Top picks for Long-Document Summarization (2026)
Summarizing books, transcripts, court filings. Ranked from 422 live models on the OpenRouter catalog, weighted for context window, reasoning quality, low cost.
Updated 2026-09-04 · prices checked at this morning's rebuild
Which should you use? Anthropic: Claude Opus 4.7 (batch) tops this ranking on blended score. If cost drives the decision, OpenAI: GPT-5.4 (batch) is the cheapest of the leaders at $1.25/M input.
| # | Model | Score | In / 1M | Out / 1M | Context | |
|---|---|---|---|---|---|---|
| 1 | Anthropic: Claude Opus 4.7 (batch)anthropic/claude-opus-4.7:batch | 178 | $2.50 | $12.50 | 1,000,000 | Details → |
| 2 | Anthropic: Claude Sonnet 4.6 (batch)anthropic/claude-sonnet-4.6:batch | 175 | $1.50 | $7.50 | 1,000,000 | Details → |
| 3 | Anthropic: Claude Sonnet 4.6anthropic/claude-sonnet-4.6 | 174 | $3.00 | $15.00 | 1,000,000 | Details → |
| 4 | Anthropic: Claude Opus 4.7anthropic/claude-opus-4.7 | 171 | $5.00 | $25.00 | 1,000,000 | Details → |
| 5 | Anthropic: Claude Opus 4.8 (batch)anthropic/claude-opus-4.8:batch | 171 | $2.50 | $12.50 | 1,000,000 | Details → |
| 6 | OpenAI: GPT-5.5 (batch)openai/gpt-5.5:batch | 170 | $2.50 | $15.00 | 1,050,000 | Details → |
| 7 | OpenAI: GPT-5.4 (batch)openai/gpt-5.4:batch | 170 | $1.25 | $7.50 | 1,050,000 | Details → |
| 8 | OpenAI: GPT-5.4openai/gpt-5.4 | 169 | $2.50 | $15.00 | 1,050,000 | Details → |
| 9 | DeepSeek: DeepSeek V4 Pro 0423deepseek/deepseek-v4-pro | 169 | $1.04 | $2.08 | 1,048,576 | Details → |
| 10 | Z.ai: GLM 5.2z-ai/glm-5.2 | 168 | $0.97 | $3.04 | 1,048,576 | Details → |
| 11 | Anthropic: Claude Fable 5 (batch)anthropic/claude-fable-5:batch | 166 | $5.00 | $25.00 | 1,000,000 | Details → |
| 12 | Google: Gemini 3.1 Pro Preview (batch)google/gemini-3.1-pro-preview:batch | 165 | $1.00 | $6.00 | 1,048,576 | Details → |
| 13 | Google: Gemini 3.1 Pro Previewgoogle/gemini-3.1-pro-preview | 165 | $2.00 | $12.00 | 1,048,576 | Details → |
| 14 | Anthropic: Claude Opus 4.8anthropic/claude-opus-4.8 | 164 | $5.00 | $25.00 | 1,000,000 | Details → |
| 15 | Meta: Muse Spark 1.3meta/muse-spark-1.3 | 163 | $1.25 | $4.25 | 1,048,576 | Details → |
How we ranked these
For Long-Document Summarization, we weight models on context window, reasoning quality, low cost. Scores combine each model's public specs with independent benchmark results (Aider Polyglot coding scores, Artificial Analysis intelligence/coding/agentic indices) and live pricing. See full methodology →
About Long-Document Summarization
Long-document summarization is the task of reducing books, transcripts, legal filings, or research papers into coherent summaries while preserving key facts and arguments. You need this when manual reading is impractical but you require accurate, domain-specific takeaways without losing critical details. Good models maintain logical flow, catch implicit connections across sections, and avoid hallucinating facts; poor ones produce fragmented summaries, miss context shifts, or invent details. Token limits matter here. A 300-page document may exceed context windows in older models, forcing chunking strategies that increase latency and risk losing cross-document connections that inform summary quality.
When to use: Use this when you need to quickly understand the core content of a lengthy document (book, contract, court transcript, research paper) without reading it entirely, but still need accuracy and specific details preserved.
Common questions
Which AI models handle long documents best without losing information?
Claude 3.5 Sonnet and GPT-4 Turbo handle 100,000+ token contexts effectively, making them strong choices for intact document processing. For documents exceeding context limits, recursive summarization (summarizing chunks, then summarizing summaries) works but introduces compounding error risk. Model selection depends on whether your documents stay within limits or require fragmented approaches.
How much does it cost to summarize a 300-page book, and how long does it take?
A 300-page document is roughly 80,000-120,000 tokens; Claude 3.5 Sonnet charges $3 per 1M input tokens, so expect $0.24-0.36 per book. Processing time is typically 10-30 seconds for a single pass. Chunked approaches cost more (repeated processing) and take longer due to sequential summaries.