Agentery pricing intelligence · Provider profile · vLLM
Provider profile · independently tracked by Agentery
vLLM
Provides high-throughput, memory-efficient inference and serving for Large Language Models
Agentery price verdictNo pricing observedsource repository
SourcePublic repositorylicence not verified
Billing model—
Last checked28 Jul 2026pricing & liveness
What it does
The specific capability behind this listing, and where to get it.
vLLM
Provides high-throughput, memory-efficient inference and serving for Large Language Models
API requests to model inference (OpenAI-compatible API, Anthropic Messages API, gRPC), prompts to Hugging Face model architectures → LLM inference outputs including streaming text, structured outputs, tool calls, and multi-modal generations
Hugging FaceOpenAI-compatible APIAnthropic Messages APIgRPCNVIDIA GPUsAMD GPUsGoogle TPUsIntel GaudiAPIautonomy: infrastructure
Price status · observed daily
Source repository available · no commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is vLLM good value?
Price is straightforward; the useful comparison is capability, compatibility and operational cost.
Source repository
Source repository available · no commercial pricing observed.
A public repository, but no identified licence or self-host evidence yet — so open-source / free-to-self-host is not asserted.
Observed commercial pricenone
NicheLLM Serving Infrastructure
Price benchmarknot applicable
What to compare instead
Check capability before deciding
Compare capability, compatibility and operational cost against comparable providers — Agentery keeps the price status explicit and never invents a verdict.
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See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
"agent_id": "vllm_ai",
"name": "vLLM",
"url": "https://github.com/vllm-project/vllm",
"logo": "https://agentery.com/logos/CP-Q9MKKZ.svg",
"niche": "llm-serving-infrastructure",
"category": "developer-tools-infra",
"short_summary": "Provides high-throughput, memory-efficient inference and serving for Large Language Models",
"task_performed": "Provides high-throughput, memory-efficient inference and serving for Large Language Models",
"inputs_accepted": [
"API requests to model inference (OpenAI-compatible API",
"Anthropic Messages API",
"gRPC)",
"prompts to Hugging Face model architectures"
],
"outputs_produced": [
"LLM inference outputs including streaming text",
"structured outputs",
"tool calls",
"and multi-modal generations"
],
"integrations_available": [
"Hugging Face",
"OpenAI-compatible API",
"Anthropic Messages API",
"gRPC",
"NVIDIA GPUs",
"AMD GPUs",
"Google TPUs",
"Intel Gaudi",
"IBM Spyre",
"Huawei Ascend",
"PyTorch"
],
"protocols_or_interfaces": [
"API"
],
"industry_fit": [
"developer tools"
],
"autonomy_level": "infrastructure",
"human_approval_needed": "unclear",
"pricing_model": "free",
"price": {
"observed": false,
"billing": "unknown",
"currency": null,
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": null,
"summary": null,
"confidence": "high",
"source_url": "https://github.com/pricing",
"checked_at": "2026-07-26T10:33:35.730Z",
"amount": null,
"display": null,
"plans": [],
"source": "render+llm"
},
"trust_or_rating_signal": [
"83.1k GitHub stars",
"18.1k forks",
"2,779 contributors",
"Apache-2.0 license",
"originally developed in Sky Computing Lab at UC Berkeley",
"academic paper (SIGOPS SOSP 2023)",
"2000+ contributors from academic institutions and companies"
],
"evidence_quality": "high",
"entity_type": "infrastructure",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://github.com/vllm-project/vllm",
"https://vllm.ai/"
],
"last_checked": "2026-06-16",
"how_to_connect": {
"website": "https://github.com/vllm-project/vllm",
"docs": "https://github.com/documentation",
"mcp": {
"endpoint": "https://github.com/mcp.json",
"transport": "http",
"config_snippet": "{\n \"mcpServers\": {\n \"vllm_ai\": {\n \"url\": \"https://github.com/mcp.json\"\n }\n }\n}"
},
"a2a": null,
"api": {
"docs_url": "https://github.com/developer",
"endpoint": null
},
"protocols": []
},
"liveness": {
"probed": true,
"alive": true,
"endpoint_kind": "site",
"latency_ms": 767,
"uptime_7d": 1,
"checked_at": "2026-07-28T02:39:27.232Z",
"consecutive_failures": 0,
"status": "alive"
},
"price_extras": {
"free_tier": null,
"unit_cost": null
},
"reported_success": null,
"feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}