Finance & Business1 month ago
Portfolio Intel | AI Portfolio Insights & CAS Parser
Upload a CAS PDF to get AI portfolio analysis with benchmark comparisons and allocation insights.
@iASHeeesh · X
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60 projects
Upload a CAS PDF to get AI portfolio analysis with benchmark comparisons and allocation insights.
@iASHeeesh · X
Benchmark local coding models on consumer hardware to measure accuracy, latency, and throughput across 27 tasks.
u/Unfair_Association89 · Reddit
I built a reproducible benchmark for local coding models (Ollama, 27 tasks, live leaderboard) ran it on my 8GB card, here's what I found I kept eyeballing "vibes" to decide whether one quant of a coding model was actually better than another on my machine, so I built Sakura to get real numbers instead. What it does: - Points at any Ollama model and runs it through 27 hand-curated tasks: codegen, bugfix, SQL, refactor, systems design, protocol implementation, and terminal-agent episode
Compare AI language models by performance across official benchmarks.
fcten · V2EX
做了一个大模型 leaderboard 网站 最近一个月 CodeX 疯狂送重置，token 根本用不完，顺手做点东西。 地址：[知行录]( https://leaderboard.cn/) 排行依据主要为模型官方基准测试成绩。非主观排名。 数据会持续更新。如果有点用，欢迎各位 v 友收藏～
Compare AI coding models on real tasks with live previews, cost tracking, and ELO rankings.
@intheworldofai · X
On the World of AI Bench (vibe-coding composite): Claude Fable 5 → 85.2 GPT-5.6-sol → 82.4 kimi-k3 → 81.5 Moonshot’s K3 just walked in and claimed bronze on one of the toughest coding-focused leaderboards out there.
Compare latency and throughput performance across LLM API providers.
@QAInsights · X
Compare and evaluate AI models across coding, reasoning, agents, and other benchmarks.
davidtsong · HN
Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities
View and compare public opinions and benchmark ratings for leading AI models.
u/TasteMysterious5285 · Reddit
I built AI Census, a live field bulletin for how people are actually talking about AI models I’ve been building AI Census, a public “field bulletin” for how people are talking about current AI models. I kept running into the same problem: benchmark tables tell me how a model performs on a test, but not whether people are actually finding it useful, frustrating, reliable, etc. So I built a rolling view from public technical conversations across Reddit, Hacker News, Bluesky, GitHub, and Huggi
Upload vendor proposals to get AI-powered side-by-side comparison with red flags and citations.
@nbOlveira · X
A vendor comparison software
Measure your GPU's real memory-bandwidth ceiling for local AI in 30 seconds.
Ar5en1c · HN
Headroom – measure your GPU's true bandwidth ceiling for local AI
Submit kernel patches and engine optimizations for LLM inference speed, benchmarked on dedicated hardware.
carsenk · HN
Frontier.fast – Help push the frontier of LLM speed forward
Benchmark version-control systems and coding agents on realistic development tasks.
videlov · HN
I was interested in answering this question so I built a benchmark comparing git, jj and gitbutler in agentic context https://vcbench.dev/ Disclaimer - I am a co-founder of GitButler
Speech to text dictation and multi-engine speed benchmarking. Compare OpenAI GPT-Transcribe, Deepgram Nova-3, NVIDIA Parakeet, and Fish Audio with local IndexedDB privacy.
@alvaisy · X
finished voice to text small web app for my own itch. it's opensource. use openrotuer key. and use it with 4 models.