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GPT-4o-mini (2024-07-18) vs Qwen2.5 72B Instruct

Qwen2.5 72B Instruct costs 1.5x less per output token than GPT-4o-mini (2024-07-18) ($0.40 vs $0.60 per million). Updated October 22, 2026; 33 benchmarks have a result for both.

Replace GPT-4o-mini (2024-07-18) Replace Qwen2.5 72B Instruct
GPT-4o-mini (2024-07-18)OpenAI
Coding
No data
Overall
No data
Output $/M
$0.60
20
Qwen2.5 72B InstructQwen
Coding
No data
Overall
26.5
Output $/M
$0.40
13
vs boards won of 33 shared

GPT-4o-mini (2024-07-18) or Qwen2.5 72B Instruct: which to pick

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

Pick GPT-4o-mini (2024-07-18) for a larger context window (128K against 33K tokens) and work measured by WeirdML or LMArena Text: coding, where it leads.

Model AGPT-4o-mini (2024-07-18)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen2.5 72B InstructQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
33
GPT-4o-mini (2024-07-18) only
13
Qwen2.5 72B Instruct only
20
Like-for-like categories
6 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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
GPT-4o-mini (2024-07-18) not benchmarked, Qwen2.5 72B Instruct not benchmarked.
Widest category
Math, 4.3 points apart on average over 4 shared benchmarks.
Widest single gap
GPQA Diamond (Epoch AI run): GPT-4o-mini (2024-07-18) 37.7% against Qwen2.5 72B Instruct 49.1%, 11.4 points apart on a 0 to 100 scale.
Output price
GPT-4o-mini (2024-07-18) $0.60 against Qwen2.5 72B Instruct $0.40 per million output tokens, 1.5x apart.
Context window
GPT-4o-mini (2024-07-18) takes 128K tokens, Qwen2.5 72B Instruct 33K.

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.

Boards won, where both have a result
CategoryGPT-4o-mini (2024-07-18)BarsQwen2.5 72B InstructTies
Coding03
Agentic work10
Reasoning04
Math04
Knowledge41
General151
All shared boards2013
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
Aider polyglot3.6%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LiveCodeBench (Artificial Analysis run)Not measured27.6%Only Qwen2.5 72B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)Not measured4.5%Only Qwen2.5 72B Instruct measured
WeirdML11.8%16.0%Qwen2.5 72B Instruct
LMArena Text: coding12901292Qwen2.5 72B Instruct
LMArena Text: software and IT12911292Qwen2.5 72B Instruct
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
AA Intelligence IndexNot measured7.7Only Qwen2.5 72B Instruct measured
Epoch Capabilities IndexNot measured129.0Only Qwen2.5 72B Instruct measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
τ²-Bench TelecomNot measured34.5%Only Qwen2.5 72B Instruct measured
METR time horizonsNot measured35.8%Only Qwen2.5 72B Instruct measured
BALROG17.4%16.2%GPT-4o-mini (2024-07-18)
TheAgentCompanyNot measured5.7%Only Qwen2.5 72B Instruct measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
GPQA Diamond (Artificial Analysis run)Not measured49.1%Only Qwen2.5 72B Instruct measured
Humanity's Last Exam (Artificial Analysis run)Not measured3.6%Only Qwen2.5 72B Instruct measured
GPQA Diamond (Epoch AI run)37.7%49.1%Qwen2.5 72B Instruct
SimpleBench10.7%Not measuredOnly GPT-4o-mini (2024-07-18) measured
Chess puzzles3.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
Mystery game puzzles12.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
VPCT34.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
BIG-Bench HardNot measured79.8%Only Qwen2.5 72B Instruct measured
LMArena Text: hard prompts12671271Qwen2.5 72B Instruct
LMArena Text: expert12341245Qwen2.5 72B Instruct
LMArena Text: hard prompts in English12781279Qwen2.5 72B Instruct
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
AA Math IndexNot measured14.0Only Qwen2.5 72B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured14.0%Only Qwen2.5 72B Instruct measured
OTIS Mock AIME6.9%8.1%Qwen2.5 72B Instruct
FrontierMath, tiers 1 to 30.7%Not measuredOnly GPT-4o-mini (2024-07-18) measured
MATH level 552.6%63.2%Qwen2.5 72B Instruct
LMArena Text: math12671283Qwen2.5 72B Instruct
LMArena Text: mathematical work12711290Qwen2.5 72B Instruct
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
MMLU Pro (Artificial Analysis run)Not measured72.0%Only Qwen2.5 72B Instruct measured
SimpleQA Verified8.3%Not measuredOnly GPT-4o-mini (2024-07-18) measured
MMLU76.7%85.3%Qwen2.5 72B Instruct
GeoBench64.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
AI2 Reasoning ChallengeNot measured94.5%Only Qwen2.5 72B Instruct measured
LMArena Text: science12861275GPT-4o-mini (2024-07-18)
LMArena Text: medicine and healthcare12821258GPT-4o-mini (2024-07-18)
LMArena Text: legal and government13051288GPT-4o-mini (2024-07-18)
LMArena Text: business and finance12651253GPT-4o-mini (2024-07-18)
Neither model has a result on the other 11 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index151
General benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
IFBenchNot measured36.9%Only Qwen2.5 72B Instruct measured
DTBenchNot measured62.9%Only Qwen2.5 72B Instruct measured
LMCANot measured13.4%Only Qwen2.5 72B Instruct measured
Creative writing (Lech Mazur)67.2%Not measuredOnly GPT-4o-mini (2024-07-18) measured
HellaSwagNot measured84.8%Only Qwen2.5 72B Instruct measured
WinoGrandeNot measured82.3%Only Qwen2.5 72B Instruct measured
PIQANot measured82.6%Only Qwen2.5 72B Instruct measured
LMArena Text12861269GPT-4o-mini (2024-07-18)
LMArena Text: instruction following12581254GPT-4o-mini (2024-07-18)
LMArena Text: creative writing12681221GPT-4o-mini (2024-07-18)
LMArena Vision1066Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: English13011283GPT-4o-mini (2024-07-18)
LMArena Text: non-English12661252GPT-4o-mini (2024-07-18)
LMArena Text: Chinese12651273Qwen2.5 72B Instruct
LMArena Text: German12721234GPT-4o-mini (2024-07-18)
LMArena Text: Japanese12161180GPT-4o-mini (2024-07-18)
LMArena Text: Korean11951188GPT-4o-mini (2024-07-18)
LMArena Text: French12971280GPT-4o-mini (2024-07-18)
LMArena Text: Spanish12761255GPT-4o-mini (2024-07-18)
LMArena Text: Russian12751264GPT-4o-mini (2024-07-18)
LMArena Text: Polish1244Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: multi-turn12851272GPT-4o-mini (2024-07-18)
LMArena Text: longer queries12891281GPT-4o-mini (2024-07-18)
LMArena Text: writing and language12821247GPT-4o-mini (2024-07-18)
LMArena Text: entertainment and media12531211GPT-4o-mini (2024-07-18)
LMArena Vision: English1072Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Vision: Chinese1033Not measuredOnly GPT-4o-mini (2024-07-18) measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
BenchmarkGPT-4o-mini (2024-07-18)Qwen2.5 72B InstructLeader
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

GPT-4o-mini (2024-07-18)$0.0004Fits in one request
Qwen2.5 72B Instruct$0.0006Fits in one request

GPT-4o-mini (2024-07-18) costs less

Repository review

50K input + 3K output tokens

GPT-4o-mini (2024-07-18)$0.0093Fits in one request
Qwen2.5 72B Instruct$0.019Exceeds the context window

GPT-4o-mini (2024-07-18) costs less

Agent loop

200K input + 10K output tokens

GPT-4o-mini (2024-07-18)$0.036Exceeds the context window
Qwen2.5 72B Instruct$0.076Exceeds the context window

GPT-4o-mini (2024-07-18) 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 GPT-4o-mini (2024-07-18) and Qwen2.5 72B Instruct
SpecificationOpenAI GPT-4o-mini (2024-07-18)Qwen2.5 72B Instruct
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedJuly 18, 2024September 19, 2024
Context window128K33K
Input $/Mtok$0.15$0.36
Output $/Mtok$0.60$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o-mini (2024-07-18) better than Qwen2.5 72B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o-mini (2024-07-18) for a larger context window (128K against 33K tokens) and work measured by WeirdML or LMArena Text: coding, where it leads.

Which is cheaper, GPT-4o-mini (2024-07-18) or Qwen2.5 72B Instruct?

GPT-4o-mini (2024-07-18) costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen2.5 72B Instruct costs $0.36 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4o-mini (2024-07-18) or Qwen2.5 72B Instruct?

GPT-4o-mini (2024-07-18), with 128K tokens against 33K.

How many benchmarks is the GPT-4o-mini (2024-07-18) vs Qwen2.5 72B Instruct comparison based on?

33 benchmarks have a result for both models as of October 22, 2026. GPT-4o-mini (2024-07-18)'s coding index rests on 0 independent benchmarks and Qwen2.5 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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