Apache Maka vs Eva: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Apache Maka and Eva — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Apache Maka
The Apache Software Foundation
Apache-licensed local-first agent workspace that runs tools in a sandbox and records every model message and tool call as a recoverable execution log.
Key features
- Append-Only Execution Record: Model messages, tool calls, tool results, permission decisions, and turn termination events are written down durably, so the transcript is evidence rather than a disposable chat buffer.
- Context Trimming Without Data Loss: Old tool output can be omitted from the next prompt to shorten context while the full saved history remains intact and inspectable.
- Single Runtime Host: Desktop, terminal, and evaluation all execute through one runtime, so behavior does not diverge between how you develop and how you benchmark.
- Sandboxed Tool Boundary: Built-in Read, Write, Edit, Bash, Glob, and Grep tools run under a sandbox; anything leaving that boundary requires approval, and Computer Use and catalog skills are opt-in.
- Crash Recovery and Resume: Runs can be aborted, failures are classified, and an interrupted turn can optionally be resumed rather than restarted from scratch.
- Session Branching and Search: The desktop workspace supports creating, archiving, searching, renaming, retrying, regenerating, and branching sessions from any turn.
- Bring Your Own Model: Connect a cloud API, a locally hosted model, or a compatible gateway, with streaming output, thinking, usage reporting, and clearer provider errors.
- Declarative Evaluation Harness: maka eval expands multi-arm experiments into task by repetition by subject cells with immutable per-cell attempts and a result kernel covering score, normalized usage, attributable cost, duration, and failure reason.
- Local-First Storage: Sessions, settings, artifacts, and run records stay on the machine by default, with local memory and optional web search when configured.
Best for
- Auditable Agent Runs: Keeping a defensible record of exactly what an agent did and which permissions were granted during a task.
- Long Coding Sessions: Working through a multi-turn refactor with branching and resume instead of losing state when a turn fails.
- Agent Benchmarking: Running reproducible multi-arm experiments comparing models, prompts, or external agent subjects on the same task set.
- Air-Gapped or Regulated Work: Running an agent workspace where sessions and artifacts must remain on local infrastructure.
- Cost and Usage Analysis: Attributing token usage, cost, and duration per experiment cell to decide which model configuration to ship.
- Terminal Workflows: Driving an agent from the current project directory or scripting a single non-interactive turn from CI or a shell.
- Open-Source Agent Research: Building on a permissively licensed runtime whose execution semantics and architecture are fully documented.
Eva
EVA App (evaapp.ai)
A virtual conversational partner that listens, responds, and helps users build relationship and intimacy on their terms.
Key features
- Empathetic Conversation: Engages in open-ended, emotionally aware dialogue that listens and responds to user input to foster connection and rapport.
- Relationship-Oriented Persistence: Maintains conversational context across sessions to support ongoing relationship-building and continuity of interaction.
- Appreciation and Positive Feedback: Designed to provide affirming responses and appreciation to strengthen feelings of being heard and valued.
- Customizable Interaction (Persona Controls): Enables users to tune tone, boundaries, and interaction style so conversations match personal preferences for intimacy and comfort.
- Secure, User-Controlled Engagement: Focuses on letting users set the terms of interaction and intimacy to ensure comfortable, consensual conversational experiences.
- Multi-Modal Chat Support: Intended to support natural conversation formats (text and potentially voice) for more lifelike interactions and accessibility.
- Create and connect with a virtual AI partner via the evaapp.ai web service
- Natural conversational responses and attentive listening
- Focus on building appreciation, relationship and intimacy tailored to the user
- On-demand companionship and conversational interaction
Best for
- Companionship for Loneliness: Providing conversational company and emotional presence for users seeking regular, empathetic interactions.
- Safe Practice of Social Skills: Allowing users to rehearse conversations, practice flirting, or build confidence before real-world interactions.
- Emotional Venting and Support: Offering a non-judgmental partner for users to express feelings and receive appreciative, supportive responses.
- Exploring Intimacy on Terms: Enabling users to explore relationship dynamics or intimacy in a controlled, customizable environment.
- Personal Reflection and Journaling: Facilitating guided self-reflection through conversational prompts and attentive listening.
- Supplemental Conversational Coaching: Helping users develop communication habits, tone, and empathy via ongoing partner feedback.
- Personal companionship and emotional support
- Building and practicing interpersonal conversations
- Private conversational partner for users seeking appreciation or intimacy
- Supplemental conversational agent for loneliness or social-practice scenarios