--- title: "futureagi-sdk vs MixEval" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-futureagi-sdk-vs-jinjieni-mixeval" tools: ["future-agi-futureagi-sdk", "jinjieni-mixeval"] --- # futureagi-sdk vs MixEval *GraphCanon updated Jul 12, 2026* ## Verdict Pick futureagi-sdk when requirements: Supports Python and TypeScript languages; Automated evaluations with sub-100ms guardrails; pick MixEval when tags unique to MixEval: large language model, benchmarking-suite, benchmark, benchmark-mixture. [futureagi-sdk](https://app.futureagi.com) reports 48 GitHub stars, 5 forks, and 3 open issues, last pushed Jul 8, 2026. [MixEval](https://mixeval.github.io/) has 254 stars, 40 forks, and 7 open issues, last pushed Nov 10, 2024. Figures are from public GitHub metadata via [futureagi-sdk's repository](https://github.com/future-agi/futureagi-sdk) and [MixEval's repository](https://github.com/JinjieNi/MixEval). | | [futureagi-sdk](/tools/future-agi-futureagi-sdk.md) | [MixEval](/tools/jinjieni-mixeval.md) | | --- | --- | --- | | Tagline | Production-grade AI evaluation, prompt management & observability SDK | The official evaluation suite and dynamic data release for MixEval. | | Stars | 48 | 254 | | Forks | 5 | 40 | | Open issues | 3 | 7 | | Language | Python | Python | | Adopt for | Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. | - | | Persona | - | - | | Runtime | - | - | | License | The Future AGI SDK uses the Apache License, Version 2.0 (Apache-2.0). It allows users to freely use, modify, and distribute the software while maintaining copyright notices. | - | | Categories | Evaluation & Observability | LLM Frameworks, Inference & Serving, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [futureagi-sdk](/tools/future-agi-futureagi-sdk.md) | [MixEval](/tools/jinjieni-mixeval.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 3d | 608d | | Open issues (now) | 3 | 7 | | Owner type | Organization | User | | Security scan | No lockfile | 109 low (109 low) | | Full report | [trust report](/tools/future-agi-futureagi-sdk/trust.md) | [trust report](/tools/jinjieni-mixeval/trust.md) | ## Decision facts: futureagi-sdk - **Requirements:** Supports Python and TypeScript languages; Automated evaluations with sub-100ms guardrails - **Adopt for:** Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. - **License detail:** The Future AGI SDK uses the Apache License, Version 2.0 (Apache-2.0). It allows users to freely use, modify, and distribute the software while maintaining copyright notices. ## Choose when ### Choose futureagi-sdk if… - Requirements: Supports Python and TypeScript languages; Automated evaluations with sub-100ms guardrails. - Tags unique to futureagi-sdk: development, dataset, machine-learning, annotations. - Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. ### Choose MixEval if… - Tags unique to MixEval: large language model, benchmarking-suite, benchmark, benchmark-mixture. - Also covers LLM Frameworks, Inference & Serving. - More GitHub stars (254 vs 48) - visibility, not fit. ## When NOT to use futureagi-sdk - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## When NOT to use MixEval - Last GitHub push was 609 days ago (dormant maintenance, Nov 10, 2024). Validate activity before betting a new project on MixEval. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## Common questions ### What is the difference between futureagi-sdk and MixEval? futureagi-sdk: Production-grade AI evaluation, prompt management & observability SDK. MixEval: The official evaluation suite and dynamic data release for MixEval.. See the comparison table for live GitHub stats and shared categories. ### When should I choose futureagi-sdk over MixEval? Choose futureagi-sdk over MixEval when Requirements: Supports Python and TypeScript languages; Automated evaluations with sub-100ms guardrails; Tags unique to futureagi-sdk: development, dataset, machine-learning, annotations; Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. ### When should I choose MixEval over futureagi-sdk? Choose MixEval over futureagi-sdk when Tags unique to MixEval: large language model, benchmarking-suite, benchmark, benchmark-mixture; Also covers LLM Frameworks, Inference & Serving; More GitHub stars (254 vs 48) - visibility, not fit. ### When should I avoid futureagi-sdk? Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### When should I avoid MixEval? Last GitHub push was 609 days ago (dormant maintenance, Nov 10, 2024). Validate activity before betting a new project on MixEval. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### Is futureagi-sdk or MixEval more popular on GitHub? MixEval has more GitHub stars (254 vs 48). Stars measure visibility, not whether either tool fits your constraints. ### Are futureagi-sdk and MixEval open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to futureagi-sdk or MixEval? GraphCanon lists graph-backed alternatives at [futureagi-sdk alternatives](/tools/future-agi-futureagi-sdk/alternatives) and [MixEval alternatives](/tools/jinjieni-mixeval/alternatives) ([futureagi-sdk markdown twin](/tools/future-agi-futureagi-sdk/alternatives.md), [MixEval markdown twin](/tools/jinjieni-mixeval/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/future-agi-futureagi-sdk-vs-jinjieni-mixeval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, futureagi-sdk or MixEval? futureagi-sdk: Very active. MixEval: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for futureagi-sdk and MixEval? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [futureagi-sdk trust report](/tools/future-agi-futureagi-sdk/trust); [MixEval trust report](/tools/jinjieni-mixeval/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-futureagi-sdk`](/api/graphcanon/graph?tool=future-agi-futureagi-sdk) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_