license, language, base_model, tags
| license | language | base_model | tags | ||||||
|---|---|---|---|---|---|---|---|---|---|
| other |
|
|
|
MiniCPM5-1B-Agentic-v8
Created by GLM-5.2. Model 8 of 8 in the agentic post-training series.
Variant: 4-way Soup (best overall)
Evaluation
| Metric | Score |
|---|---|
| Real-World Tasks | 33.3% (4/12) |
| Unique Tasks Solved | 8/12 |
| Consistent (5/5) | rw_http_server |
| Often (4/5) | rw_venv_setup |
GGUFs available: f16, q8_0, q5_k_m, q4_k_m, q3_k_m, q2_k
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 |
| q5_k_m | Good | ~0.8GB | Reasoning OK, response may degrade on longer outputs |
| q4_k_m | Fair | ~0.7GB | Reasoning OK, response degrades into repetition |
| q3_k_m | 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.