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. | 32k | 128k |
| 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. | — | $0.70 |
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. | — | $2.80 |
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 | |
| 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. | — | 6% |
| Overview | ||
| Company | Qwen | |
| Release date | Feb 8 2024 | Apr 29 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 1.0 UltravsClaude Haiku 5.5Qwen3vsClaude Haiku 5.5Gemini 1.0 UltravsGPT-6.1 SolQwen3vsGPT-6.1 SolGemini 1.0 UltravsMuse Spark OpenQwen3vsMuse Spark OpenGemini 1.0 UltravsGrok 4.7Qwen3vsGrok 4.7Gemini 1.0 UltravsDeepSeek-V4.1-Flash-1017Qwen3vsDeepSeek-V4.1-Flash-1017Gemini 1.0 UltravsMistral Large 4Qwen3vsMistral Large 4Frequently asked questions
Gemini 1.0 Ultra and Qwen3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3 has a verified first-party API price: $0.70 per million input tokens and $2.80 per million output tokens. No pay-as-you-go API rate is tracked for Gemini 1.0 Ultra. Gemini 1.0 Ultra shipped 446 days before Qwen3, so benchmark comparisons should account for the intervening progress.
Context windows are 32k (Gemini 1.0 Ultra) vs 128k (Qwen3). Gemini 1.0 Ultra is closed, while Qwen3 is open weight.
Direct benchmark comparisons are unavailable — Gemini 1.0 Ultra and Qwen3 don't publish scores on any of the same benchmarks.