Benchmark Almanac

Seed1.5-VL internal benchmark (ByteDance Seed in-house)

Seed1.5-VL 59.3% Only in system cards

Models answer more than 12,000 internal image questions over 100 tasks, from perception, OCR and STEM to agents, code and out-of-distribution puzzles. LLM judges grade answers, and the overall is a weighted average.

In-house ByteDance Seed evaluation. The tasks are not public. Many tasks are in Chinese, and the task set is refreshed over time.

Made by ByteDance Seed Released May 2025 General visual questions Tasks kept private Last in a system card May 2025 Last model added May 2025
Level
University Undergraduates and entry-level professionals
Scored
Graded by a model A language model scores each response, usually against a rubric.
Answers
Short answer A number, word or short string matched to a key.
1
Model scored in lab cards
1
System card reports it, from 1 lab

Seed1.5-VL leads with 59.3%

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 Seed1.5-VL 59.3%
#ModelScoreSettingDateSource
1 Seed1.5-VL 59.3% May 2025 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% 2025 Near the ceiling (85%) Seed1.5-VL 0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) Seed1.5-VL

Labs report it only in system cards

We read the headline results of 479 launch posts from 51 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
11 May 2025 Seed1.5-VL technical report 59.3 Internal benchmark Overall, weighted average, thinking (Table 10). OOD 44.1, Agent 63.1, Reasoning 47.6 Capabilities

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  • MMMU-Pro In use Harder MMMU: college-level multimodal questions with more options and vision-only inputs to remove text shortcuts. Kimi K3.1 Pro 84.1%
  • CharXiv In use Chart understanding on real arXiv figures. Reasoning questions require synthesizing information from complex charts. Claude Fable 5 93.5%
  • MATH-Vision (MathVision) In use 3,040 competition math problems with visual context. Answer accuracy. Qwen 3.8 Max 97.7%
  • ChartQA In use Models answer human-written and generated questions about chart images that need visual and arithmetic reasoning. Scored by relaxed accuracy with a 5 percent numeric tolerance. Command A Vision 90.9%
  • DocVQA In use Models answer 50,000 questions about 12,000 scanned document images by reading their text and layout. Scoring is ANLS, a string similarity to reference answers. Seed1.5-VL 96.9%