vioscale
Comparison

MLflow vs Together AI

No clear leader: MLflow (76.2) and Together AI (72.8) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.

MLflow full profile →Together AI full profile →
Machine formatsJSONMarkdownGraphQLor send Accept: application/json
MLflow76
Together AI73
Score
Vioscale score
MLflow76 / 100medium · 63%
Together AI73 / 100medium · 60%
Pricing
Free tier
MLflow✓
Together AI✗
Model
MLflowcommercial
Together AIcommercial
Price level
MLflowfree
Together AIlow
Starting price
MLflow–
Together AI$0.00
Transparent
MLflow✓
Together AI✓
Integrations
Count
MLflow15
Together AI–
Security
Disclosure policy
MLflow–
Together AI✓
Gdpr
MLflow–
Together AI✓
Iso27001
MLflow–
Together AI✓
Scorecard
MLflow5.5
Together AI–
Soc2
MLflow–
Together AI✓
Vulnerabilities
Reliability
Sla pct
MLflow–
Together AI99
Status page
MLflow–
Together AI✓
Adoption
Dependent repos
MLflow5,089
Together AI–
Github stars
MLflow27,687
Together AI–
Package downloads weekly
MLflow9,993,245
Together AI–
Activity
Commits last 30d
MLflow100
Together AI–
Release
Cadence days
MLflow10
Together AI–
History
MLflow20 items
Together AI–
License
Spdx
MLflowApache-2.0
Together AI–
Language
Primary
MLflowPython
Together AI–
Market
Availability

Capabilities

Feature-by-feature on the axes that matter for mlops & llmops tools. “-” means undocumented, not absent.

Core
Tool role
MLflowEnd-to-end ML platform
Together AIEnd-to-end ML platform
Deployment
Self-hostable / OSS core
MLflow✓
Together AI✗
Managed cloud available
MLflow✓
Together AI✓
On-prem / VPC deployment
MLflow✓
Together AI✓
Observability
LLM tracing / observability
MLflow✓
Together AI✗
Evaluation (offline / LLM-judge / human)
MLflow✓
Together AI✗
Dev
Prompt management + versioning
MLflow✓
Together AI✗
Tracking
Experiment tracking / model registry
MLflow✓
Together AI✗
Serving
Model serving / inference endpoint
MLflow✓
Together AI✓
Interop
OpenTelemetry / OpenLLMetry compatible
MLflow✓
Together AI✗
Framework-agnostic
MLflow✓
Together AI✓
Gateway
Multi-provider model support
MLflow✓
Together AI✓
Data
No-train-on-customer-data guarantee
MLflow-
Together AIYes

What each one is

The product in its own terms, so the numbers below have context.

MLflow

A comprehensive, open-source platform that provides experiment tracking, model registry, LLM tracing, prompt management, and deployment capabilities across the complete machine learning and AI lifecycle

Independently observed

Together AI

Together AI provides cloud infrastructure for hosting and serving open-source language, image, audio, and video models through serverless inference, reserved capacity, and dedicated GPU instances. The platform includes fine-tuning capabilities, batch processing, managed storage, and GPU cluster support for custom model development and training—eliminating the need for users to manage underlying infrastructure.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

MLflow

Open sourceFree tier
as of verify ↗

Together AI

from $0.00/tokensUsage-based

Usage-based pricing starting from $0.00014/1M tokens for serverless inference. Reserved capacity and dedicated GPU instances available; on-demand GPU pricing from $3.69/hour.

  • Serverless InferenceFrom $0.00014–$15/1M tokens depending on model. Pay only for usage.
    • 50+ open-source models
    • Variable pricing by model and token type
    • Batch API support
    • Private endpoints
  • Provisioned ThroughputReserved throughput capacity with 99% SLA. PTU-based pricing structure.
    • Reserved token capacity
    • 99% uptime SLA
    • Token-based pricing model
    • Production-grade reliability
  • Dedicated Inference$3.69–$8.99 per GPU per hour (on-demand); reserved discounts available.
    • Single-tenant GPU instances
    • Guaranteed performance (no resource sharing)
    • Custom model support
    • Autoscaling for traffic spikes
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
MLflow✓
Together AI✓
CLI
MLflow✓
Together AI✓
Deployment
Cloud / SaaS
MLflow✗
Together AI✓
Self-hosted
MLflow✓
Together AI✗
On-premise
MLflow✓
Together AI✗

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

MLflow

28 total
  • Databricks
  • AWS S3
  • Google Cloud Storage
  • Azure Storage
  • AzureML
  • Kubernetes
  • LangChain
  • Pydantic AI
  • Anthropic Claude
  • OpenAI
  • Google Gemini
  • SAP AI Core
  • JFrog
  • Aliyun
  • PostgreSQL
  • MySQL
  • MSSQL
  • Claude Code
  • OpenAI Codex
  • Gemini
  • Anthropic
  • Ollama
  • OpenClaw
  • Qwen Code
  • +4 more
Independently observed

Together AI

Not documented yet.

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.