Benchmark Almanac

Meta internal agent hallucination evaluation

Only in system cards

Agents do long-context assistant and professional tasks with tools. The benchmark reports the share of verifiable claims that are hallucinated.

In-house Meta benchmark across health, finance, legal, clinical and engineering tasks.

Made by
Meta
Kind
Hallucination rates
Level
Expert
Scored
Graded by a model
Answers
Agent task
Tasks
Kept private
Strongest model tested
Muse Spark 1.3 #26 on the capability index
Last in a system card
October 2026
Last model added
October 2026
1
Model scored in lab cards
1
System card reports it, from 1 lab

Muse Spark 1.3 leads with 5.74%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 Muse Spark 1.3 5.74%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Muse Spark 1.3 5.74% Oct 2026 Lab model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2027 Muse Spark 1.3 0% 20% 40% 60% 80% 100% 2027 Muse Spark 1.3

Source: Labs’ model cards

Labs report it only in system cards

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.

One system card reports it

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Oct 23, 2026 Muse Spark 1.3 system card 5.74 Internal Agent Hallucination Eval, claim-level hallucination rate, Muse Spark 1.3 (API) max (Figure 33a) Hallucination

More in Factuality

All 74 in Factuality
  • SimpleVQA In use Models answer 2,025 short factual questions about images across 9 tasks and 9 topics. An LLM judge grades answers against fixed references. Qwen3.7-Plus 81.7%
  • HallusionBench In use Models answer 1,129 yes or no questions about 346 images, built in pairs to expose language hallucination and visual illusion. Scored by accuracy. Keye-VL-2.0-30B-A3B 73.5%
  • SimpleQA Verified In use 1,000 human-verified, de-duplicated short-answer factual questions measuring parametric knowledge. Gemini 3.1 Pro 77.5%
  • Kimi Hallu Bench In use Models answer hard prompts drawn from practical work tasks. Fact-checking agents score the share of claims that are hallucinated. GPT-6 Astra 4.20%
  • Internal adversarially-designed factuality evaluations In use Models answer adversarial questions in nine categories such as history, math and code. Scored on agreement with human ideal responses. GPT-6 Luna 7.60%
  • AA-Omniscience v1.1 In use Models answer 3,000 knowledge questions in six domains without tools and may abstain. The index adds correct answers and subtracts wrong ones. Inkling 2 Small 16.1