EvalsHub vs Mastra: Which is Better in 2026?
A comprehensive comparison of EvalsHub and Mastra covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose EvalsHub if:
- →You want more affordable paid plans (from $39/mo)
- →You need natural-language rubrics with weights and thresholds or llm-as-a-judge scoring tailored to specific use cases
Choose Mastra if:
- →You need agents, tools, and workflows as typescript primitives or built-in observability: traces, metrics, and logs
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EvalsHub vs Mastra: At a Glance
Pricing Comparison: EvalsHub vs Mastra
Understanding the pricing differences between EvalsHub and Mastra is crucial for making the right choice. Here's how their plans compare side by side.
EvalsHub Pricing
Mastra Pricing
💡 Pricing takeaway: Both EvalsHub and Mastra offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from EvalsHub and Mastra stacks up.
What Makes Each Tool Unique
🔵 Unique to EvalsHub
Features available in EvalsHub but not in Mastra:
- ✓Natural-language rubrics with weights and thresholds
- ✓LLM-as-a-judge scoring tailored to specific use cases
- ✓Automatic regression detection and cross-model comparison
- ✓Red-team suite for prompt injection, jailbreaks and PII leakage
- ✓CI/CD integration and online auto-evals
- ✓AI-generated dataset rows and trace-span based experiments
🟣 Unique to Mastra
Features available in Mastra but not in EvalsHub:
- ✓Agents, tools, and workflows as TypeScript primitives
- ✓Built-in observability: traces, metrics, and logs
- ✓Evals, experiments, scorers, and datasets
- ✓Studio for collaborative iteration on agents
- ✓Server product for cloud deployment
- ✓Extensive learning material — course, books, templates, workshops
Use Case Recommendations
Best for: EvalsHub
EvalsHub is an AI quality-assurance platform built around LLM-as-a-judge scoring, aimed at teams still catching regressions through manual spot-checks. You define rubrics as natural-language criteria with weights and thresholds — accuracy matched against ground truth, hallucination held above a confidence bar — and evaluations run continuously against your data, comparing models and flagging regressions before a release rather than after a user finds them. Results are deterministic scores rather than impressions, which is the stated point: the site frames it as bringing traditional engineering rigour to generative output, so you can compare GPT-, Claude- and Llama-family responses on the same rubric and see which passed and which hallucinated. Alongside evaluation there is an adversarial testing surface that red-teams the model automatically: heuristic and LLM-based detection of prompt injection hidden in user input, stress testing against evolving persona-based jailbreaks and DAN-style bypasses, and verification of content filtering, PII leakage and internal policy compliance. Tracing, datasets and experiments are the underlying units — spans, AI-generated dataset rows, experiments and projects — and CI/CD integration puts the whole thing in the release path. Pricing is published in full: a genuinely usable free tier, a $39/mo Pro tier that unlocks red-teaming, A/B prompt tests, online auto-evals and custom LLM judges, and a scoped enterprise tier.
Ideal use cases:
- •Teams or individuals who need natural-language rubrics with weights and thresholds
- •Teams or individuals who need llm-as-a-judge scoring tailored to specific use cases
- •Teams or individuals who need automatic regression detection and cross-model comparison
- •Teams or individuals who need red-team suite for prompt injection, jailbreaks and pii leakage
- •Anyone focused on llm-evals workflows
- •Anyone focused on llm-as-judge workflows
Best for: Mastra
Mastra is a TypeScript framework for building AI agents and the applications around them, built by the team that previously created Gatsby. The core framework covers agents, tools, and workflows as first-class primitives, so a long-running agent is expressed in ordinary TypeScript rather than assembled from prompt strings and glue code. Around that framework sits a platform: observability with metrics, logs, and traces so agent runs are inspectable after the fact; evals, experiments, scorers, and datasets for measuring whether a change actually improved behavior; a Studio for collaborating on and iterating over agents; an Agent Builder; and a Server product that handles cloud deployment for agents. The company emphasizes agents that run for days rather than single-turn calls, which is what pushes the observability and scoring surface to the center of the product instead of leaving it as an add-on. Mastra is open source with roughly 26.7k GitHub stars and maintains a substantial learning surface — a quickstart, project templates, a video course, two books (Principles of Building AI Agents and Patterns of Building AI Agents), live workshops, and a weekly podcast — which makes it one of the more approachable entry points for JavaScript developers moving into agent work.
Ideal use cases:
- •Teams or individuals who need agents, tools, and workflows as typescript primitives
- •Teams or individuals who need built-in observability: traces, metrics, and logs
- •Teams or individuals who need evals, experiments, scorers, and datasets
- •Teams or individuals who need studio for collaborative iteration on agents
- •Anyone focused on typescript workflows
- •Anyone focused on agent framework workflows
🤖 Other AI Agent Infrastructure Tools to Consider
EvalsHub and Mastra aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is EvalsHub better than Mastra?
It depends on your needs. EvalsHub offers 6 key features including Natural-language rubrics with weights and thresholds and LLM-as-a-judge scoring tailored to specific use cases, while Mastra provides 6 features including Agents, tools, and workflows as TypeScript primitives and Built-in observability: traces, metrics, and logs. EvalsHub uses a freemium model with a free tier, while Mastra is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is EvalsHub cheaper than Mastra?
Both tools are similarly priced, starting at $39/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use EvalsHub and Mastra together?
Yes, many users combine EvalsHub and Mastra in their workflow. EvalsHub excels at natural-language rubrics with weights and thresholds, while Mastra shines with agents, tools, and workflows as typescript primitives. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between EvalsHub and Mastra?
While both are ai agent infrastructure tools, EvalsHub emphasizes natural-language rubrics with weights and thresholds, whereas Mastra is known for agents, tools, and workflows as typescript primitives. The best choice depends on your specific workflow and feature priorities.
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