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. | 8B/49B | — |
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. | 128k | 32k |
| Overview | ||
| Company | NVIDIA | Qwen |
| Release date | Mar 18 2025 | Jan 28 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Llama Nemotron (Nano/Super)vsClaude Haiku 5.5Qwen2.5-MaxvsClaude Haiku 5.5Llama Nemotron (Nano/Super)vsGPT-6.1 SolQwen2.5-MaxvsGPT-6.1 SolLlama Nemotron (Nano/Super)vsGemini 4 ArgonQwen2.5-MaxvsGemini 4 ArgonLlama Nemotron (Nano/Super)vsMuse Spark OpenQwen2.5-MaxvsMuse Spark OpenLlama Nemotron (Nano/Super)vsGrok 4.7Qwen2.5-MaxvsGrok 4.7Llama Nemotron (Nano/Super)vsDeepSeek-V4.1-Flash-1017Qwen2.5-MaxvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Llama Nemotron (Nano/Super) and Qwen2.5-Max don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen2.5-Max shipped 49 days before Llama Nemotron (Nano/Super), so benchmark comparisons should account for the intervening progress.
Context windows are 128k (Llama Nemotron (Nano/Super)) vs 32k (Qwen2.5-Max). Llama Nemotron (Nano/Super) is open weight, while Qwen2.5-Max is closed.
Direct benchmark comparisons are unavailable — Llama Nemotron (Nano/Super) and Qwen2.5-Max don't publish scores on any of the same benchmarks.