Weights & Biases
Experiment-tracking and ML-ops platform — log metrics, artifacts, datasets, sweeps. Acquired by CoreWeave in 2025 for $1.7B.
At a glance
- Type
- ML experiment tracking + ops
- Tier
- T1
- Section
- Training infrastructure
- Created
- 2017
- Latest release
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- License
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- GitHub
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- Pricing
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- Funding
- $250M total raised through Series C (2023-03, valuation reported ~$1.25B unicorn) — Insight Partners led.
Taxonomy
- storage
- n/a
- retrieval
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- persistence
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- update
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- unit
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- governance
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- conflict
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When to use
Optimised for: searched not found
Anti-fit: searched not found
Pros & cons
Pros
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Cons
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Claims & capabilities
$250M total raised through Series C ($50M, 2023-03; ~$1.25B post-money); 1M+ user accounts; CoreWeave announced acquisition of W&B in 2025-03 for ~$1.7B (closed 2025-05).
Technical surface
- API surface
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- Backend storage
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- Deployment
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- Embedding model
- not applicable — not a memory product
- Multi-tenancy
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- MCP
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- A2A
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- OpenTelemetry
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Similar systems
Other training infrastructure in the catalog, ranked by inbound references.
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- LoRA T3
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- DPO T3
Stanford method that converts RLHF into a supervised-learning loss over preference pairs — no separate reward model needed; widely adopted alignment recipe.
- GRPO T3
DeepSeek-Math's GRPO — group-relative advantage estimation replacing PPO's critic. Used in DeepSeek-R1 reasoning post-training; widely adopted in OSS reasoning RLHF.
- Accelerate (Hugging Face) T1
Hugging Face's abstraction over distributed-training backends (DDP, FSDP, DeepSpeed, Megatron). Minimal code change to scale a PyTorch script.
- Argilla T2
Open-source data-quality platform for LLM training data — human-in-the-loop labelling, RLHF data collection, dataset curation. Acquired by Hugging Face 2024.