Holo4 35B-A3B

Holo4 27B

H Company

Holo4 27B is H Company’s computer-use vision-language model built on Qwen3.8-27B. It is post-trained to work across graphical interfaces, code, MCP tools, and APIs, using screenshots and tool results to choose its next actions. Released weights support local agent research; an external harness executes clicks, typing, and code and returns observations. The dense 27B model uses a non-commercial weight license, unlike the Apache-licensed sparse Holo4 tier. Its card specifies a 262,144-token configuration limit; this is not a promise of consistent task performance throughout that window.

Holotron4 Nano

H Company

Holotron4 Nano is H Company’s computer-use vision-language model built on NVIDIA Nemotron 3 Nano Omni. It is post-trained to work across graphical interfaces, code, MCP tools, and APIs, using screenshots and tool results to choose its next actions. Released weights support local agent research; an external harness executes clicks, typing, and code and returns observations. The sparse model activates about 3B language parameters per token but still needs memory for its full checkpoint. Its card specifies a 262,144-token context. The NVIDIA Open Model Agreement governs its weights; the released page establishes text and image understanding without assuming every modality of its Omni backbone.

Holo3.1

H Company

Holo3.1 is H Company’s updated computer-use model family, adding mobile robustness, native function-calling protocols, and practical local deployment. It spans dense 0.8B, 4B, and 9B Qwen3.5-derived tiers plus a sparse 35B-A3B tier whose current card identifies Qwen3.6 ancestry. The release includes Apache-licensed weights and optimized FP8, NVFP4, and Q4 GGUF options for the larger tier. These are variants of the same trained generation rather than extra catalog models. The current H Models API exposes the 35B tier with a 65,536-token hosted context; that limit is described without treating it as a verified uniform specification for every size.