What are the hardware requirements for Qwen3.6 27B Esper3.1?

Qwen3.6 27B Esper3.1 requires approximately 55.6 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 Qwen3.6 27B Esper3.1 and how large is it?

Qwen3.6 27B Esper3.1 is developed by ValiantLabs, a model with 27b 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 Qwen3.6 27B Esper3.1?

Qwen3.6 27B Esper3.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.6 27B Esper3.1 by ValiantLabs — VRAM 55.6GB, 256K context

Name: Qwen3.6 27B Esper3.1
Author: ValiantLabs

Qwen3.6 27B Esper3.1 is an open-source language model by ValiantLabs. Features: 27b LLM, VRAM: 55.6GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.23.

27b Analytical Ansible Architect Aws Azure Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.6-27b Bash C C# C++ Chat Cloud Code Code-instruct Conversational Creative Dataset:sequelbox/mitakihara-d... Dataset:sequelbox/tachibana3-p... Dataset:sequelbox/tachibana3-p... Dataset:sequelbox/titanium3-de... Dev-ops Developer Docker En Endpoints compatible Engineer Esper Esper-3 Esper-3.1 Expert Gcp Go Grafana Haskell Helm Image-text-to-text Instruct Java Javascript Jenkins Kubernetes Powershell Problem-solving Prometheus Python Qwen Qwen-3.6 Qwen-3.6-27b Qwen3 5 text Rationality Reasoning Region:us Rust Safetensors Scripting Sharded Shell Tensorflow Terraform Typescript Valiant Valiant-labs

Model Card on HF 🤗: https://huggingface.co/ValiantLabs/Qwen3.6-27B-Esper3.1

Qwen3.6 27B Esper3.1 Parameters and Internals

LLM Name	Qwen3.6 27B Esper3.1
Repository 🤗	https://huggingface.co/ValiantLabs/Qwen3.6-27B-Esper3.1
Base Model(s)	Qwen/Qwen3.6-27B Qwen/Qwen3.6-27B
Model Size	27b
Required VRAM	55.6 GB
Updated	2026-07-18
Maintainer	ValiantLabs
Model Type	qwen3_5_text
Instruction-Based	Yes
Model Files	2.5 GB: 1-of-14 4.2 GB: 2-of-14 4.2 GB: 3-of-14 4.2 GB: 4-of-14 4.2 GB: 5-of-14 4.2 GB: 6-of-14 4.2 GB: 7-of-14 4.2 GB: 8-of-14 4.2 GB: 9-of-14 4.2 GB: 10-of-14 4.2 GB: 11-of-14 4.2 GB: 12-of-14 4.2 GB: 13-of-14 2.7 GB: 14-of-14
Supported Languages	en
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.5.3
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwen3.6 27B Esper3.1 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 Qwen3.6 27B Esper3.1

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.6 27B Esper4	256K / 55.6 GB	292	19
Qwen3.6 27B Tachibana Agent	256K / 55.6 GB	60	7

Note: green Score (e.g. "73.2") means that the model is better than ValiantLabs/Qwen3.6-27B-Esper3.1.