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Candle MistralTrix V1 by DanielClough

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Candle MistralTrix V1 is an open-source language model by DanielClough. Features: LLM, VRAM: 17.9GB, Context: 32K, License: apache-2.0, Quantized, Merged, LLM Explorer Score: 0.12.

  Merged Model   Endpoints compatible   Gguf   Mistral   Q4   Quantized   Region:us   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/DanielClough/Candle_MistralTrix-v1 

Candle MistralTrix V1 Benchmarks

LLME Score: 0.11989
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Candle MistralTrix V1 (DanielClough/Candle_MistralTrix-v1)
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Candle MistralTrix V1 Parameters and Internals

LLM NameCandle MistralTrix V1
Repository 🤗https://huggingface.co/DanielClough/Candle_MistralTrix-v1 
Merged ModelYes
Required VRAM17.9 GB
Updated2025-12-16
MaintainerDanielClough
Model Typemistral
Model Files  18.0 GB   3.0 GB   3.9 GB   5.1 GB   5.6 GB   5.1 GB   6.2 GB   6.7 GB   6.2 GB   7.4 GB   9.6 GB   10.1 GB   10.3 GB   4.9 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   3.1 GB: 4-of-4
GGUF QuantizationYes
Quantization Typeq4|gguf
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

Best Alternatives to Candle MistralTrix V1

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Context / RAM
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...istral Nemo Instruct 2407 GGUF1000K / 4.8 GB207466
...istral Nemo Instruct 2407 GGUF1000K / 4.8 GB110011
Devstral Small 2505 GGUF128K / 0.9 GB157110115
...istral C64Wizard Instruct GGUF32K / 4.4 GB260
...dle Snorkel Mistral PairRM DPO32K / 14.4 GB870
Mistral 7B1.0 GGUF32K / 5.1 GB70
Equall Saul Instruct V132K / 5.1 GB90
AI G Expander V5 GGUF32K / 4.4 GB60
MHENN4 GGUF32K / 4.4 GB520
Candle Tiny Mistral32K / 0.4 GB310
Note: green Score (e.g. "73.2") means that the model is better than DanielClough/Candle_MistralTrix-v1.

Rank the Candle MistralTrix V1 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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