24 releases covered on ThursdAI · wandb.ai ↗
Kimi K2.7 Code goes live on W&B/CoreWeave Inference
Kimi K2.7 Code became available on W&B/CoreWeave Inference, with the episode notes calling out Blackwell NVFP4 serving, speculative decoding, and 289 tokens per second near the top of Artificial Analysis speed and price-performance charts.
Weights & Biases launches HiveMind for coding-agent observability
Weights & Biases launched HiveMind, a dashboard for tracking AI coding-agent sessions, spend, transcripts, ROI, and reusable organizational learning. Chris Van Pelt and Adrian Swanberg joined the show to explain why teams need observability for their growing fleet of coding agents.
Weights & Biases launches MCP server with 20 tools for agents
W&B officially launched its MCP server with 20 schema-first tools so coding agents can read experiments, monitor training, and run autonomous research loops. Agents can query metadata before pulling full 300-metric runs, keeping their context windows from blowing up.
W&B LEET TUI ships workspace mode with multi-run compare and GPU metrics
Weights & Biases shipped workspace mode for LEET, its terminal UI for experiment tracking. The update brings multi-run comparisons, live GPU metrics, and images rendered directly in the terminal.
Gemma 4 goes live on W&B Inference with LoRA inference support
Weights & Biases put Gemma 4 live on W&B Inference, running on CoreWeave infrastructure with LoRA inference support. Replying to the W&B announcement post on X with the code 'Gem Drop' gets $20 in free inference credits.
W&B Automations launch: event triggers from training runs
Weights & Biases shipped Automations, event-triggered actions that pipe signals from your training runs into notifications (Slack), GitHub Actions, and deployments, pairing nicely with the new W&B iOS app. In the same Buzz segment: GLM-5.1 and Gemma 4 both went live on W&B Inference.
Weights & Biases launches native iOS app for monitoring training runs
W&B shipped its most-requested feature ever: a native iOS app for monitoring AI training runs with live metrics and push notifications for crash alerts. Practitioners can now keep an eye on long-running training jobs from their phone instead of staying glued to a dashboard.
Weights & Biases launches Agent Skills
Weights & Biases officially launched Agent Skills, installable via `npx skills add wandb/skills`. The launch coincided with Nemotron 3 Super becoming available on W&B Inference at $0.20/1M input tokens, one of the best price-performance options for a 120B model.
Wolfram previews Wolf Bench, a multi-metric agent eval from W&B
Wolfram Ravenwolf gave an early preview of Wolf Bench, a Terminal Bench-based evaluation framework from Weights & Biases that reports four metrics (average, best run, ceiling, and consistent floor) instead of a single score. It treats harness differences (Terminal Bench vs Claude Code vs OpenClaw) as a first-class factor and publishes benchmark cost and transparency details.
W&B Inference adds MiniMax 2.5 and Kimi K2.5
Weights & Biases added MiniMax M2.5 and Kimi K2.5 to its CoreWeave-backed Inference service. The panel emphasized price/performance, with MiniMax 2.5 presented as roughly 10x cheaper than premium alternatives in some tiers and Kimi K2.5 praised for practical function calling and image-in-loop use cases.
W&B adds Kimi K2.5 to its inference service
Weights & Biases launched Kimi K2.5 on its inference service, making Moonshot AI's model available to W&B users. In Wolfram's Terminal Bench deep dive for W&B, Kimi K2.5 achieved a 67.4% ceiling score across multiple runs, among the strongest open-model results he measured.
W&B Inference adds day-zero GLM-5 and Kimi K2.5 support
Weights & Biases launched day-zero GLM-5 support on its CoreWeave-powered W&B Inference service, alongside Kimi K2.5, with MiniMax 2.5 coming soon. Alex announced $50 in free credits for listeners to test the new open-weights models.
Catnip by W&B: open source iOS app to run Claude Code anywhere
Chris Van Pelt of Weights & Biases released Catnip, an open source iOS app that lets you run Claude Code from anywhere via GitHub Codespaces. It is available on the App Store with source on GitHub.
W&B launches LLM Evaluation Jobs for OpenAI-compatible APIs
Weights & Biases launched LLM Evaluation Jobs, letting teams run evaluations against any OpenAI-compatible API during training cycles instead of only at the end. The show framed it as a practical workflow upgrade for getting earlier model quality signals without blindly burning compute.
W&B launches Serverless LoRA Inference on CoreWeave
Weights & Biases launched Serverless LoRA Inference on CoreWeave: upload a LoRA adapter to W&B Artifacts and serve it instantly on top of any supported base model with no cold starts and no dedicated GPU instances. Alex demoed a 'Mocking SpongeBob' LoRA he trained in 25 minutes, served on a Qwen 2.5 base.
W&B ships LEET, an open-source terminal UI for monitoring ML runs
Weights & Biases released LEET (Lightweight Experiment Exploration Tool), an open-source terminal-native dashboard for tracking ML runs, demoed live by Dima Duev of the SDK team. It works fully offline for air-gapped HPC clusters and brings real-time metrics, system stats, and zoomable interactive charts to the terminal.
W&B brings Weave traces into Models workspaces for RL runs
Weights & Biases shipped Weave inside W&B Models workspaces, so reinforcement learning runs can now be logged and inspected with Weave trace tooling alongside training metrics. The show frames it as giving RL training 'x-ray vision' into what the model is actually doing.
W&B Weave Playground adds GPT-4.1 family and o3/o4-mini support
The Weights & Biases Weave Playground shipped full support for the new GPT-4.1 family and the o3/o4-mini models, letting developers evaluate and compare the week's new models for their own applications.
W&B launches observable.tools initiative and MCP observability RFC
Weights & Biases launched the observable.tools initiative and published an RFC (RFC-269) proposing observability standards for the Model Context Protocol, inviting community comment. W&B also announced it is a launch partner for Google's A2A protocol.
W&B launches Observable.tools initiative to add observability to MCP
Alex and Weights & Biases launched the Observable Tools initiative to bring observability to the Model Context Protocol (MCP) ecosystem, since external tool calls currently lose visibility for debugging and security. A concrete proposal using OpenTelemetry was posted to the MCP specification GitHub discussions for community feedback.
W&B ships official Weave MCP server - talk to your evals
Weights & Biases shipped an official MCP server for Weave, its LLM observability and evaluation tool, letting agents and MCP clients query and analyze your evals directly. Morgan McQuire of the W&B Applied AI team demoed it on the show, with wandb Models integration coming soon so agents can monitor loss curves for you.
Weights & Biases is acquired by CoreWeave
CoreWeave announced it is acquiring Weights & Biases, the AI developer platform and ThursdAI's home company. The deal pairs W&B's experiment tracking, Weave, and models tooling with CoreWeave's AI cloud infrastructure.
Weights & Biases releases an AI agents whitepaper and announces agents course
Weights & Biases released a whitepaper on evaluating AI agent applications and announced an upcoming agents course built in collaboration with OpenAI's Ilan Biggio, with signups at wandb.me/agents. The push targets agent evaluation and observability tooling for the community.
W&B programming agent breaks SOTA on SWE-bench Verified
Weights & Biases announced a state-of-the-art AI programming agent built with OpenAI's o1 that broke the SOTA score on SWE-bench Verified. The work was developed and tracked with W&B Weave, the team's LLM observability toolkit.
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