Weights & Biases

Our W&B LEET TUI went viral. So we made it way more powerful. The big new unlock is workspace mode. › Multi-run workspace. Live. › Metadata filtering. › System metrics. › Console logs. › Images in the terminal. All in one workspace. All in your terminal. 🧵

@RoundtableSpace finetuning gemma 7b using @UnslothAI , @Gradio with @wandb

Production VLA pipelines scale three workloads across three hardware profiles, plus thousands of stochastic sim rollouts. Join @anyscalecompute + @wandb May 12 to orchestrate it end-to-end with Ray. Register: na2.hubs.ly/H05dzc10

Can confirm, @cursor_ai is the best harness we've tested on @WolfBenchAI so far! @WolframRvnwlf tests Harness x Model, and Cursor (before the SDK) is the best one we've ever tested!

Easy to set up! #highlight-config-values" target="_blank" rel="nofollow noopener">docs.wandb.ai/models/track/c…

Stop hunting through config for the same 3 links every run. Pin them as References at the top of the W&B Overview tab. Renders as markdown, sits above Notes and Tags, always one click away.

W&B Inference provides frontier and open-weights models, observability included, on @SemiAnalysis_ platinum-grade infrastructure. Day-0 launches, every time. Try it below! wandb.ai/inference/core…

Why Granite 4.1 8B stands out: → ~20x fewer output tokens than Qwen3.5 9B on the Artificial Analysis Intelligence Index (4M vs 78M) → 61 on the AA Openness Index — top of class for open-weights non-reasoning models → Enhanced tool calling, instruction following, and chat

NEW: @IBM Granite 4.1 8B is live on W&B Inference! $0.05 / $0.10 per 1M tokens. 131k context. Apache 2.0. Build production agents with native tool calling, trace every call with @weave_wb, and run it all on @CoreWeave's platinum-grade AI cloud. 🧵

GPT-5.5 takes over WolfBench! It’s now the #1 model, ahead of Claude Opus 4.7 and 4.6, GPT-5.4, Sonnet 4.6, Kimi K2.6, Gemini 3.1 Pro, and more. Notable findings after 30 runs (40h runtime, >1.7B tokens, ~$3K cost): - @OpenAI's GPT-5.5 is the best model we ever tested. - @cursor_ai's Agent CLI (CA) is the best agent we ever tested. - @NousResearch's Hermes Agent (HA) outperformed OpenClaw (OC). - With Hermes, going from medium to xhigh reasoning only improved consistency, not capability. Note: This is WolfBench, where we look at more than just the average score, because one metric is not enough. The golden ∅ score is the actual 5-run average, which most other benchmarks report as their only score. ★ shows the ceiling (what percentage of the full benchmark this model+agent combination solved at least once across all runs). ■ shows the solid base (what percentage of the full benchmark it solved consistently in every run).

Take it for a spin below. wandb.ai/site/serverles…

Still feels a little unreal that you can just upload a dataset, get a fine-tuned LoRA back, and have it auto-deployed for inference without touching a single GPU config. Serverless SFT is still in public preview and adapter training is free right now. Don't sleep on it.

은 사실 RL 로 학습된 결과입니다. @wandb editorial here api.wandb.ai/links/namenu-s…

@wandb It looks absolutely fantastic

@twominutepapers 🫡

Our W&B LEET TUI went viral. So we made it way more powerful. The big new unlock is workspace mode. › Multi-run workspace. Live. › Metadata filtering. › System metrics. › Console logs. › Images in the terminal. All in one workspace. All in your terminal. 🧵

@wandb merch to lift weights 🤝

was a blast for our team at @CopilotKit to partner on the coolest happy hour at #GoogleCloudNext with @Redisinc & @wandb fun first week of work🏎️🏁

YouTube: wb.oia.bio/138yt Apple Podcasts: wb.openinapp.link/138ap Spotify: wb.oia.bio/138s

Can you drive in the dark Arctic or amidst a Tokyo typhoon? This AI car can. @wayve_ai drove through both, plus 504 more cities, with almost no additional training data for over half of them.  @alexgkendall calls it proof that “generalization at scale” is possible for AI cars.

YouTube: wb.oia.bio/AaronYT Spotify: wb.oia.bio/AaronS Apple Podcasts: wb.openinapp.link/AaronAP

Aaron Katz (@ceo_clickhouse) built a $15B company around one philosophy: Nobody likes being sold to. So he served Anthropic, OpenAI, LangChain and Vercel without a sales team. Just a shared Slack channel with their top engineers and a commitment to get you into production before competitors had even scoped the project. Four years in, 3000 customers. The numbers speak for themselves.