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. | 2M | 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. | — | $12.50 |
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. | — | $75.00 |
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. | — | $1.25 |
| — | $6,250OpenAI list price | |
| These models have no shared benchmark scores. | ||
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | 36% | — |
Advanced Cybersecurity Completion Rate (Internal)Agentic tasks — share of advanced cyber requests the model responds to; measures willingness to answer, not exploit success | — | 95% |
MATHReasoning — accuracy on the original competition mathematics test set | 91.8% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 64.7% | — |
SimpleQAKnowledge — accuracy on short, fact-seeking questions in the original SimpleQA set | 44.3% | — |
MMLU-ProKnowledge — accuracy on the ten-option MMLU-Pro benchmark | 79.1% | — |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | 72.7% | — |
| Overview | ||
| Company | OpenAI | |
| Release date | Feb 5 2025 | Aug 10 2026 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Gemini 2.0 ProvsClaude Fable 5.2GPT-5.6 CybervsClaude Fable 5.2Gemini 2.0 ProvsMuse EmberGPT-5.6 CybervsMuse EmberGemini 2.0 ProvsGrok 4.7GPT-5.6 CybervsGrok 4.7Gemini 2.0 ProvsDeepSeek-V4.1-Flash-1017GPT-5.6 CybervsDeepSeek-V4.1-Flash-1017Gemini 2.0 ProvsMistral Large 4GPT-5.6 CybervsMistral Large 4Gemini 2.0 ProvsKimi K3.1 ProGPT-5.6 CybervsKimi K3.1 ProFrequently asked questions
Gemini 2.0 Pro and GPT-5.6 Cyber don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only GPT-5.6 Cyber has a verified first-party price for an available API: $12.50 per million input tokens and $75.00 per million output tokens. No currently available pay-as-you-go API rate is tracked for Gemini 2.0 Pro. Gemini 2.0 Pro shipped 551 days before GPT-5.6 Cyber, so benchmark comparisons should account for the intervening progress.
Context windows are 2M (Gemini 2.0 Pro) vs 400k (GPT-5.6 Cyber).
Direct benchmark comparisons are unavailable — Gemini 2.0 Pro and GPT-5.6 Cyber don't publish scores on any of the same benchmarks.