What are the hardware requirements for Qwen3 14B Cobalt2?

Qwen3 14B Cobalt2 requires approximately 59 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 14B Cobalt2 and how large is it?

Qwen3 14B Cobalt2 is developed by ValiantLabs, a model with 14b 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 14B Cobalt2?

Qwen3 14B Cobalt2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 14B Cobalt2 by ValiantLabs — VRAM 59GB, 40K context

Name: Qwen3 14B Cobalt2
Author: ValiantLabs

Qwen3 14B Cobalt2 is an open-source language model by ValiantLabs. Features: 14b LLM, VRAM: 59GB, Context: 40K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.18.

14b Analytical Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-14b Chat Cobalt Cobalt-2 Conversational Creative Dataset:sequelbox/raiden-deeps... Dataset:zwhe99/deepmath-103k En Endpoints compatible Expert Instruct Math Math-instruct Math-reasoning Problem-solving Qwen Qwen-3 Qwen-3-14b Qwen3 Rationality Reasoning Region:us Safetensors Sharded Tensorflow Valiant Valiant-labs

Model Card on HF 🤗: https://huggingface.co/ValiantLabs/Qwen3-14B-Cobalt2

Qwen3 14B Cobalt2 Parameters and Internals

LLM Name	Qwen3 14B Cobalt2
Repository 🤗	https://huggingface.co/ValiantLabs/Qwen3-14B-Cobalt2
Base Model(s)	Qwen3 14B Qwen/Qwen3-14B
Model Size	14b
Required VRAM	59 GB
Updated	2026-07-18
Maintainer	ValiantLabs
Model Type	qwen3
Instruction-Based	Yes
Model Files	4.7 GB: 1-of-13 4.7 GB: 2-of-13 4.9 GB: 3-of-13 4.9 GB: 4-of-13 4.7 GB: 5-of-13 4.9 GB: 6-of-13 4.9 GB: 7-of-13 4.7 GB: 8-of-13 4.9 GB: 9-of-13 4.9 GB: 10-of-13 4.7 GB: 11-of-13 3.0 GB: 12-of-13 3.1 GB: 13-of-13
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float32
Errors	replace

Rank the Qwen3 14B Cobalt2 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 14B Cobalt2

Best Alternatives	Context / RAM	Downloads	Likes
...uct 21B Brainstorm20x 128K Ctx	128K / 84.1 GB	8	0
Qwen3 14B Instruct	40K / 29.7 GB	15805	13
Qwen3 14B Sk Alpaca Slovak It	40K / 23.2 GB	67	1
Supertron1 14B	40K / 9.9 GB	87	5
... 14B Instruct LoRA 1310 Merged	40K / 29.5 GB	9	0
Ophiuchi Qwen3 14B Instruct	40K / 29.5 GB	1068	11
...DER Instruct 21B Brainstorm20x	40K / 84.1 GB	12	2
...14B Instruct Wildfeedback Seed	40K / 29.5 GB	6	0
Qwen3 14B Esper3	40K / 59 GB	19	14
Bee1reason Arabic Qwen 14B	40K / 29.5 GB	584	8

Note: green Score (e.g. "73.2") means that the model is better than ValiantLabs/Qwen3-14B-Cobalt2.