Unverified50% confidenceFactExact time
Running vLLM 0.27.1 official image to infer Qwen2.5-0.5B-Instruct (fp16) on an H100 SXM 80GB on vast.ai ($2.689 per hour, 20 vCPU), the cost per million output tokens is about $1.26 under a single-request serial load.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/13/2026
First Seen
Valid until: 1/11/2027
Sources
Related Entities
Related Claims
VerifiedThe NVIDIA H100 SXM5 has a peak FP16 compute performance of approximately 989 TFLOPS, with a single-card price exceeding $30,000 and a cloud rental cost of approximately $2–4 per hour.73% similarUnverifiedOn SIE Cloud, Qwen3.8-27B (FP8) is offered at $0.72 per million tokens for both input and output; GLiNER2 Large is $0.186 per million input tokens.73% similarUnverifiedAn L4 instance costs about $1.0465 per hour, roughly ten times that of a 1 vCPU instance.73% similarUnverifiedA 256 GB M5 Ultra costs approximately $10,000, an amount that could sustain four years of paying $200 per month to Cloud or ChatGPT to use state-of-the-art models.72% similarUnverified一块H100 GPU租用成本约每小时2-4美元,单卡每秒可生成约1000-3000个输出Token71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1014543API
curl https://kongchang.com/api/v1/knowledge/claims/1014543MCP
get_claim(id=1014543)