# WorldVQA ForceAnswer ![Category](https://img.shields.io/badge/Category-Visual%20Question%20Answering-1f6feb) ![Metric](https://img.shields.io/badge/Metric-%25%20Accuracy-2da44e) ![Saturation](https://img.shields.io/badge/Saturation-Low-d29922) ![Created](https://img.shields.io/badge/Created-2026-555) > **Quick answer:** WorldVQA ForceAnswer tests AI models on real-world visual question answering under a "forced-answer" protocol, meaning the model cannot abstain or say "I don't know" — every question must receive a definitive answer, penalizing both incorrect guesses and evasive non-answers. Kimi K3 scores 51.0% as of July 2026. ## At a Glance **What it tests:** A model's ability to answer real-world visual questions accurately when abstention is not allowed, testing both visual perception and confident, committed reasoning. **Why it matters:** Many benchmarks allow models to hedge or abstain on uncertain questions, inflating apparent reliability. The forced-answer setting removes this escape hatch, giving a more honest accuracy signal. **Known limitations:** As an emerging benchmark, exact question sourcing and world-knowledge domain coverage are not yet independently published outside its citation by Moonshot AI. ## What WorldVQA ForceAnswer Measures WorldVQA ForceAnswer evaluates visual question answering grounded in general world knowledge, under a forced-answer protocol that disallows abstention. This design choice ensures the reported accuracy reflects genuine visual-plus-world-knowledge competence rather than a model's tendency to hedge on difficult questions. ## Benchmark Specifications | Field | Value | |---|---| | Task category | Reasoning / visual question answering | | Metric | % accuracy | | Saturation | Low | | Created by | Not yet independently documented | ## How WorldVQA ForceAnswer Is Scored Models must provide a definitive answer to every visual question (no abstention permitted), scored on % accuracy against ground-truth answers. ## State-of-the-Art Results | Rank | Model | Score | Source | Date | |---|---|---|---|---| | 1 | [Kimi K3](/models/moonshot/kimi-k3) | 51.0% | [Kimi K3 technical report](https://www.kimi.com/blog/kimi-k3) | 2026-07 | *Score sourced from Moonshot AI's Kimi K3 announcement, July 2026.* ## WorldVQA ForceAnswer on Benchgen > No Benchgen results yet — [be the first to run WorldVQA ForceAnswer](/benchmarks/platform/worldvqa-forceanswer). ## WorldVQA ForceAnswer vs Other Benchmarks | Benchmark | What it tests | Saturation | |---|---|---| | **WorldVQA ForceAnswer** | Forced-answer real-world visual QA | Low | | [PerceptionBench](/benchmarks/moonshot-ai/perceptionbench) | Fine-grained visual perception | Low | | [SimpleQA](/benchmarks/openai/simpleqa) | Short-form factual QA | High | | [BabyVision](/benchmarks/platform/babyvision) | Early-stage visual reasoning | Low | ## Run WorldVQA ForceAnswer on Your Model Benchgen lets you run WorldVQA ForceAnswer against your own multimodal model, tracking forced-answer accuracy to measure genuine visual-plus-world-knowledge reliability. ## Frequently Asked Questions

What is WorldVQA ForceAnswer?

WorldVQA ForceAnswer is a visual question answering benchmark that disallows abstention — every question requires a definitive answer, testing genuine reliability rather than hedged responses.

What does a good score look like on WorldVQA ForceAnswer?

Kimi K3 reports 51.0% as of July 2026, reflecting the added difficulty of the forced-answer setting compared to benchmarks that allow abstention.

Who created WorldVQA ForceAnswer?

WorldVQA ForceAnswer's originating team is not yet independently documented outside of its citation in Kimi K3's July 2026 technical report.

WorldVQA ForceAnswer — Results

WorldVQA ForceAnswer — Phases

WorldVQA ForceAnswer