🤖 GPT Models & Alternatives
Explore the evolution of GPT, compare leading models, and understand the competitive landscape of generative AI.
The GPT Evolution Timeline
GPT-2
2019
1.5B
parameters
Capabilities:
Basic text generation, few-shot learning impossible
🎯 Breakthrough:
First proof of scaling concept
GPT-3
2020
175B
parameters
Capabilities:
Few-shot learning, reasoning, code generation
🎯 Breakthrough:
Emergent abilities from scale
GPT-3.5
2022
175B
parameters
Capabilities:
RLHF training, instruction following, ChatGPT
🎯 Breakthrough:
Made AI accessible to millions
GPT-4
2023
~1.7T
parameters
Capabilities:
Multimodal, superior reasoning, 128K context
🎯 Breakthrough:
SOTA on benchmarks, near-human level
GPT-4 Turbo
2024
~1.7T
parameters
Capabilities:
128K tokens, function calling, vision
🎯 Breakthrough:
Faster, cheaper, more capable
📊 Scaling Laws Insight
GPT's evolution demonstrates clear scaling laws: performance improves predictably with more parameters, data, and compute. This has enabled researchers to forecast capabilities before training.
Each generation represents roughly 10x parameters but shows 100x+ improvement in specific capabilities. This superlinear scaling suggests we haven't reached physical limits yet.