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. | 200k | 1M |
| 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. | $15.00 | $0.50 |
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. | $60.00 | $3.00 |
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. | $7.50 | — |
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. | $15.00OpenAI | $0.325Alibaba |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $60.00OpenAI | $1.95Alibaba |
| $6,000OpenAI list price | $163Alibaba | |
| 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. | — | 72% |
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | — | 78.8% |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | — | 28.8% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 75.7% | — |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Dec 5 2024 | Apr 2 2026 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
o1vsClaude Haiku 5.5Qwen3.6-PlusvsClaude Haiku 5.5o1vsGemini 4 ArgonQwen3.6-PlusvsGemini 4 Argono1vsMuse Spark OpenQwen3.6-PlusvsMuse Spark Openo1vsGrok 4.7Qwen3.6-PlusvsGrok 4.7o1vsDeepSeek-V4.1-Flash-1017Qwen3.6-PlusvsDeepSeek-V4.1-Flash-1017o1vsMistral Large 4Qwen3.6-PlusvsMistral Large 4Frequently asked questions
o1 and Qwen3.6-Plus don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen3.6-Plus is cheaper on both input and output: $0.50 vs $15.00 per million input tokens, and $3.00 vs $60.00 per million output tokens. Figures are base-tier rates. o1 shipped 483 days before Qwen3.6-Plus, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (o1) vs 1M (Qwen3.6-Plus).
Direct benchmark comparisons are unavailable — o1 and Qwen3.6-Plus don't publish scores on any of the same benchmarks.