Laserxtral GGUF 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)
Laserxtral GGUF Parameters and Internals
| LLM Name | Laserxtral GGUF |
| Repository 🤗 | https://huggingface.co/cognitivecomputations/laserxtral-GGUF |
| Model Size | 7b |
| Required VRAM | 8.8 GB |
| Updated | 2024-09-07 |
| Maintainer | cognitivecomputations |
| Model Type | mixtral |
| Model Files | |
| GGUF Quantization | Yes |
| Quantization Type | gguf|q2|q4_k|q5_k |
| Model Architecture | MixtralForCausalLM |
| License | cc-by-nc-2.0 |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.36.2 |
| Vocabulary Size | 32000 |
| Torch Data Type | bfloat16 |
Best Alternatives to Laserxtral GGUF
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Mixtral 7Bx2 MoE GGUF | 32K / 4.8 GB | 164 | 2 |
| Mistral 7B MoEified 8x | 32K / 14.6 GB | 142 | 3 |
| ...izardLM 2 4x7B MoE EXL2 3 0bpw | 32K / 9.4 GB | 4 | 1 |
| Buttercup 4x7B 6bpw EXL2 | 32K / 18.4 GB | 4 | 2 |
| BurningBruce 003 EXL2 B8.0 | 32K / 24.3 GB | 4 | 1 |
| ...ixtral 2x7b DPO 8.0bpw H8 EXL2 | 32K / 13 GB | 6 | 4 |
| ...ixtral 2x7b DPO 5.0bpw H6 EXL2 | 32K / 8.3 GB | 6 | 1 |
| ...ixtral 2x7b DPO 4.0bpw H6 EXL2 | 32K / 6.7 GB | 4 | 1 |
| ...ixtral 2x7b DPO 6.0bpw H6 EXL2 | 32K / 9.8 GB | 4 | 1 |
| ...t V0.2 2x7B MoE 6.0bpw H6 EXL2 | 32K / 9.9 GB | 11 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than cognitivecomputations/laserxtral-GGUF .
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803