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OpenVLHarness

Official Code for OpenVLHarness

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GITHUB · launched Oct 15, 2026 · 14 upvotes (top 78%)

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Could you build this?

Partial The harness itself (tool orchestration, vision tool wrappers, and a memory store around existing multimodal LLM APIs) is vibe-codeable. Matching the reported results across 22 benchmarks and six backbones requires research-level design iteration and significant evaluation compute.

What it would actually take: Build a Python agent loop that calls multimodal model APIs with tool schemas for grounding, segmentation, and cropping, backed by existing open vision models such as SAM or detection models. Persistent multimodal memory needs an embedding store with image and text retrieval. The hard part is the tuned memory and tool-selection logic that produces the claimed gains, which needs ML research skill and GPU or API budget for benchmark runs.

Competitors

Other products that read as similar to this one : 452 launches clear the similarity bar, closest 8 shown.

Attention rank: #358 of 453 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 335 days after the earliest competitor.

Other launches for this product

More details
External ID
1420250493
Company
n/a
Product
OpenVLHarness
Website domain
github.io
Cohort
n/a
Upvotes percentile
0.22
All tags
n/a
AI summary
evaluation harness for vision-language models
Manually corrected
No