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AI Rankings

GPT-4.1 mini: Score, Price and Context Window

Where GPT-4.1 mini from OpenAI ranks, what it costs and how much text it can read, in plain numbers with the sources.

Data updated

  • OpenAI
  • Closed weights
  • Released Apr 2025

Its score range overlaps with Gemini 2.0 Pro, the model just above it, so a small gap in rank is not a meaningful difference.

Best for

  • Very long documents: its context window is 1M tokens, roughly 786,000 words.

These lines are worked out from the numbers on this page, not from hands-on testing.

Key facts

Overall score
134.9
Rank 145 of 270. Likely range 131.0 to 136.5.
Human preference: chat
1383
Rank 114 of 166. 38,701 votes.
Human preference: coding
1433
Rank 111 of 166. 6,821 votes.
Human preference: images
1201
Rank 65 of 85. 40,201 votes.
Price per million tokens
$0.40 in / $1.60 out
Blended $0.70. Cached input $0.10. List price from OpenAI, checked 26 Oct 2026.
Context window
1M tokens
About 786,000 words at once. One answer up to 33K tokens.
Weights
Closed
Used through the maker's apps or API (Epoch AI: API access).

Features listed by the price list: Image input, PDF input, Tool use, Web search, Prompt caching, Structured output.

How GPT-4.1 mini stacks up

Each strip shows every model we track as faint bars. The dot is this model. Better is always to the right, even for price.
GPT-4.1 mini compared with all models we trackOverall capability: 134.9. Better than 46% of the other 269 models. Human preference: chat: 1383. Better than 31% of the other 165 models. Human preference: coding: 1433. Better than 33% of the other 165 models. Human preference: images: 1201. Better than 23% of the other 84 models. Price: $0.70 per 1M. Cheaper than 61% of the other 200 priced models. Context window: 1M tokens. Larger context window than 83% of the other 198 models.
  • Overall capability134.9

    Better than 46% of the other 269 models

    Epoch Capabilities Index: one score that combines many tests.

  • Human preference: chat1383

    Better than 31% of the other 165 models

    How often people pick its answers over another model's on Arena.

  • Human preference: coding1433

    Better than 33% of the other 165 models

    How often people pick its answers to coding questions on Arena.

  • Human preference: images1201

    Better than 23% of the other 84 models

    How often people pick its answers about pictures on Arena.

  • Price$0.70 per 1M

    Cheaper than 61% of the other 200 priced modelsUpper half

    Blended price per million tokens. Lower is better, so the cheapest models sit on the right.

  • Context window1M tokens

    Larger context window than 83% of the other 198 modelsTop 25%

    How much text it can read at once. Bigger suits long documents.

Compared with the other published models that have each measure. Data updated 26 Oct 2026.

Test results

Each test checks one kind of skill. Place shows where it stands among the models that took that test.
  • GPQA Diamond

    Very hard multiple-choice science questions in biology, physics and chemistry, written by experts and designed so a quick web search does not give the answer.

  • OTIS Mock AIME

    Maths competition problems in the style of the US AIME exam, from the 2024 and 2025 sets. Every answer is a whole number.

    44.7%

    Place 119 of 174

  • Aider Polyglot

    225 coding exercises in six programming languages. The AI edits the code files and the exercise's tests decide pass or fail.

  • ARC-AGI-2

    Visual puzzles where the AI must work out a new rule from a few examples and apply it. They test picking up a new idea quickly, not recalling facts.

    0.0%

    Place 79 of 86

    tied with 7 others

  • SimpleQA Verified

    Short factual questions that each have one correct answer. It measures how often a model gets facts right.

  • FrontierMath (Tiers 1-3)

    Original, very hard maths problems written by mathematicians. Each has an exact answer and the problems are kept private so models cannot have memorised them. This is the Tiers 1 to 3 set, version 2.

What it costs in everyday terms

List prices turned into amounts you can picture. Real bills depend on how you use it.
100 chats
$0.12
Cost of 100 chats assumes each chat sends 1,000 tokens (about 750 words) and gets 500 tokens (about 375 words) back.
A 300-page book
$0.04
Cost to read a 300-page book assumes about 100,000 input tokens and no reply. A real book varies with page size and language.
Blended price
$0.70 per 1M
Three parts input to one part output. Our own calculation for comparing models.

Assumptions: 100 chats of about 1,000 tokens in and 500 tokens back. a 300-page book of about 100,000 tokens, read once with no reply.

Questions about GPT-4.1 mini

How much does GPT-4.1 mini cost?
GPT-4.1 mini costs $0.40 per million input tokens and $1.60 per million output tokens, using the list price from OpenAI as of 26 Oct 2026. That is about $0.12 for 100 chats of about 1,000 tokens in and 500 tokens back. Confirm on the maker's site before you buy, because prices change.
What is the context window of GPT-4.1 mini?
GPT-4.1 mini has a context window of 1M tokens, roughly 786,000 words of text read at once. A single answer can be up to 33K tokens long.
Is GPT-4.1 mini open source?
We list GPT-4.1 mini as closed: it is used through its maker's apps or API and its weights are not published (Epoch AI lists its access as "API access").
How good is GPT-4.1 mini compared with other AI models?
On the Epoch Capabilities Index, GPT-4.1 mini scores 134.9 (likely range 131.0 to 136.5), which ranks 145 of 270 models we track. On Arena's human-vote text board it is ranked 114 of 166. Scores close together are a tie in practice.
How does GPT-4.1 mini compare with Gemini 2.0 Pro?
Gemini 2.0 Pro scores higher on 1 of 3 shared quality measures, GPT-4.1 mini on 0. 2 measures are too close to call. See the full comparison for every measure.
How current are these numbers for GPT-4.1 mini?
The newest data on this page is dated 26 Oct 2026. Scores come from Epoch AI and Arena, prices from the open LiteLLM price list.

Where this data comes from

  • Epoch AI: Benchmark data: Epoch AI, 'Capabilities & benchmarking', epoch.ai/benchmarks (CC BY 4.0). We match models across sources, rank them and show them in charts. Scores are not changed. Epoch AI does not endorse this site.
  • Arena (formerly LMArena): Human-preference ratings: Arena (arena.ai) leaderboard dataset, CC BY 4.0. We keep the latest published ratings, match them to models from other sources and rank them. Ratings are not changed. Arena does not endorse this site.
  • LiteLLM model price list: Prices and context windows: LiteLLM model price list (github.com/BerriAI/litellm, MIT licence). We use the model maker's own price entry when there is one. Prices change often, so always confirm on the maker's site before you buy.

Newest data on this page: 26 Oct 2026. Prices are list prices and change often, so confirm on the maker's site before you buy. Sponsors never change a score or an order. How we calculate this · Report a mistake

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