Best LLM for summarization (2026): quality & ₹ cost

Best LLM for document summarization

Summarization is high-volume: one call per document, thousands a day. Cost and quality both matter, and they trade off differently by model. Claude Sonnet preserves tone and nuance. DeepSeek V3.2 wins on speed and price. GPT-4o handles dense, multi-topic documents well. Here's the 2026 picture, priced in rupees on unoblox.

Summarization LLM head-to-head

Model	₹ input / 1M	₹ output / 1M	Latency	Best for
DeepSeek V3.2	₹26.21	₹38.30	Fast	High-volume, factual summaries
Claude Sonnet	₹201.6	₹1,008	Moderate	Nuanced, editorial, brand voice
GPT-4o	₹252	₹1,008	Moderate	Complex, multi-topic documents
Qwen3 Max	₹120.95	₹604.77	Moderate	Balanced quality and speed

Calling the API — same pattern for every model

from openai import OpenAI

client = OpenAI(
    api_key="ub-gw-...",
    base_url="https://api.unoblox.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek-ai/deepseek-v3.2",  # swap for gpt-4o, claude-sonnet, qwen3-max
    messages=[
        {"role": "system", "content": "Summarize in 3 sentences, factual tone."},
        {"role": "user", "content": document_text}
    ]
)

DeepSeek V3.2 — the budget pick

Fast and reliably factual. Best for news articles, research abstracts, product docs, and support-ticket summaries where tone matters less than getting the facts right. Roughly ₹0.04 per 1,000-word document (input + output combined).

Claude Sonnet — the quality pick

Preserves tone, nuance, and brand voice — the right choice for blog posts, whitepapers, executive briefs, and anything a reader will notice was summarized badly. Roughly ₹0.41 per 1,000-word document.

GPT-4o — the complexity pick

Handles dense, multi-topic, cross-referencing documents accurately — legal briefs, research papers, policy documents. Roughly ₹0.48 per 1,000-word document.

₹ math at 10,000 documents a month

• DeepSeek V3.2: 10,000 × ₹0.04 ≈ ₹400/month
• Claude Sonnet: 10,000 × ₹0.41 ≈ ₹4,100/month
• GPT-4o: 10,000 × ₹0.48 ≈ ₹4,800/month

When to pick each

• DeepSeek: news feeds, support tickets, internal product summaries, high-volume automation.
• Claude: marketing copy, brand-sensitive content, editorial pieces read by humans who'll notice a flat summary.
• GPT-4o: legal and compliance documents, dense research, anything spanning multiple topics that needs to stay correctly cross-referenced.

Frequently asked questions

Does summarization quality differ meaningfully between models? Somewhat. Claude and GPT-4o preserve tone better; DeepSeek is strongest at pure factual extraction. For straightforward information retrieval, all three are close enough to pick on cost.

Should I always use the cheapest model? Not if the summary is user-facing — invest in Claude or GPT-4o there. For internal or high-volume pipelines, DeepSeek saves real money without a visible quality drop.

How long a document can these models handle? All three comfortably summarize 10,000-word documents. Beyond that, chunk-and-summarize (or a longer-context model) works better than one giant prompt.

Can I A/B test models on my own documents? Yes — point the same request at https://api.unoblox.ai/v1, swap only the model field, and compare output side by side on real data.

Is there a limit on summary length? No — all models respect the standard max_tokens parameter; set it per request based on how long you want the output.

Do these models summarize well in Hindi? Yes — DeepSeek and Qwen3 Max both handle Hindi summarization well using the same prompts as English.

Get started in rupees → https://unoblox.ai/sign-in