This reporting page is intentionally narrow. It focuses on currently tracked sourced factuality signals such as SimpleQA, HLE without tools, and multimodal factuality. It is a reporting page, not a mature weighted category.
This page ranks models using only sourced factuality benchmarks in the reporting family.
Bottom line: Factuality benchmarks are intentionally narrow — SimpleQA and HLE-no-tools are the primary signals. Claude Mythos Preview leads, but this category is still maturing.
According to BenchLM.ai, DeepSeek V4 Pro (Max) leads this ranking with a score of 57.9, followed by Claude Mythos Preview (56.8) and DeepSeek V4 Pro Base (55.2). The top three are separated by just a few points — any of them would perform well for this use case.
The best open-weight option is DeepSeek V4 Pro (Max) (ranked #1 with a score of 57.9). Open-weight models are highly competitive in this category — self-hosting is a viable alternative to proprietary APIs.
This ranking is based on provisional overall weighted scores across BenchLM.ai's scoring formula tracked by BenchLM.ai. For detailed model profiles, click any model name below. To compare two specific models head-to-head, use the "vs #" links.
DeepSeek V4 Pro (Max)
DeepSeek · 1M
Claude Mythos Preview
Anthropic · 1M
Best factuality score. Leads SimpleQA and HLE-no-tools.
DeepSeek V4 Pro Base
DeepSeek · 1M
Claude Mythos Preview leads factuality with the best SimpleQA and HLE-no-tools scores.
Gemini 3.1 Pro strong factuality for a non-reasoning model.
GPT-5.4 solid SimpleQA performance, especially on knowledge-heavy queries.
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The top model on this sourced reporting-family slice is DeepSeek V4 Pro (Max) by DeepSeek with an average of 57.9.
The best open-weight model is DeepSeek V4 Pro (Max) at position #1.
23 models are listed with sourced benchmark coverage in this reporting family.
This is a reporting family ranking, not a weighted category. It averages sourced factuality benchmarks to give a focused view of this capability.
Models must have sourced results on at least a quarter of the benchmarks in this family to be included. Coverage varies — a model with 2 benchmark scores is less reliable than one with 5.
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