QVikhr 2.5 1.5B Instruct SMPO MLX 8bit by Vikhrmodels

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QVikhr 2.5 1.5B Instruct SMPO MLX 8bit is an open-source language model by Vikhrmodels. Features: 1.5b LLM, VRAM: 1.6GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.19.

  8-bit   8bit Base model:quantized:vikhrmode... Base model:vikhrmodels/qvikhr-...   Conversational   En   Endpoints compatible   Instruct   Mlx   Quantized   Qwen2   Region:us   Ru   Safetensors

QVikhr 2.5 1.5B Instruct SMPO MLX 8bit Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
QVikhr 2.5 1.5B Instruct SMPO MLX 8bit (Vikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO_MLX-8bit)
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QVikhr 2.5 1.5B Instruct SMPO MLX 8bit Parameters and Internals

LLM NameQVikhr 2.5 1.5B Instruct SMPO MLX 8bit
Repository ๐Ÿค—https://huggingface.co/Vikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO_MLX-8bit 
Model NameVikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO
Base Model(s)  Vikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO   Vikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO
Model Size1.5b
Required VRAM1.6 GB
Updated2026-01-12
MaintainerVikhrmodels
Model Typeqwen2
Instruction-BasedYes
Model Files  1.6 GB
Supported Languagesru en
Quantization Type8bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.47.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151665
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Vikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO_MLX-8bit.

Rank the QVikhr 2.5 1.5B Instruct SMPO MLX 8bit Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
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Release v20241124