tensward
Profile and diagnose LLM serving on your own GPU. Measures your vLLM setup on your real workload and suggests what to change.
This is 1 of 208 launches in GPU acceleration and developer tools — see how it stacks up on momentum and crowding →
49 other launches read as similar to this one →
Details
- External ID
- 1399503811
- Source
- GITHUB
- Company
- —
- Product
- tensward
- Website domain
- pypi.org
- Launched
- Oct. 1, 2026
- Cohort
- —
- Upvotes
- 9
- Upvotes percentile
- 0.14634146341463414
- Tags
- —
- Fetched at
- Oct. 2, 2026, 1:02 a.m.
- Updated at
- Oct. 2, 2026, 1:02 a.m.
Enrichment
- Theme
- GPU acceleration and developer tools
- Vertical
- Horizontal
- Function
- Observability & eval
- Audience
- Developer
- AI stance
- AI feature
- Project type
- Commercial product
- Normalized one-liner
- llm serving profiling and diagnosis tool for gpus
- Manually corrected
- False
Could you build this?
Partial Building the benchmarking UI and basic command runners is straightforward, but profiling low-level GPU memory dynamics and vLLM performance metrics requires deep CUDA and LLM serving systems knowledge.
What it would actually take: Requires a Python client that hooks directly into vLLM internals, PyTorch CUDA memory allocators, and NVIDIA NVML/DCGM APIs to track KV-cache consumption, token throughput, and TTFT under varying batch sizes. The hard part is generating reliable automated diagnosis rules and tuning heuristics based on kernel execution traces and PagedAttention bottlenecks across disparate GPU architectures. This demands deep domain expertise in distributed LLM inference and GPU systems profiling.
Competitors
Other products that read as similar to this one — 49 launches clear the similarity bar, closest 8 shown.
Attention rank: #38 of 50 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 336 days after the earliest competitor.
- Open-source calculator for "will my GPU run this LLM?" · hn · 2026-08-24 · 5 upvotes · similarity 0.52
- VRAMGlass · ph · 2026-09-19 · 1 upvotes · similarity 0.46
- agent-gpu-calculator · github · 2026-09-24 · 7 upvotes · similarity 0.40
- Utilyze · hn · 2026-04-27 · 128 upvotes · similarity 0.39
- r9700-stack · github · 2026-09-21 · 9 upvotes · similarity 0.39
- Minimal LLM Post-Training Experiments on an 8GB GPU (SFT, DPO, GRPO) · hn · 2026-08-01 · 21 upvotes · similarity 0.39
- Tokenflood · hn · 2025-11-12 · 21 upvotes · similarity 0.38
- Find the best local LLM for your hardware, ranked by benchmarks · hn · 2026-05-15 · 283 upvotes · similarity 0.38
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a observability & eval tool for Media & entertainment yet.