Model Card on HF 🤗: https://huggingface.co/TheBloke/Vicuna-7B-CoT-fp16
Vicuna 7B CoT Fp16 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)
Vicuna 7B CoT Fp16 Parameters and Internals
| LLM Name | Vicuna 7B CoT Fp16 |
| Repository 🤗 | https://huggingface.co/TheBloke/Vicuna-7B-CoT-fp16 |
| Model Size | 7b |
| Required VRAM | 13.5 GB |
| Updated | 2025-09-14 |
| Maintainer | TheBloke |
| Model Type | llama |
| Model Files | |
| Quantization Type | fp16 |
| Model Architecture | LlamaForCausalLM |
| License | other |
| Context Length | 2048 |
| Model Max Length | 2048 |
| Transformers Version | 4.29.2 |
| Tokenizer Class | LlamaTokenizer |
| Beginning of Sentence Token | <s> |
| End of Sentence Token | </s> |
| Unk Token | <unk> |
| Vocabulary Size | 32000 |
| Torch Data Type | float32 |
Best Alternatives to Vicuna 7B CoT Fp16
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Smaugv0.1 6.0bpw H6 EXL2 | 195K / 26.4 GB | 3 | 4 |
| Smaugv0.1 5.0bpw H6 EXL2 | 195K / 22.3 GB | 2 | 3 |
| Smaugv0.1 3.0bpw H6 EXL2 | 195K / 13.9 GB | 5 | 1 |
| Smaugv0.1 4.0bpw H6 EXL2 | 195K / 18 GB | 3 | 1 |
| Smaugv0.1 4.65bpw H6 EXL2 | 195K / 20.8 GB | 3 | 1 |
| Smaugv0.1 8.0bpw H8 EXL2 | 195K / 34.9 GB | 3 | 1 |
| DeepSeek Prover V2 7B 4bit | 64K / 3.9 GB | 1137 | 4 |
| Mistral 7B Openplatypus 1K | 32K / 29 GB | 1720 | 0 |
| Mistral 7B OpenOrca 1K | 32K / 29 GB | 1709 | 3 |
| ...rnlm2 20B Llama 4.0bpw H6 EXL2 | 32K / 11 GB | 6 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Vicuna-7B-CoT-fp16 .
Rank the Vicuna 7B CoT Fp16 Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124