Mistral 7B Instruct V0.3 GPTQ 4bit is an open-source language model by stan-hua. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, Quantized, Instruction-Based, LLM Explorer Score: 0.14.
Arxiv:1910.09700 4-bit 4bit Autotrain compatible Conversational Endpoints compatible Gptq Instruct Mistral Quantized Region:us Safetensors
Model Card on HF 🤗: https://huggingface.co/stan-hua/Mistral-7B-Instruct-v0.3-GPTQ-4bit
Mistral 7B Instruct V0.3 GPTQ 4bit Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
Mistral 7B Instruct V0.3 GPTQ 4bit Parameters and Internals
| LLM Name | Mistral 7B Instruct V0.3 GPTQ 4bit |
| Repository 🤗 | https://huggingface.co/stan-hua/Mistral-7B-Instruct-v0.3-GPTQ-4bit |
| Base Model(s) | |
| Model Size | 7b |
| Required VRAM | 4.2 GB |
| Updated | 2025-09-23 |
| Maintainer | stan-hua |
| Model Type | mistral |
| Instruction-Based | Yes |
| Model Files | |
| GPTQ Quantization | Yes |
| Quantization Type | gptq|4bit |
| Model Architecture | MistralForCausalLM |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.41.1 |
| Tokenizer Class | LlamaTokenizer |
| Vocabulary Size | 32768 |
| Torch Data Type | float16 |
Best Alternatives to Mistral 7B Instruct V0.3 GPTQ 4bit
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Mistral 7B Instruct V0.3 GPTQ | 32K / 4.2 GB | 65551 | 1 |
| ...ral 7B Instruct V0.3 GPTQ 4bit | 32K / 4.2 GB | 6839 | 23 |
| Mistral 7B Instruct V0.2 GPTQ | 32K / 4.2 GB | 47360 | 54 |
| ...ral 7B Instruct V0.3 GPTQ 4bit | 32K / 4.2 GB | 2946 | 18 |
| Mistral 7B Instruct V0.3 GPTQ | 32K / 4.2 GB | 6 | 0 |
| ...tral 7B Instruct 32K GPTQ INT8 | 32K / 7.7 GB | 3 | 1 |
| ...stral 7B Instruct V0.3 GPTQ 8B | 32K / 7.7 GB | 4 | 1 |
| ...stral 7B Instruct V0.3 GPTQ 4B | 32K / 4.2 GB | 5 | 0 |
| ...nstruct V0.2 Neural Story GPTQ | 32K / 4.6 GB | 4 | 1 |
| Mistral 7B Instruct V0.2 GPTQ | 32K / 4.2 GB | 124 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than stan-hua/Mistral-7B-Instruct-v0.3-GPTQ-4bit .
Rank the Mistral 7B Instruct V0.3 GPTQ 4bit Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
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Release v20260328a