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. | 7B/13B/33B/65B | 397B |
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. | 2k | 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. | — | $0.40 |
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. | — | $2.40 |
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. | — | $0.26Alibaba |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $1.56Alibaba |
| — | $130Alibaba | |
| Overview | ||
| Company | Meta | Qwen |
| Release date | Feb 24 2023 | Feb 16 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
LLaMA 1vsClaude Haiku 5.5Qwen3.5-PlusvsClaude Haiku 5.5LLaMA 1vsGPT-6.1 SolQwen3.5-PlusvsGPT-6.1 SolLLaMA 1vsGemini 4 ArgonQwen3.5-PlusvsGemini 4 ArgonLLaMA 1vsGrok 4.7Qwen3.5-PlusvsGrok 4.7LLaMA 1vsDeepSeek-V4.1-Flash-1017Qwen3.5-PlusvsDeepSeek-V4.1-Flash-1017LLaMA 1vsMistral Large 4Qwen3.5-PlusvsMistral Large 4Frequently asked questions
LLaMA 1 and Qwen3.5-Plus don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3.5-Plus has a verified first-party API price: $0.40 per million input tokens and $2.40 per million output tokens. No pay-as-you-go API rate is tracked for LLaMA 1. LLaMA 1 shipped 1088 days before Qwen3.5-Plus, so benchmark comparisons should account for the intervening progress.
LLaMA 1 has 7B/13B/33B/65B parameters, while Qwen3.5-Plus has 397B. Context windows are 2k (LLaMA 1) vs 1M (Qwen3.5-Plus). LLaMA 1 is open weight, while Qwen3.5-Plus is closed.
Direct benchmark comparisons are unavailable — LLaMA 1 and Qwen3.5-Plus don't publish scores on any of the same benchmarks.