Loading
Document summaries, meeting notes, content condensing. Ranked by quality, cost, and real-world performance.
5 models compared · Data powered by Artificial Analysis
Ranked comparison of 5 AI models for summarization tasks. MiniMax M2.1 leads on quality (score 48), while Gemini 3 Flash provides the most affordable entry point.
Summarization tasks require models that can identify key information, maintain factual accuracy, and produce concise outputs. Context window size directly impacts how much content can be summarized in a single pass.
Budget and mid-range models handle summarization well — you don't need frontier-class quality for condensing documents. Focus on models with large context windows to handle longer inputs.
For high-volume summarization (100+ documents/day), free models can significantly reduce costs while maintaining acceptable quality.
| # | Model | Tier | Quality | Price (In/Out) | Est. Cost (100/mo) |
|---|---|---|---|---|---|
| 1 | MiniMax M2.1 MiniMax | Mid-Range | 48 | $0.28 / $1.20 | $0.52 |
| 2 | Gemini 3 Flash Google | Budget | 42 | $0.07 / $0.30 | $0.13 |
| 3 | Claude Haiku 4.5 Anthropic | Budget | 40 | $1.00 / $5.00 | $2.08 |
| 4 | GPT-4o Mini OpenAI | Budget | 38 | $0.15 / $0.60 | $0.26 |
| 5 | Llama 3.3 70B (Free) Meta | Free | 35 | Free / Free | Free |