Track, evaluate, and ship AI models and agents in one connected environment.
Estimated monthly website visits
Similarweb estimates for this domain, not active users. Only available observation months are shown; collection date is separate from the traffic period.
Collected Nov 11, 2026
This is our editors' assessment out of 5, not an average of user ratings. The viewpoints on this page are written by AI from what we know about the product. They are not customer reviews.
According to OpenAITools.app telemetry verified on 2026-11-11, Weights & Biases (CoreWeave Forge) (wandb.ai) is an AI platform indexed under AI Developer Tools generating 315.62K monthly visits with a month-over-month traffic delta of -1.28M (-80.2%). Its primary geographic market is United States (32.2% traffic share), and it operates on a Freemium, Contact for Pricing, Free pricing model. Top competing alternatives by monthly volume include Arize AI (249.03K visits/mo), Maxim AI (121.35K visits/mo), Confident AI (83.4K visits/mo).
Literally saved our team months of lost hyperparameter sweeps and debugging chaos.
CoreWeave rebrand confused us at first, but all our old runs and keys just worked.
Essential for tracking complex LLM agent evaluation runs.
UI feels a bit heavy when comparing thousands of runs simultaneously.
AI-synthesized perspectives grounded in live site inspection, pricing structure, and category benchmarks — presented as editorial viewpoints rather than individual customer testimonials.
Log metrics, losses, and media from training runs and compare them side by side in interactive charts to spot what actually improves your model.
Run automated hyperparameter sweeps and visualize parameter importance so you can converge on better configurations faster.
Version datasets and model artifacts, track lineage, and promote models through a registry from training to production.
Build, log, and evaluate LLM prompts and applications, with tracing and evaluation tools grouped under an LLMOps workflow.
Ship AI applications and agents in one connected environment that spans tracking, serving, and cloud infrastructure.
Share runs, dashboards, and reports with teammates so results and findings stay reproducible across the team.
Weights & Biases (W&B) has long been the go-to toolkit for machine learning teams that need to see what their models are doing. Following its integration into CoreWeave, the platform now operates as CoreWeave Forge while keeping the same core capabilities — and, importantly, existing W&B credentials continue to work, so current users can sign in and access their projects and data as before.
The platform spans the full AI development loop. During training you log metrics, losses, and sample media and compare hundreds of runs in interactive dashboards. You can launch automated hyperparameter sweeps, version datasets and model artifacts, and manage promotion through a model registry. For generative AI work, the same environment provides prompt logging and evaluation plus tracing for LLM applications, covering the LLMOps side of the workflow.
Because it is now part of CoreWeave Forge, W&B sits in a broader connected environment that also covers compute and serving, letting teams run models and agents without stitching together separate tools. It is widely used across research, ML engineering, and applied AI teams, from solo practitioners on the free tier to enterprise organizations with governance and scale requirements.
Compare training runs, launch sweeps, and visualize metrics to train better models faster.
Log prompts, run evaluations, trace generations, and monitor LLM applications in production.
Version datasets and artifacts and promote models through a registry for reproducible, auditable work.
Give stakeholders shared dashboards and reports that show model performance and experiment history.
Side-by-side telemetry comparison of competing AI tools in the same primary category
| Rank | AI Tool | Monthly Visits | MoM Growth | Direct traffic share | Pricing | Head-to-Head |
|---|---|---|---|---|---|---|
| ● | Weights & Biases (CoreWeave Forge) | 315.62K | -80.2% | 73% direct | Freemium, Contact for Pricing, Free | Current |
| 1 | Arize AI Provides deep production LLM observability and tracing, focusing heavily on debugging production failures and drift. | 249.03K | +3.2% | 43% direct | Paid, Contact for Pricing | vs Arize AI |
| 2 | Maxim AI Offers robust LLM evaluation and testing suites with integrated enterprise gateways, prioritizing prompt benchmarking. | 121.35K | +10% | 32% direct | Contact for Pricing, Free Open Source | vs Maxim AI |
| 3 | Confident AI Specializes in automated LLM unit testing and security red-teaming, though less focused on traditional MLOps experiment tracking. | 83.4K | -3.3% | 35% direct | Freemium, Paid, Contact for Pricing | vs Confident AI |
| 4 | PromptLayer Focuses specifically on prompt versioning, collaborative CMS management, and agent tracing rather than general MLOps. | 85.9K | -4.6% | 16% direct | Free Trial, Contact for Pricing | vs PromptLayer |
| 5 | honeyhive.ai Combines agent tracing with offline experimentation and dataset evaluation, geared toward production agent workflows. | 8.84K | -52.5% | 79% direct | Freemium, Contact for Pricing | vs honeyhive.ai |
| 6 | ClearML Delivers an open-source end-to-end MLOps suite for GPU infrastructure and experiment tracking, with broader infrastructure control. | 20.12K | -60.9% | 33% direct | Contact for Pricing | vs ClearML |
Free / Open-sourceProvides deep production LLM observability and tracing, focusing heavily on debugging production failures and drift.
Free / Open-sourceProvides deep production LLM observability and tracing, focusing heavily on debugging production failures and drift.
Free / Open-sourceOffers robust LLM evaluation and testing suites with integrated enterprise gateways, prioritizing prompt benchmarking.
Free / Open-sourceOffers robust LLM evaluation and testing suites with integrated enterprise gateways, prioritizing prompt benchmarking.
Specializes in automated LLM unit testing and security red-teaming, though less focused on traditional MLOps experiment tracking.
Specializes in automated LLM unit testing and security red-teaming, though less focused on traditional MLOps experiment tracking.
Focuses specifically on prompt versioning, collaborative CMS management, and agent tracing rather than general MLOps.
Focuses specifically on prompt versioning, collaborative CMS management, and agent tracing rather than general MLOps.
Combines agent tracing with offline experimentation and dataset evaluation, geared toward production agent workflows.
Combines agent tracing with offline experimentation and dataset evaluation, geared toward production agent workflows.
Free / Open-sourceDelivers an open-source end-to-end MLOps suite for GPU infrastructure and experiment tracking, with broader infrastructure control.
Free / Open-sourceDelivers an open-source end-to-end MLOps suite for GPU infrastructure and experiment tracking, with broader infrastructure control.
Free / Open-sourceProvides an open-source workspace specifically for prompt experimentation, LLM evaluation, and agent deployment pipelines.
Free / Open-sourceProvides an open-source workspace specifically for prompt experimentation, LLM evaluation, and agent deployment pipelines.
SpecialistFeatures simulation and guardrail tools for testing LLM safety and robustness before production deployment.
SpecialistFeatures simulation and guardrail tools for testing LLM safety and robustness before production deployment.
SpecialistCollaborative platform to build, test, and monitor LLM features
SpecialistCollaborative platform to build, test, and monitor LLM features
SpecialistThe simulation platform for agent self-improvement
SpecialistThe simulation platform for agent self-improvement
SpecialistEnterprise platform for building, evaluating and shipping AI agents
Free / Open-sourceRun and build with open AI models locally or in the cloud
Free / Open-sourceRun and build with open AI models locally or in the cloud
