Compare AI models
| Specifications | ||
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. | 100k | 400k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $0.25 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $2.00 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | — | $0.025 |
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $0.125OpenAI |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $1.00OpenAI |
| — | $150OpenAI list price | |
| These models have no shared benchmark scores. | ||
ProgramBenchProgram reconstruction — The AI receives a working program and its documentation, then builds a replacement from scratch without the original source code, internet access or decompilation. The score is the percentage of 200 programs that pass every behavioral test. We record each model's best published mini-SWE-agent result, including higher reasoning efforts where available. Partial test-pass rates and almost-solved programs do not count toward this score. Equal scores share a rank here; the official board also uses partial progress to break ties. Higher is better. | — | 0% |
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. | 71.2% | — |
MMLUGeneral knowledge — A 57-subject multiple-choice exam — history, law, medicine, maths — that was the standard measure of how much a model knows from 2020 until roughly 2024, when frontier scores crowded into the high 80s and labs moved on to harder tests. The scores here were published years apart under different testing setups, so read them as a historical record rather than a like-for-like ranking. Higher is better. | 78.5% | — |
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. | 88% | — |
| Overview | ||
| Company | Anthropic | OpenAI |
| Release date | Jul 11 2023 | Aug 7 2025 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Claude 2vsGemini 4 ArgonGPT-5 minivsGemini 4 ArgonClaude 2vsMuse Spark OpenGPT-5 minivsMuse Spark OpenClaude 2vsGrok 4.7GPT-5 minivsGrok 4.7Claude 2vsDeepSeek-V4.1-Flash-1017GPT-5 minivsDeepSeek-V4.1-Flash-1017Claude 2vsMistral Large 4GPT-5 minivsMistral Large 4Claude 2vsKimi K3GPT-5 minivsKimi K3Frequently asked questions
Claude 2 and GPT-5 mini don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only GPT-5 mini has a verified first-party API price: $0.25 per million input tokens and $2.00 per million output tokens. No pay-as-you-go API rate is tracked for Claude 2. Claude 2 shipped 758 days before GPT-5 mini, so benchmark comparisons should account for the intervening progress.
Context windows are 100k (Claude 2) vs 400k (GPT-5 mini).
Direct benchmark comparisons are unavailable — Claude 2 and GPT-5 mini don't publish scores on any of the same benchmarks.