subtitleStyle,
        color: isChecked ? 'rgba(255,255,255,0.85)' : 'inherit'
      }}>
                          {item.subtitle}
                        </small>}
                    </label>;
    }) : items.map(item => {
      const isChecked = values[option.name] === item.id;
      const isDisabled = Boolean(item.disabled);
      return <label key={item.id} title={item.disabledReason || ''} style={{
        ...labelBaseStyle,
        ...isChecked ? checkedStyle : {},
        ...isDisabled ? disabledStyle : {}
      }}>
                      <input type="radio" name={option.name} value={item.id} checked={isChecked} disabled={isDisabled} onChange={() => !isDisabled && handleRadioChange(option.name, item.id)} style={{
        display: 'none'
      }} />
                      {item.label}
                      {item.subtitle && <small style={{
        ...subtitleStyle,
        color: isChecked ? 'rgba(255,255,255,0.85)' : 'inherit'
      }}>
                          {item.subtitle}
                        </small>}
                    </label>;
    })}
            </div>
          </div>;
  })}

      <div style={cardStyle}>
        <div style={titleStyle}>Run this Command:</div>
        <pre style={commandDisplayStyle}>{command}</pre>
      </div>
    </div>;
};

export const DiffusionModelTags = ({tags = []}) => {
  const normalizedTags = Array.isArray(tags) ? tags : [tags];
  return <div className="not-prose sgd-model-tags">
      {normalizedTags.map(tag => <span key={tag} className="sgd-chip">
          {tag}
        </span>)}
    </div>;
};

<DiffusionModelTags tags={["image editing", "text replacement", "character consistency", "multi-person", "20B"]} />

## 1. Model Introduction

[Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) is the 20B editing counterpart to Qwen-Image. It is strongest at changing text, materials, lighting, viewpoint, or composition while reducing drift in regions that were not requested to change.

Choose it for identity-sensitive portrait edits, multi-person composition, typography replacement, and geometry-aware design work. It is substantially heavier than small specialist editors, and consistency is improved rather than guaranteed; evaluate untouched-region drift on the actual editing workload.

## 2. SGLang-diffusion Installation

SGLang-diffusion offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.

Please refer to the [official SGLang-diffusion installation guide](https://docs.sglang.io/docs/sglang-diffusion/installation) for installation instructions.

## 3. Model Deployment

This section provides deployment configurations optimized for different hardware platforms and use cases.

### 3.1 Basic Configuration

Qwen-Image-Edit-2511 is a 20B parameter model optimized for image editing tasks. The recommended launch configurations vary by hardware.

**Interactive Command Generator**: Use the configuration selector below to automatically generate the appropriate deployment command for your hardware platform.

<QwenImageEditDeployment />

### 3.2 Configuration Tips

See [Performance Optimization](/docs/sglang-diffusion/performance-optimization) for acceleration features and their runtime requirements.

* `--vae-path`: Path to a custom VAE model or HuggingFace model ID (e.g., fal/FLUX.2-Tiny-AutoEncoder). If not specified, the VAE will be loaded from the main model path.
* `--num-gpus`: Number of GPUs to use
* `--tp-size`: Tensor parallelism size (only for the encoder; should not be larger than 1 if text encoder offload is enabled, as layer-wise offload plus prefetch is faster)
* `--sp-degree`: Sequence parallelism size (typically should match the number of GPUs)
* `--ulysses-degree`: The degree of DeepSpeed-Ulysses-style SP in USP
* `--ring-degree`: The degree of ring attention-style SP in USP

### 3.3 Decompose an image into layers on H200

`Qwen/Qwen-Image-Layered` returns separate RGBA images. For this model,
`--num-frames 4` requests four output layers. The CLI saves all four PNGs,
and `DiffGenerator.generate()` returns one result per layer.

On Linux with NVIDIA CUDA and two H200 GPUs, you can run the conditional and
unconditional branches on separate GPUs:

```bash Command theme={null}
CUDA_VISIBLE_DEVICES=0,1 sglang generate \
  --model-path Qwen/Qwen-Image-Layered \
  --num-gpus 2 \
  --cfg-parallel-size 2 \
  --tp-size 1 \
  --ulysses-degree 1 \
  --quality lossless \
  --enable-torch-compile false \
  --warmup-mode request \
  --width 640 --height 640 --num-frames 4 \
  --num-inference-steps 50 --guidance-scale 4.0 --seed 42 \
  --image-path https://raw.githubusercontent.com/QwenLM/Qwen-Image-Layered/main/assets/test_images/4.png \
  --prompt "a high quality, cute halloween themed illustration, consistent style and lighting" \
  --output-path outputs/qwen-layered \
  --save-output
```

For a single H200, set `CUDA_VISIBLE_DEVICES=0`, `--num-gpus 1`, and
`--cfg-parallel-size 1`. Both configurations use eager execution. Layered
does not currently support breakable CUDA graph; enabling BCG falls back to
eager execution.

The Layered CFG policy gathers the branch predictions before applying the
single-GPU arithmetic order, preserving BF16 rounding and alpha values in the
validated fixed-seed example. Each GPU still holds a full DiT replica, so CFG
parallelism reduces request latency without reducing the model memory needed
on each GPU.

## 4. API Usage

For complete API documentation, please refer to the [official API usage guide](/docs/sglang-diffusion/api/openai_api).

### 4.1 Edit an Image

```python Example theme={null}
import base64
from openai import OpenAI

client = OpenAI(api_key="EMPTY", base_url="http://localhost:3000/v1")

response = client.images.edit(
    model="Qwen/Qwen-Image-Edit-2511",
    image=open("input.png", "rb"),
    prompt="Change the color of the taxi to black.",
    n=1,
    response_format="b64_json",
)

# Save the edited image
image_bytes = base64.b64decode(response.data[0].b64_json)
with open("output.png", "wb") as f:
    f.write(image_bytes)
```

### 4.2 Advanced Usage

#### 4.2.1 Cache-DiT Acceleration

SGLang integrates [Cache-DiT](https://github.com/vipshop/cache-dit), a caching acceleration engine for Diffusion Transformers (DiT), to achieve up to 7.4x inference speedup with minimal quality loss. You can set `SGLANG_CACHE_DIT_ENABLED=True` to enable it. For more details, please refer to the SGLang Cache-DiT [documentation](/docs/sglang-diffusion/cache_dit).

**Basic Usage**

```bash Command theme={null}
SGLANG_CACHE_DIT_ENABLED=true sglang serve --model-path Qwen/Qwen-Image-Edit-2511
```

**Advanced Usage**

* DBCache Parameters: DBCache controls block-level caching behavior:

<table style={{width: "100%", borderCollapse: "collapse", tableLayout: "fixed"}}>
  <colgroup>
    <col style={{width: "25.0%"}} />

    <col style={{width: "25.0%"}} />

    <col style={{width: "25.0%"}} />

    <col style={{width: "25.0%"}} />
  </colgroup>

  <thead>
    <tr style={{borderBottom: "2px solid #d55816"}}>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.02)"}}>Parameter</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.05)"}}>Env Variable</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.02)"}}>Default</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.05)"}}>Description</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>Fn</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`SGLANG_CACHE_DIT_FN`</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>1</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Number of first blocks to always compute</td>
    </tr>

    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>Bn</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`SGLANG_CACHE_DIT_BN`</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>0</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Number of last blocks to always compute</td>
    </tr>

    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>W</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`SGLANG_CACHE_DIT_WARMUP`</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>4</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Warmup steps before caching starts</td>
    </tr>

    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>R</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`SGLANG_CACHE_DIT_RDT`</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>0.24</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Residual difference threshold</td>
    </tr>

    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>MC</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`SGLANG_CACHE_DIT_MC`</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>3</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Maximum continuous cached steps</td>
    </tr>
  </tbody>
</table>

* TaylorSeer Configuration: TaylorSeer improves caching accuracy using Taylor expansion:

<table style={{width: "100%", borderCollapse: "collapse", tableLayout: "fixed"}}>
  <colgroup>
    <col style={{width: "25.0%"}} />

    <col style={{width: "25.0%"}} />

    <col style={{width: "25.0%"}} />

    <col style={{width: "25.0%"}} />
  </colgroup>

  <thead>
    <tr style={{borderBottom: "2px solid #d55816"}}>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.02)"}}>Parameter</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.05)"}}>Env Variable</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.02)"}}>Default</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.05)"}}>Description</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>Enable</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`SGLANG_CACHE_DIT_TAYLORSEER`</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>false</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Enable TaylorSeer calibrator</td>
    </tr>

    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>Order</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`SGLANG_CACHE_DIT_TS_ORDER`</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>1</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Taylor expansion order (1 or 2)</td>
    </tr>
  </tbody>
</table>

Combined Configuration Example:

```bash Command theme={null}
SGLANG_CACHE_DIT_ENABLED=true \
SGLANG_CACHE_DIT_FN=2 \
SGLANG_CACHE_DIT_BN=1 \
SGLANG_CACHE_DIT_WARMUP=4 \
SGLANG_CACHE_DIT_RDT=0.4 \
SGLANG_CACHE_DIT_MC=4 \
SGLANG_CACHE_DIT_TAYLORSEER=true \
SGLANG_CACHE_DIT_TS_ORDER=2 \
sglang serve --model-path Qwen/Qwen-Image-Edit-2511
```

#### 4.2.2 CPU Offload

* `--dit-cpu-offload`: Use CPU offload for DiT inference. Enable if run out of memory.
* `--text-encoder-cpu-offload`: Use CPU offload for text encoder inference.
* `--image-encoder-cpu-offload`: Use CPU offload for image encoder inference.
* `--vae-cpu-offload`: Use CPU offload for VAE.
* `--pin-cpu-memory`: Pin memory for CPU offload. Only added as a temp workaround if it throws "CUDA error: invalid argument".

#### 4.2.3 Known LoRA examples

Use `--lora-path` at startup or the [LoRA management API](/docs/sglang-diffusion/api/openai_api#lora-management) to load an adapter. Known Qwen-Image-Edit examples include:

* [`ostris/qwen_image_edit_inpainting`](https://huggingface.co/ostris/qwen_image_edit_inpainting)
* [`lightx2v/Qwen-Image-Edit-2511-Lightning`](https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning)

## 5. Benchmark

Test Environment:

* Hardware: NVIDIA B200 GPU (1x)
* Model: Qwen/Qwen-Image-Edit-2511
* sglang diffusion version: 0.5.6.post2

### 5.1 Speedup Benchmark

#### 5.1.1 Edit a image

**Server Command**:

```shell Command theme={null}
sglang serve --model-path Qwen/Qwen-Image-Edit-2511 --port 30000
```

**Benchmark Command**:

```shell Command theme={null}
python3 -m sglang.multimodal_gen.benchmarks.bench_serving \
    --dataset vbench --task image-to-image --num-prompts 1 --max-concurrency 1
```

**Result**:

```text Output theme={null}
================= Serving Benchmark Result =================
Model:                                   Qwen/Qwen-Image-Edit-2511
Dataset:                                 vbench
Task:                                    image-to-image
--------------------------------------------------
Benchmark duration (s):                  35.31
Request rate:                            inf
Max request concurrency:                 1
Successful requests:                     1/1
--------------------------------------------------
Request throughput (req/s):              0.03
Latency Mean (s):                        35.3053
Latency Median (s):                      35.3053
Latency P99 (s):                         35.3053
--------------------------------------------------
Peak Memory Max (MB):                    47959.35
Peak Memory Mean (MB):                   47959.35
Peak Memory Median (MB):                 47959.35
============================================================
```

#### 5.1.2 Edit a image with high concurrency

**Benchmark Command**:

```shell Command theme={null}
python3 -m sglang.multimodal_gen.benchmarks.bench_serving \
    --dataset vbench --task image-to-image --num-prompts 20 --max-concurrency 20
```

**Result**:

```text Output theme={null}
================= Serving Benchmark Result =================
Model:                                   Qwen/Qwen-Image-Edit-2511
Dataset:                                 vbench
Task:                                    image-to-image
--------------------------------------------------
Benchmark duration (s):                  286.11
Request rate:                            inf
Max request concurrency:                 20
Successful requests:                     20/20
--------------------------------------------------
Request throughput (req/s):              0.07
Latency Mean (s):                        150.0428
Latency Median (s):                      150.0600
Latency P99 (s):                         283.3843
--------------------------------------------------
Peak Memory Max (MB):                    47971.82
Peak Memory Mean (MB):                   47971.49
Peak Memory Median (MB):                 47971.29
============================================================
```