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. | — | 0.6B/1.7B/4B/8B/14B/30B/32B/235B |
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. | 400k | — |
| API pricingUSD per 1M tokens · lower wins | ||
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. | — | $0.08DeepInfra |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.22NextBit |
| — | $30.00DeepInfra · fp8 | |
| Benchmarks | ||
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. | 32% | 6% |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Nov 13 2025 | Apr 29 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
GPT-5.1-CodexvsClaude Fable 5.2Qwen3vsClaude Fable 5.2GPT-5.1-CodexvsGemini 4 CarbonQwen3vsGemini 4 CarbonGPT-5.1-CodexvsMuse EmberQwen3vsMuse EmberGPT-5.1-CodexvsGrok 4.7Qwen3vsGrok 4.7GPT-5.1-CodexvsDeepSeek-V4.1-Flash-1017Qwen3vsDeepSeek-V4.1-Flash-1017GPT-5.1-CodexvsMistral Large 4Qwen3vsMistral Large 4Frequently asked questions
GPT-5.1-Codex leads Qwen3 on 1 of the 1 benchmark they both report (BullshitBench v2). Qwen3 shipped 198 days before GPT-5.1-Codex, so benchmark comparisons should account for the intervening progress.
GPT-5.1-Codex is closed, while Qwen3 is open weight.
On BullshitBench v2, GPT-5.1-Codex leads at 32% vs Qwen3 at 6%.