Ministral 3B
Mistral AI's smallest open-weight model - 3B parameters, 256K context, Apache 2.0 license, built for edge and cost-sensitive deployments.
Articles Tagged "Small Language Models"
ZAYA1-8B: Open Reasoning Model Rivals Claude on AMD GPUs
Zyphra's ZAYA1-8B matches Claude 4.5 Sonnet on HMMT 2025 math benchmarks at just 760M active parameters, trained entirely on AMD Instinct MI300X GPUs under Apache 2.0.
ZAYA1-8B
Zyphra's ZAYA1-8B is an 8.4B-parameter MoE reasoning model with only 760M active parameters that matches DeepSeek-R1-0528 on math and coding benchmarks while running at a fraction of the compute cost.
Edge and Mobile LLM Leaderboard 2026: Phi, Gemma, Qwen
Rankings of the best LLMs for on-device edge inference - phones, laptops without GPUs, Raspberry Pi, and Jetson - scored by quality benchmarks and real tokens/sec on iPhone, MacBook, and Raspberry Pi 5.
Google AI Edge Gallery Puts Gemma 4 on Your Phone
Google's AI Edge Gallery officially launched on the Play Store and App Store on April 9, running Gemma 4 E2B and E4B models fully offline on any phone from Android 12 or iOS 17 onward.
Microsoft Phi-4 Reasoning: Small Model, Big Math
Microsoft's Phi-4 reasoning family delivers near-70B-class math performance in a 14B open-weight package, but the overthinking problem is real and the use case is narrower than the benchmarks suggest.
Nemotron 3 Nano 4B: NVIDIA Edge Model Runs on 8GB
NVIDIA's Nemotron 3 Nano 4B packs a Mamba-dominant hybrid architecture, 262K token context, and 95.4% on MATH500 into a model that fits an 8GB Jetson Orin Nano.
Mistral Small 4 Review: One Model, Three Jobs
Mistral Small 4 packs reasoning, vision, and agentic coding into a 119B MoE under Apache 2.0 - a serious small-model contender at a price that's hard to ignore.
Small Language Model Leaderboard: Best Under 10B
Rankings of the best small language models under 10 billion parameters, comparing Phi-4, Gemma 3, Qwen 3.5, and more across key benchmarks.
Microsoft's Phi-4 Vision Matches Models 10x Its Size
Microsoft releases Phi-4-reasoning-vision-15B - a 15B open-weight multimodal model trained on 240 GPUs in 4 days that competes with 100B+ parameter models on math, science, and GUI understanding.
Qwen 3.5 Small Series Ships Four Models From 0.8B to 9B
Alibaba completes the Qwen 3.5 lineup with four small models - 0.8B, 2B, 4B, and 9B - all natively multimodal, 262K context, Apache 2.0. The 9B outperforms last-gen Qwen3-30B and beats GPT-5-Nano on vision benchmarks.
Qwen3.5-0.8B
Qwen3.5-0.8B is the smallest natively multimodal model in the Qwen 3.5 family - 0.8B parameters handling text, images, and video with 262K context. MathVista 62.2, OCRBench 74.5. Apache 2.0.
