BenchLLM Alternatives

Test and evaluate LLM-powered apps with flexible evaluation methods, automated testing, and insightful reports, ensuring seamless integration and performance monitoring.
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HoneyHive

If you're looking for a replacement to BenchLLM, HoneyHive is a good contender. It's a full-featured AI evaluation, testing, and observability platform geared for teams building GenAI apps. HoneyHive offers automated CI testing, production pipeline monitoring, dataset curation and prompt management, as well as automated evaluators and human feedback collection. It supports more than 100 models through popular GPU clouds, and offers a free Developer plan for solo developers and researchers.

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Langtail

Another contender is Langtail, which is geared toward making it easier to build AI-powered apps. It includes tools for debugging, testing and deploying LLM prompts, including fine-tuning prompts with variables, running tests to avoid unexpected behavior, and deploying prompts as API endpoints. Langtail also includes a no-code playground and adjustable parameters for easier collaboration to develop and test AI apps. It comes in three pricing tiers, including a free option for small businesses and solopreneurs.

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Deepchecks

Deepchecks is another option. The tool automates evaluation and helps spot problems like hallucinations and bias in LLM apps. It uses a "Golden Set" approach for rich ground truth and includes features like automated evaluation, LLM monitoring, debugging and custom properties for more advanced testing. Deepchecks comes in several pricing tiers, including a free Open-Source option, so it should be useful for many development needs.

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Promptfoo

For those who like a command-line interface, Promptfoo is a simple YAML-based configuration system for evaluating LLM output quality. It supports multiple LLM providers and lets you customize evaluation metrics. Promptfoo is geared for developers and teams that need to maximize model quality and watch for regressions, with features like red teaming to try to find weaknesses and remediation advice.

More Alternatives to BenchLLM

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Humanloop

Streamline Large Language Model development with collaborative workflows, evaluation tools, and customization options for efficient, reliable, and differentiated AI performance.

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Parea

Confidently deploy large language model applications to production with experiment tracking, observability, and human annotation tools.

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Langfuse

Debug, analyze, and experiment with large language models through tracing, prompt management, evaluation, analytics, and a playground for testing and optimization.

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Keywords AI

Streamline AI application development with a unified platform offering scalable API endpoints, easy integration, and optimized tools for development and monitoring.

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Vellum

Manage the full lifecycle of LLM-powered apps, from selecting prompts and models to deploying and iterating on them in production, with a suite of integrated tools.

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Freeplay

Streamline large language model product development with a unified platform for experimentation, testing, monitoring, and optimization, accelerating development velocity and improving quality.

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Klu

Streamline generative AI application development with collaborative prompt engineering, rapid iteration, and built-in analytics for optimized model fine-tuning.

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LastMile AI

Streamline generative AI application development with automated evaluators, debuggers, and expert support, enabling confident productionization and optimal performance.

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LangWatch

Ensures quality and safety of generative AI solutions with strong guardrails, monitoring, and optimization to prevent risks and hallucinations.

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Airtrain AI

Experiment with 27+ large language models, fine-tune on your data, and compare results without coding, reducing costs by up to 90%.

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ACCELQ

Achieve codeless test automation across web, mobile, API, and desktop applications, scaling efforts easily with no coding expertise required.

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LangChain

Create and deploy context-aware, reasoning applications using company data and APIs, with tools for building, monitoring, and deploying LLM-based applications.

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Octomind

Automates end-to-end testing for web applications, discovering and generating Playwright tests, and auto-fixing issues, ensuring reliable and fast CI/CD pipelines.

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QA.tech

Automates software quality assurance through autonomous testing, providing fast feedback and confidence in app functionality with comprehensive memory and customizable tests.

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Baseplate

Links and manages data for Large Language Model tasks, enabling efficient embedding, storage, and versioning for high-performance AI app development.

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MonsterGPT

Fine-tune and deploy large language models with a chat interface, simplifying the process and reducing technical setup requirements for developers.

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ContextQA

Automates software testing, finding bugs and ensuring consistent user experiences across mobile devices, operating systems, and browsers, while reducing testing backlogs.

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Predibase

Fine-tune and serve large language models efficiently and cost-effectively, with features like quantization, low-rank adaptation, and memory-efficient distributed training.

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Prompt Studio

Collaborative workspace for prompt engineering, combining AI behaviors, customizable templates, and testing to streamline LLM-based feature development.

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LLMStack

Build sophisticated AI applications by chaining multiple large language models, importing diverse data types, and leveraging no-code development.