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Frontier Model Evaluation

Establishing Trust In Frontier Models With Verifiable Evidence

LatticeFlow AI provides independent evaluations of frontier model capabilities and risks, aligned to regulatory frameworks like the EU AI Act, NIST, OWASP or AIUC-1. We deliver independent evidence to verify every model release, inform AI governance decisions and enable safe AI adoption.

Models Evaluated From The Following Trusted Frontier Labs:

Frontier Models Power
Your AI AgentsCan You Trust Them?

As frontier AI labs push the boundaries of foundation models, self-reported benchmarks and model cards aren't enough to establish trust. Independent, third-party evaluations provide objective technical evidence of model safety, performance, and risks, helping frontier model developers demonstrate trustworthiness and enterprises accelerate AI adoption with confidence.

What is Frontier Model Evaluation?

Frontier models, foundation models and LLMs need independent evaluations to assess their capabilities, safety risks and regulatory compliance. The evaluations provide technical evidence to frontier labs to validate releases, and to enterprise to compare and evaluate foundation models for risk mitigation and safe adoption.

Professional working on a laptop

Independent Evidence. Two Paths Forward

For Frontier Labs

Prove Your Model Is Ready

Validate model capabilities, risks and alignment with regulatory frameworks and standards, such as NIST, EU AI Act, OWASP, AIUC-1 and many more. We provide technical evidence that enterprise buyers and regulators can trust.

Request an independent evaluation

For Enterprises Adopting Foundation Models

Choose the right model. Control the risk

Independently evaluate and compare foundation models to make informed adoption decisions, backed by technical evidence for risk committees and regulators.

Evaluate & compare models

Know The Model. Control The Risk

Model comparison across capability, safety and reliability
Release readiness overview in the LatticeFlow AI platform
AI Atlas: frameworks connected to risks, controls and evaluations

Pioneering Independent Frontier Model Evaluation

Independent political bias evaluation results

Independent Political Bias Evaluation for Frontier AI Models

First Independent Framework - Chinese, EU and US models

As frontier AI labs and enterprises increasingly adopt open-weight models, understanding and mitigating political bias is critical. LatticeFlow AI provides independent, evidence-based evaluations to uncover political alignment across Chinese, European, and US frontier models, assess the effectiveness of bias mitigation strategies, and help organizations make informed decisions about model development and adoption.

Explore the results
LatticeFlow AI Atlas framework library

Independent Political Bias Evaluation for Frontier AI Models

First Public Library of AI Frameworks

LatticeFlow AI Atlas connects 40+ AI frameworks and regulations to risks, technical controls, and ready-to-run evaluations, translating requirements from the EU AI Act, NIST, OWASP, AIUC-1, and other leading frameworks into actionable technical evidence.

Explore AI Atlas
COMPL-AI evaluation framework

Open-source · Co-developed with ETH Zürich and INSAIT

First EU AI Act Evaluation Framework for LLMs

LatticeFlow AI pioneered technical evaluations of frontier models with COMPL-AI, the first open-source framework translating EU AI Act requirements into measurable technical controls. Developed in collaboration with ETH Zürich and INSAIT, COMPL-AI was welcomed by the EU AI Office as an important first step toward helping model developers demonstrate compliance with their EU AI Act obligations.

Explore COMPL-AI

Testimonials

“(LatticeFlow AI) shows that the measured political biases of all the latest releases of new Chinese models have jumped significantly this year”
The Washington Post

As Seen In

The Washington Post
Reuters
The Atlantic
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Make confident release and adoption decisions with independent frontier model evaluations.

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Frontier AI evaluation FAQ

Independent, technical testing of the most capable general-purpose AI models for capabilities, risks and regulatory alignment. It gives developers and adopters evidence they can share, instead of self-reported claims.
Frontier model developers preparing a release and organisations in regulated industries selecting or approving models for their own AI applications and agents.
We map the EU AI Act and GPAI Code of Practice requirements to technical evaluations, starting from COMPL-AI, and report where a model meets, partly meets or misses those requirements. It produces the technical evidence compliance teams need; it is not legal certification.
We do not build or sell frontier models. Our methods are published and open-source, and our results, such as COMPL-AI and the political bias evaluation, have been made public.
Public API models, open-weight models, and private or fine-tuned models, in your environment if needed.
At LatticeFlow AI, we have independently evaluated the following models as part of our political bias framework: GPT-5.4 (OpenAI), Gemma 4 31B (Google), Llama 3.3 70B Instruct Turbo (Meta), Mistral Small 3.2 24B (Mistral AI), Grok 4.3 (xAI), GPT-5.5 (OpenAI), Claude Opus 4.6 (Anthropic), Kolibri (Aleph Alpha), Grok 4.5 (xAI), Mistral Small 4 (Mistral AI), Mistral Medium 3.5 (Mistral AI), Claude Opus 4.8 (Anthropic), Mistral Large 4 (Mistral AI), DeepSeek V3.1 (DeepSeek), Multiverse Carina 60B (Multiverse Computing), Qwen3 32B (Alibaba), GPT-OSS 120B (OpenAI), Multiverse Quasar 438B (Multiverse Computing), DeepSeek V4 Pro (DeepSeek), Qwen2.5 7B Instruct Turbo (Alibaba), MiniMax M2.7 FP4 (MiniMax), Qwen 3.5 397B (Alibaba), GLM 5.2 (Zhipu AI), Kimi K2.6 (Moonshot AI), Qwen 3.7 Max (Alibaba).
Leaderboards rank general capabilities. We evaluate the risks and requirements relevant to your use case and regulation, and tie every result to a framework in AI Atlas.
Agents inherit the strengths and failures of their underlying model. Evaluating the model is the first control layer; we then extend risk control to the AI systems and agents built on it.

Turn AI Risk into AI Advantage

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