What are the hardware requirements for Text2cypher Codestral 16bit Gguf?

Text2cypher Codestral 16bit Gguf requires approximately 44.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Text2cypher Codestral 16bit Gguf and how large is it?

Text2cypher Codestral 16bit Gguf is developed by tomasonjo, a model with 22b 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 Text2cypher Codestral 16bit Gguf?

Text2cypher Codestral 16bit Gguf is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Text2cypher Codestral 16bit Gguf by tomasonjo — VRAM 44.5GB

Name: Text2cypher Codestral 16bit Gguf
Author: tomasonjo

Text2cypher Codestral 16bit Gguf is an open-source language model by tomasonjo. Features: 22b LLM, VRAM: 44.5GB, License: MNPL-0.1, Quantized, LLM Explorer Score: 0.13.

16bit Base model:mistralai/codestral... Base model:quantized:mistralai... Dataset:tomasonjo/text2cypher-... En Endpoints compatible Gguf Mistral Quantized Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/tomasonjo/text2cypher-codestral-16bit-gguf

Text2cypher Codestral 16bit Gguf Parameters and Internals

Model Type

text-generation-inference, transformers, unsloth, mistral, gguf

Training Details

Data Sources:

tomasonjo/text2cypher-gpt4o-clean

Methodology:

The model was trained 2x faster with Unsloth and Huggingface's TRL library.

LLM Name	Text2cypher Codestral 16bit Gguf
Repository 🤗	https://huggingface.co/tomasonjo/text2cypher-codestral-16bit-gguf
Base Model(s)	mistralai/Codestral-22B-v0.1 mistralai/Codestral-22B-v0.1
Model Size	22b
Required VRAM	44.5 GB
Updated	2026-07-10
Maintainer	tomasonjo
Model Type	mistral
Model Files	44.5 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|16bit
Model Architecture	AutoModel
License	MNPL-0.1

Rank the Text2cypher Codestral 16bit Gguf 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 Text2cypher Codestral 16bit Gguf

Best Alternatives	Context / RAM	Downloads	Likes
Codestral 22B V0.1 GGUF	0K / 4.8 GB	2720	9
...t2cypher Codestral Q4 K M Gguf	0K / 13.3 GB	160	5
Qwen1.5 22B Chat Merge GGUF	0K / 12.6 GB	32	1
Nucleus 22B Token 500B GGUF	0K / 9.1 GB	345	3
Llama2 22B Daydreamer V3 GGUF	0K / 9.1 GB	362	2
Llama2 22B GPLATTY GGUF	0K / 9.1 GB	168	3
Huginn 22B Prototype GGUF	0K / 9.1 GB	301	2
Llama2 22B Daydreamer V2 GGUF	0K / 9.1 GB	166	1
Huginn 22B Prototype GGML	0K / 9.2 GB	4	1
Llama2 22B GPLATTY GGML	0K / 9.2 GB	5	7

Note: green Score (e.g. "73.2") means that the model is better than tomasonjo/text2cypher-codestral-16bit-gguf.