What are the hardware requirements for XLAM 7B R?

XLAM 7B R requires approximately 14.4 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed XLAM 7B R and how large is it?

XLAM 7B R is developed by Salesforce, a model with 7b 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 XLAM 7B R?

XLAM 7B R is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

XLAM 7B R by Salesforce — VRAM 14.4GB, 32K context

Name: XLAM 7B R
Author: Salesforce

XLAM 7B R is an open-source language model by Salesforce. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: cc-by-nc-4.0, Instruction-Based, LLM Explorer Score: 0.14.

Arxiv:2402.15506 Arxiv:2406.18518 Arxiv:2409.03215 Arxiv:2503.22673 Conversational Dataset:salesforce/xlam-functi... En Endpoints compatible Function-calling Instruct Llm agent Mistral Pytorch Region:us Safetensors Sharded Tensorflow Tool-use

Model Card on HF 🤗: https://huggingface.co/Salesforce/xLAM-7b-r

XLAM 7B R Parameters and Internals

Model Type

text generation

Use Cases

Areas:

research

Additional Notes

The model is exclusively released for research purposes and is expected to have enhanced versions available commercially in the future.

Supported Languages

en (Proficient)

Input Output

Input Format:

Specific prompt structures for function calling.

Accepted Modalities:

text

Output Format:

JSON with function call specifications.

Performance Tips:

Use provided prompt format for optimal function-calling performance.

LLM Name	XLAM 7B R
Repository 🤗	https://huggingface.co/Salesforce/xLAM-7b-r
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-08
Maintainer	Salesforce
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.42.3
Tokenizer Class	LlamaTokenizer
Padding Token	[PAD]
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the XLAM 7B R 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 XLAM 7B R

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
... Summarize 64K QLoRANET Merged	128K / 4.1 GB	10	0
...1 Summarize 64K LoRANET Merged	128K / 14.4 GB	10	0
Mistral 7B Instruct V0.2	32K / 14.4 GB	1115337	3184
Mistral 7B Instruct V0.1	32K / 14.4 GB	253629	1846
Mistral 7B Instruct V0.2	32K / 14.4 GB	1338	0
Copywriting Llm	32K / 4.1 GB	122	1

Note: green Score (e.g. "73.2") means that the model is better than Salesforce/xLAM-7b-r.