MosaicML
MosaicML
What is MosaicML?
Train and serve large models efficiently with Databricks Mosaic AI practices
Key Capabilities
What makes MosaicML powerful
Efficiency recipes
Adopt tested settings for optimization sharding and memory that raise throughput and reduce dollars per token.
Streaming data
Ingest curate and dedupe corpora continuously so training sets stay fresh and high quality.
Optimized inference
Use quantization and tuned runtimes with autoscaling to meet latency budgets reliably.
Lineage and policy
Attach governance lineage and controls so ML systems satisfy security and compliance teams.
Professional Integration
These capabilities work together to provide a comprehensive AI solution that integrates seamlessly into professional workflows. Each feature is designed with enterprise-grade reliability and performance.
Key Features
What makes MosaicML stand out
- Efficiency recipes: Apply proven training and finetuning settings that cut cost while preserving quality targets
- Data pipelines: Use curation deduplication and streaming so corpora stay fresh and clean over time
- Observability: Monitor throughput memory and loss to tune training jobs across clusters
- Inference stack: Deploy with quantization optimized runtimes and autoscaling for latency and cost
- Governance: Leverage Databricks lineage access control and compliance tooling for ML at scale
- Reproducibility: Package experiments and artifacts so results are auditable and portable
- Model choice: Support open models and organization specific checkpoints as needed
- Expert support: Work with solution engineers to land production systems safely
Use Cases
How MosaicML can help you
- Migrate research code into governed production pipelines
- Pretrain or finetune domain models with lower compute cost
- Build streaming datasets that remain deduped and clean
- Set up evaluation harnesses to track objective metrics
- Serve models with latency and autoscaling targets
- Run ablations on optimizers and memory settings
- Quantize and pack models to reduce inference spend
- Adopt audit trails for compliance and finance teams
Perfect For
ml platform leads, research engineers, data engineers, architects, and FinOps stakeholders building efficient training and inference on Databricks
Pricing
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Starting price
Quick Information
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Frequently Asked Questions
How is MosaicML offered today?
Can we bring our own models and data?
How does it lower training cost?
Is inference supported or training only?
What compliance options exist?
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