Total runs:
5.2K
Run Growth:
5.2K
Growth Rate:
100.00%
Sponsored by
APIMart
artindnr / mochi-GGUF
Model's Last Updated: August 08 2026
text-generation
Introduction of mochi-GGUF
Model Details of mochi-GGUF
🍡 Mochi GGUF
GGUF quantizations of artindnr/mochi , a math-reasoning fine-tune of GLM-4.7-Flash trained on the Open Math Reasoning (mini) dataset — the same chain-of-thought data behind the winning submission to the AIMO-2 Kaggle competition .
These quants let you run Mochi locally with
llama.cpp
, Ollama, LM Studio, or any other GGUF-compatible runtime.
Files
| File | Quant | Notes |
|---|---|---|
mochi.Q8_0.gguf
|
Q8_0 | Highest quality of the three, largest file size, closest to full precision |
mochi.Q5_K_M.gguf
|
Q5_K_M | Balanced quality/size trade-off, good default for most setups |
mochi.Q4_K_M.gguf
|
Q4_K_M | Smallest and fastest, some quality loss vs. higher-bit quants |
If you're unsure which to pick: Q5_K_M is a solid default. Use Q8_0 if you have the VRAM/RAM to spare and want maximum fidelity, and Q4_K_M if you're constrained on memory or want faster inference.
Usage
llama.cpp
./llama-cli -m mochi.Q5_K_M.gguf -p "If x^2 - 5x + 6 = 0, what are the values of x?" -n 512
Or serve it as an OpenAI-compatible endpoint:
./llama-server -m mochi.Q5_K_M.gguf -c 4096
Ollama
Create a
Modelfile
:
FROM ./mochi.Q5_K_M.gguf
Then:
ollama create mochi -f Modelfile
ollama run mochi
LM Studio
Download the
.gguf
file of your choice directly in LM Studio's model browser (search
artindnr/mochi-gguf
), or drop the file into your local models folder.
About Mochi
Mochi is a chain-of-thought math fine-tune of GLM-4.7-Flash. See the full model card for training details, dataset info, and intended use.
- Base model: GLM-4.7-Flash
- Fine-tuning data: unsloth/OpenMathReasoning-mini
- Focus: Step-by-step mathematical reasoning (olympiad-style problems)
-
Format:
GGUF, for use with
llama.cppand compatible runtimes
Limitations
- Quantization introduces some precision loss versus the original fp16/bf16 weights — expect small quality differences between Q8_0, Q5_K_M, and Q4_K_M, especially on harder problems.
- Fine-tuned specifically for math reasoning; general chat ability may differ from the base GLM-4.7-Flash model.
- Always verify important results — this is not a substitute for a calculator or formal proof checker.
Acknowledgements
- GLM-4.7-Flash for the base model
- Unsloth for fine-tuning tooling
- NVIDIA's AIMO-2 team for the OpenMathReasoning dataset
- llama.cpp for the GGUF format and quantization tooling
Runs of artindnr mochi-GGUF on huggingface.co
299
Total runs
0
24-hour runs
12
3-day runs
265
7-day runs
299
30-day runs
More Information About mochi-GGUF huggingface.co Model
Url of mochi-GGUF
mochi-GGUF huggingface.co Url
Provider of mochi-GGUF huggingface.co
Other API from artindnr
Updated:August 10 2026
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727
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