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Spiral Qwen3 4B by spiral-rl

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Spiral Qwen3 4B is an open-source language model by spiral-rl. Features: 4b LLM, VRAM: 8.1GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.19.

  Arxiv:2506.24119 Base model:finetune:qwen/qwen3...   Base model:qwen/qwen3-4b-base   Conversational   Endpoints compatible   Qwen3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/spiral-rl/Spiral-Qwen3-4B 

Spiral Qwen3 4B Benchmarks

LLME Score: 0.19418
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Spiral Qwen3 4B (spiral-rl/Spiral-Qwen3-4B)
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Spiral Qwen3 4B Parameters and Internals

LLM NameSpiral Qwen3 4B
Repository 🤗https://huggingface.co/spiral-rl/Spiral-Qwen3-4B 
Base Model(s)  Qwen3 4B Base   Qwen/Qwen3-4B-Base
Model Size4b
Required VRAM8.1 GB
Updated2026-06-07
Maintainerspiral-rl
Model Typeqwen3
Model Files  5.0 GB: 1-of-2   3.1 GB: 2-of-2
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.51.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Spiral Qwen3 4B

Best Alternatives
Context / RAM
Downloads
Likes
FastContext 1.0 4B SFT256K / 8.1 GB5735357
FastContext 1.0 4B RL256K / 8.1 GB455961
Qwen3 4B Instruct 2507256K / 8.1 GB5455321886
GRPO 4 70256K / 8.1 GB50
Qwen3 4B Thinking 2507256K / 8.1 GB599357591
Lightning 4B256K / 8.1 GB136
Qwen3 4B Instruct 2507 FP8256K / 5.2 GB84028179
Jan V1 4B256K / 8.1 GB108354353
AgentCPM Explore256K / 8.9 GB499415
OpenSonnet Lite MAX256K / 8 GB40530
Note: green Score (e.g. "73.2") means that the model is better than spiral-rl/Spiral-Qwen3-4B.

Rank the Spiral Qwen3 4B 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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