Salesforce/Dense

SxLAM-2 3B Function-Calling

The new xLAM-2 series, built on our most advanced data synthesis, processing, and training pipelines, marks a significant leap in multi-turn conversation and tool usage.

tool_useagentic
3B
Parameters
32K
Context length
0
Benchmarks
6
Quantizations
0
Architecture
Dense
Released
2025-03-12
Layers
36
KV Heads
2
Head Dim
128
Family
other

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.892.3 GBgood
Q5_K_S5.572.6 GBgood
Q5_K_M5.72.6 GBgood
Q6_K6.562.9 GBexcellent
Q8_08.53.7 GBlossless
FP16166.5 GBlossless

Select your GPU above to see speed estimates and compatibility for each quantization.

READY TO RUN THIS?RENT BY THE HOUR

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Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run other:3b-q4_K_M

Tag may need adjustment — check ollama.com/library/other for available tags.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA Tesla C2050
3 GB VRAM • 144 GB/s
NVIDIA
NVIDIA Tesla M2050
3 GB VRAM • 148 GB/s
NVIDIA
NVIDIA Tesla S2050
3 GB VRAM • 148 GB/s
NVIDIA

Find the best GPU for xLAM-2 3B Function-Calling

Build Hardware for xLAM-2 3B Function-Calling
▸ SPEC SHEET

xLAM-2 3B Function-Calling3B Dense.

▸ SPECIFICATIONS
PARAMETERS
3B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
tool_use, agentic
RELEASE DATE
2025-03-12
PROVIDER
Salesforce
FAMILY
other
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.892.3 GB94%
Q5_K_S5.572.6 GB96%
Q5_K_M5.72.6 GB96%
Q6_K6.562.9 GB97%
Q8_08.53.7 GB100%
FP16166.5 GB100%