Compare AI models

Specifications
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality.
—671B
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider.
100k128k
Benchmarks
HumanEvalFunction synthesis — 164 small Python problems: the AI is given a function's description and has to write the working function. This was the coding benchmark of the GPT-3.5 and GPT-4 era, before the field moved to fixing real bugs in real repositories. Higher is better.
58.7%65.2%
GSM8KGrade-school math — Grade-school maths word problems that take a few steps of arithmetic to work through. It separated the models of 2022 and 2023 sharply, then saturated. One caveat on the historical numbers: OpenAI included part of the GSM8K training set in GPT-4's pre-training mix, so GPT-4's score is not a clean few-shot result. Higher is better.
86.7%89.3%
Overview
CompanyAnthropicDeepSeek
Release dateAug 9 2023Dec 25 2024
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

DeepSeek V3 Base leads Claude Instant 1.2 on 2 of the 2 benchmarks they both report (HumanEval, GSM8K). Claude Instant 1.2 shipped 504 days before DeepSeek V3 Base, so benchmark comparisons should account for the intervening progress.

Context windows are 100k (Claude Instant 1.2) vs 128k (DeepSeek V3 Base). Claude Instant 1.2 is closed, while DeepSeek V3 Base is open weight.

On HumanEval, DeepSeek V3 Base leads at 65.2% vs Claude Instant 1.2 at 58.7%. On GSM8K, DeepSeek V3 Base leads at 89.3% vs Claude Instant 1.2 at 86.7%.