Comparisons of Tiny Open Source AI Models (≤4B)

Open source AI models with 4B parameters or fewer. These are usually the smallest models in terms of resource demand.

Models are considered open source (also commonly referred to as open weights) where their weights are accessible to download. This allows self-hosting on your own infrastructure and enables customizing the model such as through fine-tuning.

For more details including relating to our methodology, see our FAQs.

Institute of Foundation Models logoK2 Horizon 3.7B and OpenBMB logoMiniCPM5-2B are the highest intelligence Tiny open source models, defined as those with ≤4B parameters, followed by AI9Stars logoG9v3-3B & IBM logoGranite 4.2 3B.

Highlights

Artificial Analysis Openness Index · Higher is better
Updated
Artificial Analysis Intelligence Index · Higher is better
Trainable parameters in billions

Openness

Artificial Analysis Openness Index: Score

Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1
Estimate (independent evaluation forthcoming)

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better
See more

Agentic knowledge work, (Elo-500)/2000

Agentic real-world work tasks, (Elo-500)/2000

Agentic SaaS workflows

Agentic coding & terminal use

Coding

Reasoning & knowledge

Professional document reasoning, All-pass

Physics reasoning

Long context reasoning

Legal agentic work, criterion pass rate

No data available

Agentic business operations

No data available

Quantitative analysis on spreadsheets & documents

No data available

Agentic tool use

Kubernetes incident root-cause analysis

No data available

Visual reasoning

Medical long context reasoning

No data available

Size

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference

Intelligence Index vs. Active Parameters

Artificial Analysis Intelligence Index · Active parameters at inference time
Most attractive quadrant
Pareto line

Intelligence Index vs. Total Parameters

Artificial Analysis Intelligence Index · Size in parameters (billions)
Most attractive quadrant
Pareto line

Context Window

Context Window

Context window: tokens limit · Higher is better

Further details

Weights
Provider Benchmarks
K2 Horizon 3.7B
Institute of Foundation Models logoInstitute of Foundation Models
16
3.7B
524k
-
-
-
MiniCPM5-2B
OpenBMB logoOpenBMB
13
2.6B
131k
-
-
-
G9v3-3B
AI9Stars logoAI9Stars
11
3B
131k
-
-
AI9Stars
Granite 4.2 3B
IBM logoIBM
9
3B
131k
$0.0
215
DeepInfra
MiniCPM5-1B (Reasoning)
OpenBMB logoOpenBMB
9
1B
128k
-
-
-
MiniCPM5-1B (Non-reasoning)
OpenBMB logoOpenBMB
9
1B
128k
-
-
-
Nanbeige4.1-3B
Nanbeige logoNanbeige
8
3.9B
256k
-
-
-
LFM2.5-2.6B
Liquid AI logoLiquid AI
8
2.7B
128k
-
-
Liquid AI
NVIDIA Nemotron 3 Nano 4B
NVIDIA logoNVIDIA
7
4.0B
262k
-
-
-
Qwen3.5 2B (Reasoning)
Alibaba logoAlibaba
7
2.3B
262k
-
-
-
Phi-4 Mini Instruct
Microsoft logoMicrosoft
6
3.8B
128k
-
45
Microsoft Azure
Qwen3.5 2B (Non-reasoning)
Alibaba logoAlibaba
6
2.3B
262k
-
-
-