100% Free Open Source AI Hub

Top Open Source AI Models& Free Cloud GPUs

Discover the world's best open-weights models (DeepSeek, Llama, Qwen, Flux). Check detailed pros & cons, hardware requirements, and run them free on Google Colab or your PC.

Top Trending ReasoningMIT (Full Open Source)DeepSeek AI

DeepSeek-R1 (671B MoE & Distills)

Open-weight reasoning powerhouse rivaling OpenAI o1 and o3 at 95% lower compute cost.

Local PC VRAM:8GB for 7B / 14GB for 14B / 24GB for 32B / 40GB+ for 70B
Free Cloud GPU:Google Colab (T4 for 7B/8B), Kaggle (14B), RunPod RTX 4090/A100 (32B/70B)
Parameters / Sizes:671B (37B active) / Distills: 1.5B, 7B, 8B, 14B, 32B, 70B

DeepSeek-R1 utilizes massive reinforcement learning (RL) without supervised warmups to produce long chain-of-thought internal reasoning. It excels at PhD-level mathematics (AIME), complex multi-file coding refactors, and algorithmic problem solving.

Fayde / Key Advantages

  • Near-parity with proprietary models like OpenAI o1 on coding and mathematics
  • Distilled versions (7B, 14B, 32B) can run locally on consumer RTX 3060/4070/4090 GPUs
  • Permissive MIT license allows commercial modification and deployment
  • Native support in Ollama, vLLM, LM Studio, and HuggingFace

Nuksan / Limitations

  • Full 671B model requires massive multi-GPU clusters (8x H100 or dual 80GB)
  • Verbose thinking tokens take longer to generate than standard conversational LLMs
  • Occasional language mixing in long chain-of-thought without strict system prompt
1-Click Run CommandsSelect runtime
vllm
vllm serve deepseek-ai/DeepSeek-R1-Distill-Qwen-14B --port 8000 --gpu-memory-utilization 0.9
ollama
ollama run deepseek-r1:8b
# Or for high accuracy:
ollama run deepseek-r1:14b
google colab
!pip install -q vllm
from vllm import LLM, SamplingParams
llm = LLM('deepseek-ai/DeepSeek-R1-Distill-Qwen-7B')
output = llm.generate(['Explain quantum computing with step by step reasoning:'])

Recommended Free Cloud Platforms for DeepSeek-R1 (671B MoE & Distills):

Google Colab
Free (T4 GPU)
Runs 7B / 8B distilled models smoothly
Kaggle
Free (Dual T4 - 30 hrs/wk)
Runs 14B quantized model
Groq / Together AI
Free Tier API
Sub-second 300+ tokens/sec inference
Top Open Source CoderApache 2.0 (Permissive Open Source)Alibaba Cloud

Qwen 2.5 Coder (32B & 7B)

The highest-rated open-source coding model in the world, matching GPT-4o on real-world software development.

Local PC VRAM:6GB for 7B / 18GB for 32B (Q4)
Free Cloud GPU:Google Colab Free (7B/14B), Kaggle (14B/32B), RunPod ($0.25/hr RTX 3090/4090)
Parameters / Sizes:32B, 14B, 7B, 3B, 1.5B, 0.5B
Top Visual ModelApache 2.0 (schnell) / Non-Commercial (dev)Black Forest Labs

FLUX.1 [schnell] & [dev]

The 12B transformer that beat Midjourney v6 in photorealism, typography rendering, and prompt adherence.

Local PC VRAM:12GB VRAM (with GGUF/NF4 quantization) / 24GB recommended
Free Cloud GPU:Google Colab Free (T4 with NF4), RunPod ($0.30/hr RTX 4090), HuggingFace Spaces
Parameters / Sizes:12 Billion Parameters (Flow Matching Transformer)
Universal Audio StandardMIT (Full Open Source)OpenAI

OpenAI Whisper (Large-v3 & Turbo)

The undisputed gold standard in multi-language audio transcription and translation.

Local PC VRAM:2GB - 6GB VRAM (Runs on almost any laptop/PC or CPU)
Free Cloud GPU:Google Colab Free, Kaggle, Local CPU / Apple Silicon M-series
Parameters / Sizes:1.55 Billion Parameters / Turbo: 809 Million
Industry StandardLlama 3.3 Community License (Commercial up to 700M MAU)Meta AI

Meta Llama 3.3 (70B & 8B)

Meta's flagship open-weights model delivering 405B-class performance in an efficient 70B footprint.

Local PC VRAM:6GB for 8B (4-bit) / 40GB for 70B (4-bit)
Free Cloud GPU:Google Colab Free (8B), Kaggle (8B/14B), Vast.ai / RunPod 1x RTX 4090 / A6000 (70B)
Parameters / Sizes:70B Dense / 8B Dense
Top European FrontierMistral Research License (Free for research/testing)Mistral AI

Mistral Large 2 (123B) & Codestral

Elite 128k context model rivaling GPT-4o in reasoning, mathematics, coding, and multi-lingual fluency.

Local PC VRAM:14GB for Codestral 22B (4-bit) / 70GB+ for Large 2
Free Cloud GPU:Google Colab (Codestral), RunPod / Vast.ai (Mistral Large 2)
Parameters / Sizes:123 Billion Dense / Codestral: 22B