vLLM
Established LeaderThe High-Throughput and Memory-Efficient inference and serving engine for LLMs
vllm.ai Source★ 27.3KApache-2.0AI Models & Agents / Model Training & Inference Infrastructure
- Monthly visits
- 1M
- Down3.9%MoMSep 2026
- Public revenue
- Undisclosed
- No public revenue evidence yet
- Entry price
- Free
- No monthly subscription pricing
- Launched
- 3y ago
- 2023-06-19 · Est.
Traffic
Marketing moves
Launches, search & content, referrals, promotions- vLLM-Omni also support H3-Image across NVIDIA data-center and RTX GPUs, AMD, Intel, Moore Threads, and Huawei Ascend NPUs 🙌 From your desktop to Rubin, let’s create! 🖼️ 回复原帖 @vllm_project: On 4x Rubin GPUs, initial throughput tuning al
@vllm_project · 2026-11-12 · 3 likes · 0 reposts · 1,088 views
- Congrats to @MiniMax_AI on H3-Image taking the #1 spot among open-weight models for image editing by Artificial Analysis! 🎉 We’re bringing NVIDIA Vera Rubin support H3-image to vLLM-Omni, and native 4K generation in 0.87 seconds!⚡️ Check
@vllm_project · 2026-11-12 · 44 likes · 6 reposts · 3,159 views
- These gains come from optimizations across the vLLM engine (e.g., eliminating CPU overheads) and Rubin-optimized kernels, including MiniMax Sparse Attention and decode-specialized kernels. Our M3.1 blog covered the first wave of Rubin opti
@vllm_project · 2026-11-11 · 8 likes · 0 reposts · 1,396 views
vLLM-Omni supports H3-Image across multiple GPU and NPU platformsProduct Activity
vLLM announced that vLLM-Omni supports H3-Image across NVIDIA data-center and RTX GPUs, AMD, Intel, Moore Threads, and Huawei Ascend NPUs.
Nov 12 · 2d agoX Post
PyTorch hosts Ascend for PyTorch Meetup in BeijingPromotions
On November 7, PyTorch hosted the Ascend for PyTorch Meetup in Beijing, bringing together maintainers from PyTorch core, TorchNPU, vLLM, and over a hundred developers for technical talks, roundtables, and hands-on sessions.
Nov 7 · 7d agoX Post
vLLM adds day-0 support for ERNIE 5.5 Flash BaseProduct Activity
vLLM announced Day-0 support for Baidu's ERNIE 5.5 Flash Base. Models can be served in FP8 or BF16 using Baidu's vLLM-ERNIE plugin on vLLM 0.32.0.
Nov 5 · 9d agoLaunch PostX Post
New product launchLaunch
Jun 19, 2023 · 3y agoWebsite
Open Source & Self-Hosting
- GitHub Stars
- ★ 27.3K
- Forks
- 5,925
- License
- Apache-2.0
- Primary language
- Python
Traffic sources
Traffic breakdown
Channels
- Direct43%
- Organic Search35%
- Referrals16%
- Other5%
Countries
- China42%
- United States13%
- India5%
- Nigeria3%
- South Korea3%
Search
Domain authority 82Domain registered 2023-06-19
| Keyword | Monthly volume |
|---|---|
| vllm | 138.5K |
| deepseek v4.1 | 96.6K |
| vllm-ascend | 2,000 |
| vllm ascend | 1,930 |
| vllm recipe | 1,920 |
Traffic data: Vaneform
Pricing
Pricing page not identified yet, or no public pricing listed.
Pages & changes
Key pages
Weekly snapshots- Homevllm.ai/
- Featuresvllm.ai/events Snapshot 2026-11-05
Official blog & changelog
Recent articles & product updatesH3-Image Day-0 Support: 4K in 0.87s with Vera Rubin
H3-Image on Vera Rubin: 0.87-second 4K generation or 6,115 images/hour on four GPUs, with projected API revenue and support across consumer and data-center hardware.
Encoder Disaggregation in vLLM: Scaling Multimodal Serving with EPD
Recent advances in vLLM encoder disaggregation: metadata-only multimodal requests, dedicated encoder execution, remote embedding transfer, cross-encoder caching, and lower-overhead EPD routing.
Migrating vLLM to the LibTorch Stable ABI
How vLLM migrated its CUDA build and compiled dependencies to the LibTorch Stable ABI, enabling compatible PyTorch upgrades without rebuilding vLLM.
VeRL-Omni v0.3.0: Async Training and Broader Multimodal Post-Training
VeRL-Omni v0.3.0 expands async RL, makes the V1 trainer the default, and adds reproducible recipes for audio-video generation and multimodal understanding.
Changes
No pricing, plan, or positioning changes detected since tracking started.
Design
Minimal Monochrome (Light canvas, airy density) featuring centered headline + cta layout and pure typography & geometry visuals.
First-screen preview · click to zoom
First-screen pitch & conversion flow
“The High-Throughput and Memory-Efficient inference and serving engine for LLMs”
Centered Headline + CTA hero structure paired with download app / install extension CTA and no explicit trust bar.
Conversion path: Centered Headline + CTA + Pure Typography & Geometry → Download App / Install Extension
- Category Positioning Anchor
Palette · click to copy
- Typography
- 7.0
- Color & Contrast
- 7.0
- Layout & Spacing
- 7.0
- Craft & Polish
- 7.0
- Distinctiveness
- 5.0
Structure
- Fonts
- Inter
- Hero layout
- Centered Headline + CTA
- Primary visual
- Pure Typography & Geometry
- Conversion CTA
- Download App / Install Extension
- Social proof
- No Explicit Trust Bar
- Navigation
- Full-Width Top Bar
- Theme & density
- Light · Airy
- Corners & depth
- Small Radius · Hairline borders
Preview full AI design brief (includes :root CSS variables & layout rules)Style tokens only; never copy brand names, logos, copy, or images
# Design Brief: Minimal Monochrome
Monochrome palette with a single accent color, hairline dividers, and generous whitespace.
## Design Tokens
```css
:root {
--background: #ffffff;
--surface: #eaf6fe;
--foreground: #050510;
--muted-foreground: #6b7787;
--accent: #35a3ef;
--radius: 4px;
--font-heading: "Inter", ui-sans-serif, system-ui, sans-serif;
--font-body: "Inter", ui-sans-serif, system-ui, sans-serif;
}
```
Color area ratio: Background #FFFFFF (~84%) · Surface #EAF6FE (~3%) · Text #050510 (~6%) · Muted Text #6B7787 (~3%) · Accent #35A3EF (~4%). Background and surface dominate the canvas; reserve the accent color for primary buttons and active states.
## Layout & Conversion Structure
- Hero layout: Centered Headline + CTA
- Navigation: Full-Width Top Bar
- Theme & density: Light · Airy
- Border radius & elevation: Small Radius; no drop shadows—separate layers with hairline borders and whitespace
- Primary visual medium: Pure Typography & Geometry
- Conversion CTA: Download App / Install Extension
- Headline hook: Category Positioning Anchor
- Spatial layout notes: Centered Headline + CTA hero structure paired with download app / install extension CTA and no explicit trust bar.
- Visual summary: Minimal Monochrome (Light canvas, airy density) featuring centered headline + cta layout and pure typography & geometry visuals.
## Avoid
- Multi-stop neon gradients
- Heavy drop shadows
- More than one competing accent color
Implement the UI following the design tokens and layout specifications above: use only these color variables, and reserve the accent color strictly for primary actions and active states. Adopt only this visual style—never copy any reference product’s brand name, logo, copy, or imagery.
Questions & evidence
- How much website traffic does vLLM get?
- Vaneform estimates 1M website visits in 2026-09. Visits can include repeat visits; this estimate does not measure paying customers or revenue.Source
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