Best AI for summarising text

As of 2026-10-13, Google: Gemini 3.5 Flash Lite is the strongest model for this task in our daily benchmark, where over 350 AI models are evaluated and the best are presented.

A summary is only useful if it stays within the source and within the length you asked for. That is exactly where models diverge: many return a summary twice as long as requested, or add points that are not in the text.

For summaries we rank by how precisely the model follows instructions. Ranked by instruction score, from today’s benchmark.

Runner-up
Anthropic: Claude Opus 5.5
anthropic
Score: 8.3/10
Language: 9.0/10
Speed: 266 t/s
$4.00
Third choice
Cohere: Command R+ (08-2024)
cohere
Score: 8.3/10
Language: 9.3/10
Speed: 276 t/s
$2.50

Today’s ranking

ModelProviderScoreLanguageSpeedInput price/1M
Google: Gemini 3.5 Flash Litegoogle8.7/109.7/10178 t/s$0.30
Anthropic: Claude Opus 5.5anthropic8.3/109.0/10266 t/s$4.00
Cohere: Command R+ (08-2024)cohere8.3/109.3/10276 t/s$2.50
Meta: Llama 4 Maverickmeta-llama7.5/108.7/10111 t/s$0.19
OpenAI: GPT-6 Astraopenai7.4/108.3/10160 t/s$10.00
Mistral: Mistral Nemomistralai7.2/108.3/10131 t/s$0.03
DeepSeek: DeepSeek V4 Flash 0731deepseek8.1/108.7/10452 t/s$0.02
Anthropic: Claude Sonnet 5.5anthropic8.0/109.0/10200 t/s$2.00

Ask for a format, not just “a summary”

Say how long it should be, who it is for and what it will be used for: “five bullets for an executive making a decision” produces something entirely different from “summarise this”. It also helps to ask the model to separate what the text actually says from what it is inferring.

Check against the source

The most common failure in AI summaries is not outright fabrication but weighting: a side point gets promoted to the main conclusion. Always read the summary with the source alongside it when it will be used for anything that matters.

hvilkenAI is independent. We have no affiliate agreements, sponsored placements or commercial ties to the AI providers we test. Every recommendation rests on test results alone.

Frequently asked questions

Which AI is best at summarising?
The ranking above comes from today’s benchmark. We evaluate over 350 models and present the ones that follow instructions most precisely.
Can AI summarise an entire book?
Most models have enough context for long documents, but quality drops as the text gets very long. Split it into chapters and summarise stepwise for a better result.
Why is the summary longer than I asked for?
Models tend to elaborate. State a hard limit — “80 words maximum” — and repeat it at the end of the prompt.
Can I trust an AI summary?
As a starting point, yes. As the sole basis for a decision, no — verify the claims that actually matter against the original.

Other tasks

Doing something else? See which model is best for it.

→ Other tasks

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How to get more value from this recommendation

Use this recommendation as a practical decision aid, not as an advertising list. HvilkenAI is built to make AI selection easier when the market changes quickly and model names alone say little about real quality.

Start with the task you actually need to solve. A model that is good at short chat is not automatically best for long documents, code, customer-facing text, research or work involving sensitive information. Consider language quality, price, speed, stability and how much editing the answer requires before choosing a subscription or API.

We evaluate over 350 AI models and present the most useful signals in a format that works for everyday users, students, businesses and developers. The exact calculation is proprietary, but the assessment is based on standardised tasks, updated benchmark data and editorial review of whether the recommendations make sense in practical use.

For important decisions, run a small test of your own: use the same prompt, language and expected format in two or three relevant models. Look at precision, source handling, tone, speed and how easy the answer is to verify. That makes the benchmark a time-saving starting point, not a final answer you must follow blindly.

Use the links on the page as well. One page rarely gives the whole picture: the benchmark shows today’s numbers, the AI test translates your need into concrete recommendations, and the privacy/terms pages explain which data and limitations you should consider. Used together, these sources make the choice more robust than following a model name from social media.

If the result will be used at work, document why the tool was chosen: which task it solves, which alternatives were considered, which data should not be shared and how the answer will be quality-checked. That makes it easier to switch model later if price, quality or provider terms change.

When a page is included in the sitemap, it should also stand on its own as a useful explanation. That is why we emphasise practical choices, concrete control questions and clear limits for how data can be used.

The goal is that the reader can move on with a safer choice after a few minutes, without already knowing every model or provider.

Pay particular attention to whether the recommendation fits the language, price and risk in your own situation.

In short: choose what you can verify.

When free is enough

Choose free or low-cost first when the task is simple, risk is low and you can verify the answer yourself.

When paid is worth it

Paid models can be worth the cost when documents are long, precision matters or you save real working time.

When to wait

If the need is unclear, start with the test and benchmark before committing to a provider.