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o4 Mini High vs Relace Apply 3

Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace o4 Mini High Replace Relace Apply 3
o4 Mini HighOpenAI
Coding
No data
Overall
No data
Output $/M
$4.40
Relace Apply 3Relace
Coding
No data
Overall
No data
Output $/M
$1.25
vs $4.40 vs $1.25 per 1M output tokens. Relace Apply 3 is 3.5x cheaper.

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model Ao4 Mini HighOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BRelace Apply 3RelaceNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
0
o4 Mini High only
2
Relace Apply 3 only
0
Like-for-like categories
0 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
o4 Mini High not benchmarked, Relace Apply 3 not benchmarked.
Widest category
No category has a result for both models.
Widest single gap
No benchmark has a result for both models.
Output price
o4 Mini High $4.40 against Relace Apply 3 $1.25 per million output tokens, 3.5x apart.
Context window
o4 Mini High takes 200K tokens, Relace Apply 3 256K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

CodingDirectional onlySix of these boards feed the Vibe Coding Index1 board, none shared
Coding benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
ALE-Bench826.2Not measuredOnly o4 Mini High measured
Neither model has a result on the other 37 boards here
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Intelligence benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
Neither model has a result on 2 boards here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
GDPval25.3%Not measuredOnly o4 Mini High measured
Neither model has a result on the other 38 boards here
ReasoningNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Reasoning benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
Neither model has a result on 21 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
Neither model has a result on 13 boards here
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Knowledge benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
Neither model has a result on 17 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
Neither model has a result on 9 boards here
GeneralNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
General benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
Neither model has a result on 46 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for o4 Mini High and Relace Apply 3
Benchmarko4 Mini HighRelace Apply 3Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

o4 Mini High$0.0033Fits in one request
Relace Apply 3$0.0015Fits in one request

Relace Apply 3 costs less

Repository review

50K input + 3K output tokens

o4 Mini High$0.068Fits in one request
Relace Apply 3$0.046Fits in one request

Relace Apply 3 costs less

Agent loop

200K input + 10K output tokens

o4 Mini High$0.264Exceeds the context window
Relace Apply 3$0.182Fits in one request

Relace Apply 3 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of o4 Mini High and Relace Apply 3
SpecificationOpenAI o4 Mini HighRelace Apply 3
MakerOpenAIRelace
WeightsNo public weights listedNo public weights listed
ReleasedApril 16, 2025September 26, 2025
Context window200K256K
Input $/Mtok$1.10$0.85
Output $/Mtok$4.40$1.25
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is o4 Mini High better than Relace Apply 3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, o4 Mini High or Relace Apply 3?

o4 Mini High costs $1.10 per million input tokens and $4.40 per million output tokens; Relace Apply 3 costs $0.85 and $1.25. Cost per solved task is known for neither of them.

Which has the bigger context window, o4 Mini High or Relace Apply 3?

Relace Apply 3, with 256K tokens against 200K.

How many benchmarks is the o4 Mini High vs Relace Apply 3 comparison based on?

0 benchmarks have a result for both models as of October 21, 2026. o4 Mini High's coding index rests on 0 independent benchmarks and Relace Apply 3's on 0. Where only one model has a result, the page says so instead of naming a winner.

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