What are the hardware requirements for Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill?

Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill requires approximately 8.1 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill and how large is it?

Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill is developed by TeichAI, a model with 4b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill?

Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill by TeichAI — VRAM 8.1GB, 256K context

Name: Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill
Author: TeichAI

Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill is an open-source language model by TeichAI. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.21.

Base model:finetune:unsloth/qw... Base model:unsloth/qwen3-4b-th... Conversational En Endpoints compatible Qwen3 Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/TeichAI/Qwen3-4B-Thinking-2507-Kimi-K2-Thinking-Distill

Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill Parameters and Internals

LLM Name	Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill
Repository 🤗	https://huggingface.co/TeichAI/Qwen3-4B-Thinking-2507-Kimi-K2-Thinking-Distill
Base Model(s)	Qwen3 4B Thinking 2507 unsloth/Qwen3-4B-Thinking-2507
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-08-30
Maintainer	TeichAI
Model Type	qwen3
Model Files	5.0 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.56.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Qwen3 4B Thinking 2507 Kimi K2 Thinking Distill

Best Alternatives	Context / RAM	Downloads	Likes
GRPO 4 70	256K / 8.1 GB	9	0
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
...2.5 Flash Lite Preview Distill	256K / 8.1 GB	31	1
Lightning 4B	256K / 8.1 GB	13	6
Fable Traces	256K / 8.1 GB	345	210
Qwen3 4B Thinking 2507	256K / 8.1 GB	291023	606
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
Qwen3 4B Sft Prm	256K / 17.6 GB	602	0

Note: green Score (e.g. "73.2") means that the model is better than TeichAI/Qwen3-4B-Thinking-2507-Kimi-K2-Thinking-Distill.