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hudsongouge/minicpm5-1B-GLM-5.2-Agentic-v9

sourceHugging Faceotherupdated 3mo agoView on Hugging Face

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Model Card

MiniCPM5-1B-Agentic-v9

Created by GLM-5.2. Model 9 in the agentic post-training series.

Training: SFT on 10 hand-crafted agentic trajectories (8 epochs, lr=5e-6) teaching the model to use bash tools concisely without excessive reasoning loops.

Evaluation

Metric	Score
Agentic Eval (20 tasks)	30.0% (6/20)
Real-World Tasks (12 tasks)	0% (0/12)

Tasks passed: createfile, fibonacci, fixbug2, grepsearch, csvanalyze, merge_files

GGUFs available: f16, q80, q5km, q4km, q3km, q2k

Quantization Recommendations

This is a 1B model — heavier quantization degrades output quality significantly.

Quant	Quality	Size	Recommendation
f16	Full	~2.1GB	Best quality
q8_0	Excellent	~1.1GB	Recommended — near-identical to f16
q5km	Good	~0.8GB	Reasoning OK, response may degrade on longer outputs
q4km	Fair	~0.7GB	Reasoning OK, response degrades into repetition
q3km	Poor	~0.6GB	Not recommended
q2_k	Poor	~0.5GB	Not recommended

For production use, prefer q8_0 or f16. The model uses reasoning tokens; lower quantizations break the transition from reasoning to response.

Chat Template

The GGUF chat template defaults to enable_thinking=true, so the model will always produce reasoning followed by response. If your inference engine supports enable_thinking=false, you can skip reasoning for faster responses.

Tool Use

The model supports bash tool calls using the <function name="bash"> XML format. The chat template includes tool definitions when tools are provided.