GEHIRNS/magi-1.1-4B
text-generation model by GEHIRNS
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Model card & documentation
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magi-1.1-4B is Qwen3.5-4B in 2.61 GiB at a 32K context. On our 2,313-task benchmark it scores 81.7%, against 84.0% for the BF16 model in 9.51 GiB, and it thinks 28% less than magi-1.0-4B. It is magi-1.0-4B with one LoRA fine-tune merged in before quantization: Against magi-1.0-4B on the same 2,313 tasks (paired): Capability density is ρ = −log₂(1 − score) / GiB: how many times the benchmark error rate is halved per gibibyte of memory. Memory for all three models is measured the same way: llama.cpp with a q40 KV cache at a 32K context, from llama-fit-params. The magi-1.0-4B card's chart used Ollama's memory figures, so its numbers are not comparable with these. magi-1.1-4B reaches its answer sooner. It ends thinking on its own more often, so fewer tasks are cut off at the 4,096-token budget and fewer traces end in a repetition loop. Every column was run on one…
Read the full model card ↗ · Preview checked 2026-11-07T07:41:27.574Z
Inside the original model card — Document outline
- Introduction
- Capability density
- Thinking
- Benchmarks
- Recipe
- Training
- How to run
- Limitations
- Related
- Citation
- License
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Model overview
GEHIRNS/magi-1.1-4B is a text-generation model repository published by GEHIRNS on Hugging Face. The source reports the gguf library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- gguf
- Recent downloads (30 days)
- 0
- Cumulative likes
- 1
- Hugging Face trending score
- 1
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-11-07T06:21:08.000Z
- Last modified
- 2026-11-07T06:37:45.000Z
Compatibility and lineage
Reported languages: en
Reported base models: Qwen/Qwen3.5-4B
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-07T06:54:27.277Z. Daily imports are snapshots, not real-time monitoring.
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