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 | 1M |
| 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. | — | $1.50 |
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. | — | $0.125Google AI Studio |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.75Google AI Studio |
| — | $125Google list price | |
| These models have no shared benchmark scores. | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 11% |
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% | — |
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% | — |
| Overview | ||
| Company | Anthropic | |
| Release date | Aug 9 2023 | Mar 3 2026 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
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Claude Instant 1.2 and Gemini 3.1 Flash-Lite don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Gemini 3.1 Flash-Lite has a verified first-party API price: $0.25 per million input tokens and $1.50 per million output tokens. No pay-as-you-go API rate is tracked for Claude Instant 1.2. Claude Instant 1.2 shipped 937 days before Gemini 3.1 Flash-Lite, so benchmark comparisons should account for the intervening progress.
Context windows are 100k (Claude Instant 1.2) vs 1M (Gemini 3.1 Flash-Lite).
Direct benchmark comparisons are unavailable — Claude Instant 1.2 and Gemini 3.1 Flash-Lite don't publish scores on any of the same benchmarks.