What separates a useful AI model from a dangerous one isn’t just raw intelligence — it’s whether you can trust what it tells you. Hallucination, the tendency of AI models to confidently state things that are false, remains one of the biggest obstacles to deploying AI in high-stakes settings like healthcare, law, and finance.
The AA-Omniscience Index, developed by independent AI benchmarking firm Artificial Analysis, is one of the most rigorous tools available for measuring exactly this. Spanning 6,000 questions across 42 economically relevant topics — from business and law to health and software engineering — the benchmark rewards correct answers, penalizes hallucinations, and assigns no penalty for abstaining. Scores range from -100 to 100; a score of zero means a model answers correctly as often as it answers incorrectly. In March 2026, very few models manage to post a meaningfully positive score. Below, we rank the 10 most factual AI models currently available, according to the latest AA-Omniscience data.
1. Gemini 3.1 Pro Preview (Google)
AA-Omniscience Score: 33
Google’s Gemini 3.1 Pro Preview is currently the most factual AI model on the planet by a considerable margin, posting an AA-Omniscience score of 33 — more than double the score of the second-place model. Built by Google DeepMind, it also holds the top spot on the overall Artificial Analysis Intelligence Index v4.0 with a score of 57, and it gets there at a cost roughly half that of its nearest rivals from OpenAI and Anthropic. What makes the Gemini 3.1 Pro Preview particularly noteworthy as the most factual AI model is how it achieved its Omniscience score: not just through higher raw accuracy (53%), but through a dramatic 38-percentage-point reduction in hallucination rate compared to its predecessor, Gemini 3 Pro Preview. It does make sense for Google to have a factually-accurate model, given its Google search roots, and Gemini 3.1 Pro Preview does manage to do that. It is priced at $2 per million input tokens and $12 per million output tokens, making it a compelling option for enterprises that need reliable, high-volume factual outputs.
2. Claude Opus 4.6 — Max Reasoning (Anthropic)
AA-Omniscience Score: 14
Anthropic’s Claude Opus 4.6 in its maximum reasoning configuration is the second most factual AI model available today, scoring 14 on the AA-Omniscience Index. Released in February 2026, Opus 4.6 is Anthropic’s current flagship model and represents a substantial leap over its predecessor, Opus 4.5. It was the first Opus-class model to ship with a one-million-token context window in beta, enabling it to work through large codebases, lengthy legal documents, and complex enterprise datasets in a single session. On BrowseComp, which measures agentic search accuracy, Opus 4.6 scored 84.0% — significantly higher than any competing model at launch. As a most factual AI model contender, it is particularly strong in domains like law and software engineering, where Anthropic’s models have historically led the Omniscience leaderboard. It is available via claude.ai and the Anthropic API at $5 per million input tokens.
3. Claude Sonnet 4.6 — Max Reasoning (Anthropic)
AA-Omniscience Score: 12
Claude Sonnet 4.6 at maximum reasoning effort comes in tied for third on the most factual AI model rankings, also scoring 12. Like its sibling Opus 4.6, it is built by Anthropic — the San Francisco-based AI safety company — and reflects the company’s consistent emphasis on calibration and low hallucination rates. Sonnet 4.6 occupies a middle tier in Anthropic’s lineup, sitting between the more powerful Opus and the lighter Haiku, but at maximum reasoning effort it matches Gemini 3 Flash’s factual reliability while offering Anthropic’s characteristically high token efficiency. It scores 52 on the overall Artificial Analysis Intelligence Index and is generally regarded as one of the most cost-effective options for factual, knowledge-intensive tasks where organizations want the Anthropic trust profile without paying full Opus pricing.
4. Gemini 3 Flash (Google)
AA-Omniscience Score: 12
Also scoring 12 on the AA-Omniscience Index, Gemini 3 Flash is the second Google model in the top four, and its presence here is a remarkable achievement for a model in its class. Google DeepMind designed Gemini 3 Flash as a faster, more efficient alternative to Gemini 3 Pro — intended for latency-sensitive workloads — yet it still ranks as one of the most factual AI models across the entire landscape. Gemini 3 Flash outputs at a blistering 128 tokens per second, making it one of the fastest models in the top tier of the Intelligence Index. The fact that it matches much heavier reasoning models on factual reliability while maintaining lower operational costs makes it especially attractive for real-time applications in legal research, customer support, and automated fact-checking pipelines.
5. GPT-5.3 Codex — xHigh Reasoning (OpenAI)
AA-Omniscience Score: 10
GPT-5.3 Codex from OpenAI, run at its highest reasoning effort, is the fifth most factual AI model in the current rankings with a score of 10. OpenAI launched GPT-5.3 Codex in February 2026, describing it as “the most capable agentic coding model to date” and revealing that it was the first model instrumental in creating itself — the Codex team used early versions of the model to debug its own training and manage its deployment. While Codex is primarily positioned as a coding and agent model, its factual reliability at high reasoning effort is competitive with the best general-purpose models. It scores 54 on the Artificial Analysis Intelligence Index overall and has particular strengths in software engineering domains, where knowledge precision is critical. Its deployment via ChatGPT’s Codex interface, as well as via the API, makes it widely accessible.
6. GPT-5.4 — xHigh Reasoning (OpenAI)
AA-Omniscience Score: 6
GPT-5.4, OpenAI’s latest general-purpose flagship, scores 6 on the AA-Omniscience Index at its highest reasoning effort — placing it sixth among the most factual AI models. Released in early March 2026, GPT-5.4 is OpenAI’s first general-purpose model with native computer-use capabilities and is positioned as the company’s most accurate release to date. OpenAI says individual factual claims in GPT-5.4 are 33% less likely to be false compared to GPT-5.2, and full responses are 18% less likely to contain any errors. On the Artificial Analysis Intelligence Index, GPT-5.4 is tied with Gemini 3.1 Pro Preview at 57 — the first time a new OpenAI frontline model has failed to push past the existing leader. It is priced at $2.50 per million input tokens and $15 per million output tokens.
7. Grok 4.0 (xAI)
AA-Omniscience Score: 4
Grok 4.0 from Elon Musk’s xAI earns a score of 4 on the AA-Omniscience Index, making it the seventh most factual AI model. Grok 4 was released in mid-2025 and made a significant impact on the AI landscape, briefly topping several major benchmarks at launch — including achieving a perfect 100% on the AIME mathematics competition with its Heavy variant. xAI designed Grok 4 as a reasoning-first model with a 2-million-token context window, which is among the largest available at the frontier. As a most factual AI model pick, Grok 4 performs particularly well in Health and Science, Engineering & Mathematics domains on the Omniscience benchmark. Its hallucination rate is higher than the Anthropic models above it, but the sheer breadth of its knowledge base — partially attributable to its integration with X (formerly Twitter) data — contributes to its overall positive score.
8. Claude Opus 4.6 — Standard (Anthropic)
AA-Omniscience Score: 3
The standard (non-maximum-reasoning) configuration of Claude Opus 4.6 also makes the list, scoring 3 on the AA-Omniscience Index. This entry underscores Anthropic’s consistent focus on factual calibration across reasoning modes — even without extended reasoning enabled, Opus 4.6 remains a most factual AI model option. The non-reasoning variant is considerably faster and cheaper to run, making it practical for high-throughput deployments where latency matters. It is the same underlying model as the #2 entry above, but operated without the extended chain-of-thought reasoning that boosts the score higher. For organizations that need Claude’s Anthropic safety profile and low hallucination tendencies but can’t afford the token cost of maximum reasoning, the standard Opus 4.6 remains a strong factual performer.
9. GLM-5 (Zhipu AI / Z.AI)
AA-Omniscience Score: 2
GLM-5 from Zhipu AI (also marketed under the Z.AI brand) is the most factual AI model among open-weights models, scoring 2 on the AA-Omniscience Index — a 35-point improvement over its predecessor, GLM-4.7. This achievement is particularly striking given that GLM-5 is one of the few models on this list with publicly available weights, meaning organizations can deploy it on their own infrastructure. The improvement was driven by a 56-percentage-point reduction in hallucination rate, achieved primarily through more frequent abstention when the model lacks confidence. GLM-5 scores 50 on the Artificial Analysis Intelligence Index overall, placing it competitively with frontier proprietary models despite being open-weights. Its model weights are released in BF16 precision and total approximately 1.5TB, which is a significant hardware requirement for self-hosting.
10. GPT-5.2 — xHigh Reasoning (OpenAI)
AA-Omniscience Score: 2
Rounding out the top 10 most factual AI models is GPT-5.2 at its highest reasoning effort, with an AA-Omniscience score of 2. GPT-5.2 was the model that topped the Artificial Analysis Intelligence Index when the benchmark was restructured into its current v4.0 form in early January 2026, and it held the top spot until Claude Opus 4.6’s release. While newer OpenAI releases have since appeared on this list, GPT-5.2 xhigh remains a competitive factual performer — and one that many enterprise deployments have already standardized on. It performs particularly well on business-domain factual questions, and its strong tool-use capabilities make it well-suited for retrieval-augmented generation pipelines where being a most factual AI model is the primary requirement.