An int4 group-scaled conversion of `zai-org/GLM-5.3-Flash`, packed in the container format that colibrì streams from disk. **This is not the official checkpoint.** The weights are Z.ai's; this repository only changes how they are stored. It will not load in transformers or vLLM. It loads in colibrì's `glm53` engine and nothing else. Running a 321B multimodal model on a machine with 25 GB of RAM, by keeping the routed experts on disk and reading only the ones each token selects.

Visual QA

Input Text · Image→ Output Text

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Qwen3-Coder-30B-A3B-colibri-int4

Justvugg

An int4 group-scaled conversion of `Qwen/Qwen3-Coder-30B-A3B-Instruct`, packed in the container format that colibrì reads. **This is not the official checkpoint.** The weights are the Qwen team's, released under Apache 2.0; this repository only changes how they are stored. It will not load in transformers or vLLM. It loads in colibrì's `qwen36` engine, with Qwen3 MoE support from #1828 onwards. A 30B coding model with 3.3B active parameters per token, running on the CPU of an ordinary machine.

Text generation

Input Text→ Output Text

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Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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GLM-5.3-colibri-int4-g64

GLM-5.3-Flash-colibri-int4-g64

Qwen3-Coder-30B-A3B-colibri-int4

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