AI Rankings
o4-mini: Score, Price and Context Window
Data updated
- OpenAI
- Closed weights
- Released Apr 2025
Its score range overlaps with MiniMax-M2.7, the model just above it, so a small gap in rank is not a meaningful difference.
Key facts
- Price per million tokens
- $1.10 in / $4.40 out
- Blended $1.93. Cached input $0.28. List price from OpenAI, checked 26 Oct 2026.
Features listed by the price list: Image input, PDF input, Tool use, Reasoning, Web search, Prompt caching, Structured output.
How o4-mini stacks up
- Overall capability145.5
Better than 67% of the other 269 modelsUpper half
Epoch Capabilities Index: one score that combines many tests.
- Human preference: chat1391
Better than 35% 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 25% of the other 84 models
How often people pick its answers about pictures on Arena.
- Price$1.93 per 1M
Cheaper than 39% of the other 200 priced models
Blended price per million tokens. Lower is better, so the cheapest models sit on the right.
- Context window200K tokens
Larger context window than 39% of the other 198 models
How much text it can read at once. Bigger suits long documents.
Where o4-mini ranks
Test results
Aider Polyglot
225 coding exercises in six programming languages. The AI edits the code files and the exercise's tests decide pass or fail.
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.
79.6%
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.
81.7%
Place 84 of 174
Humanity's Last Exam
A large set of very hard, expert-written questions across many subjects, built to stay difficult for top AI models.
18.1%
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.
6.1%
SimpleBench
Everyday common-sense and trick questions that most people answer correctly but AI models often get wrong.
38.7%
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.
36.1%
SimpleQA Verified
Short factual questions that each have one correct answer. It measures how often a model gets facts right.
19.6%
What it costs in everyday terms
- 100 chats
- $0.33
- 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
- $0.11
- 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
- $1.93 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.
Similar models
Questions about o4-mini
- How much does o4-mini cost?
- o4-mini costs $1.10 per million input tokens and $4.40 per million output tokens, using the list price from OpenAI as of 26 Oct 2026. That is about $0.33 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 o4-mini?
- o4-mini has a context window of 200K tokens, roughly 150,000 words of text read at once. A single answer can be up to 100K tokens long.
- Is o4-mini open source?
- We list o4-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 o4-mini compared with other AI models?
- On the Epoch Capabilities Index, o4-mini scores 145.5 (likely range 142.9 to 147.2), which ranks 88 of 270 models we track. On Arena's human-vote text board it is ranked 108 of 166. Scores close together are a tie in practice.
- How does o4-mini compare with MiniMax-M2.7?
- MiniMax-M2.7 scores higher on 2 of 3 shared quality measures, o4-mini on 0. 1 measure is too close to call. MiniMax-M2.7 costs about 73% less than o4-mini on a blended price of $0.52 against $1.93 per million tokens. See the full comparison for every measure.
- How current are these numbers for o4-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