Compare AI models

Specifications
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one.
—1T
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view.
—256k
API pricingUSD per 1M tokens · lower wins · base tier
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
—$1.20
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.
—$6.00
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.
$0.15DeepSeek—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.60DeepSeek—
$60.00DeepSeek$540Qwen list price
These models have no shared benchmark scores.
Overview
CompanyDeepSeekQwen
Release dateOct 17 2026Sep 24 2025
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

DeepSeek-V4.1-Flash-1017 and Qwen3-Max don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3-Max has a verified first-party API price: $1.20 per million input tokens and $6.00 per million output tokens. No pay-as-you-go API rate is tracked for DeepSeek-V4.1-Flash-1017. Qwen3-Max shipped 388 days before DeepSeek-V4.1-Flash-1017, so benchmark comparisons should account for the intervening progress.

DeepSeek-V4.1-Flash-1017 is open weight, while Qwen3-Max is closed.

Direct benchmark comparisons are unavailable — DeepSeek-V4.1-Flash-1017 and Qwen3-Max don't publish scores on any of the same benchmarks.