Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | — | 0.5B/1.5B/3B/7B/14B/32B |
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 | 128k |
| 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. | $2.00 | — |
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. | $8.00 | — |
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. | $0.50 | — |
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. | $2.00OpenAI | $0.66Cloudflare |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $8.00OpenAI | $1.00Cloudflare |
| $800OpenAI list price | $182Cloudflare | |
| 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. | 26% | — |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Apr 16 2025 | Nov 12 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
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o3 and Qwen2.5-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only o3 has a verified first-party API price: $2.00 per million input tokens and $8.00 per million output tokens. No pay-as-you-go API rate is tracked for Qwen2.5-Coder. Qwen2.5-Coder shipped 155 days before o3, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (o3) vs 128k (Qwen2.5-Coder). o3 is closed, while Qwen2.5-Coder is open weight.
Direct benchmark comparisons are unavailable — o3 and Qwen2.5-Coder don't publish scores on any of the same benchmarks.