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GPT-4.1 Mini vs Qwen3.5-27B

Updated October 21, 2026. 48 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

GPT-4.1 MiniOpenAI
Coding
28.5
Overall
10.2
Output $/M
$1.60
1
Qwen3.5-27BQwen
Coding
22.6
Overall
22.9
Output $/M
$2.16
47
vs boards won of 48 shared

Decision reading

Pick GPT-4.1 Mini for coding: it scores 28.5 on the Vibe Coding Index against 22.6 for Qwen3.5-27B.

Pick Qwen3.5-27B when what matters is Terminal-Bench Hard (Artificial Analysis run) or WeirdML, where it leads.

Shared results
48
GPT-4.1 Mini only
36
Qwen3.5-27B only
5
Like-for-like categories
7 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
GPT-4.1 Mini 28.5 from 2 benchmarks, Qwen3.5-27B 22.6 from 1 benchmark.
Widest category
Agentic work, 40.9 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-4.1 Mini 52.9% against Qwen3.5-27B 93.9%, 40.9 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Mini $1.60 against Qwen3.5-27B $2.16 per million output tokens, 1.4x apart.
Context window
GPT-4.1 Mini takes 1.05M tokens, Qwen3.5-27B 262K.

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-4.1 MiniBarsQwen3.5-27BTies
Coding04
Intelligence01
Agentic work01
Reasoning07
Math02
Knowledge04
General128
All shared boards147
CodingLike-for-likeFour of these boards feed the Vibe Coding Index04
Coding benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
Aider polyglot32.4%Not measuredOnly GPT-4.1 Mini measured
SWE-bench Verified23.9%Not measuredOnly GPT-4.1 Mini measured
LMArena WebDevNot measured1358Only Qwen3.5-27B measured
AA Coding Index20.2Not measuredOnly GPT-4.1 Mini measured
LiveCodeBench (Vals AI)58.2%Not measuredOnly GPT-4.1 Mini measured
LiveCodeBench (Artificial Analysis run)48.3%Not measuredOnly GPT-4.1 Mini measured
Terminal-Bench Hard (Artificial Analysis run)7.6%32.6%Qwen3.5-27B
WeirdML37.6%39.5%Qwen3.5-27B
ALE-BenchNot measured349.4Only Qwen3.5-27B measured
LMArena Text: coding13671427Qwen3.5-27B
LMArena Text: software and IT13601431Qwen3.5-27B
LMArena WebDev: ReactNot measured1346Only Qwen3.5-27B measured
LMArena WebDev: HTMLNot measured1386Only Qwen3.5-27B measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
AA Intelligence Index10.222.9Qwen3.5-27B
Epoch Capabilities Index134.9Not measuredOnly GPT-4.1 Mini measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
τ²-Bench Telecom52.9%93.9%Qwen3.5-27B
Vending-Bench 2Not measured$202Only Qwen3.5-27B measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
GPQA Diamond67.9%Not measuredOnly GPT-4.1 Mini measured
MMMU Pro (Vals AI)70.5%Not measuredOnly GPT-4.1 Mini measured
GPQA Diamond (Artificial Analysis run)66.4%85.8%Qwen3.5-27B
Humanity's Last Exam (Artificial Analysis run)5.0%23.9%Qwen3.5-27B
GPQA Diamond (Epoch AI run)65.8%Not measuredOnly GPT-4.1 Mini measured
ARC-AGI3.5%Not measuredOnly GPT-4.1 Mini measured
ARC-AGI-20.0%Not measuredOnly GPT-4.1 Mini measured
Chess puzzles1.0%Not measuredOnly GPT-4.1 Mini measured
Mystery game puzzles7.0%Not measuredOnly GPT-4.1 Mini measured
LMArena Text: hard prompts13491415Qwen3.5-27B
LMArena Text: expert13381427Qwen3.5-27B
LMArena Text: hard prompts in English13621429Qwen3.5-27B
LMArena Vision: diagrams11821249Qwen3.5-27B
LMArena Vision: homework12141256Qwen3.5-27B
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
AIME49.4%Not measuredOnly GPT-4.1 Mini measured
MATH 500 (Vals AI)88.0%Not measuredOnly GPT-4.1 Mini measured
MGSM (Vals AI)87.8%Not measuredOnly GPT-4.1 Mini measured
AA Math Index46.3Not measuredOnly GPT-4.1 Mini measured
AIME 2025 (Artificial Analysis run)46.3%Not measuredOnly GPT-4.1 Mini measured
OTIS Mock AIME44.7%Not measuredOnly GPT-4.1 Mini measured
FrontierMath, tiers 1 to 36.7%Not measuredOnly GPT-4.1 Mini measured
MATH level 587.3%Not measuredOnly GPT-4.1 Mini measured
LMArena Text: math13431429Qwen3.5-27B
LMArena Text: mathematical work13471429Qwen3.5-27B
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
MMLU Pro77.2%Not measuredOnly GPT-4.1 Mini measured
LegalBench (Vals AI)78.0%Not measuredOnly GPT-4.1 Mini measured
CorpFin (Vals AI)57.9%Not measuredOnly GPT-4.1 Mini measured
TaxEval (Vals AI)71.9%Not measuredOnly GPT-4.1 Mini measured
MortgageTax (Vals AI)65.5%Not measuredOnly GPT-4.1 Mini measured
MedQA (Vals AI)84.6%Not measuredOnly GPT-4.1 Mini measured
MMLU Pro (Artificial Analysis run)78.1%Not measuredOnly GPT-4.1 Mini measured
SimpleQA Verified12.7%Not measuredOnly GPT-4.1 Mini measured
LMArena Text: science13281437Qwen3.5-27B
LMArena Text: medicine and healthcare13241425Qwen3.5-27B
LMArena Text: legal and government13431405Qwen3.5-27B
LMArena Text: business and finance13221399Qwen3.5-27B
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
Design Arena: websites997Not measuredOnly GPT-4.1 Mini measured
Design Arena: UI components961Not measuredOnly GPT-4.1 Mini measured
Design Arena: game dev1071Not measuredOnly GPT-4.1 Mini measured
Design Arena: data viz1034Not measuredOnly GPT-4.1 Mini measured
Design Arena: 3D837Not measuredOnly GPT-4.1 Mini measured
Design Arena: all code categories994Not measuredOnly GPT-4.1 Mini measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index128
General benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
IFBench38.3%75.6%Qwen3.5-27B
Long context reasoning (AA-LCR)44.0%77.7%Qwen3.5-27B
DTBench68.8%82.4%Qwen3.5-27B
LMCA21.1%34.0%Qwen3.5-27B
Fiction.LiveBench44.4%Not measuredOnly GPT-4.1 Mini measured
LMArena Text13411409Qwen3.5-27B
LMArena Text: instruction following13331393Qwen3.5-27B
LMArena Text: creative writing12991362Qwen3.5-27B
LMArena Vision11811241Qwen3.5-27B
LMArena Text: English13561425Qwen3.5-27B
LMArena Text: non-English13181390Qwen3.5-27B
LMArena Text: Chinese13291478Qwen3.5-27B
LMArena Text: German13501392Qwen3.5-27B
LMArena Text: Japanese12901346Qwen3.5-27B
LMArena Text: Korean12981359Qwen3.5-27B
LMArena Text: French13581410Qwen3.5-27B
LMArena Text: Spanish13191407Qwen3.5-27B
LMArena Text: Russian13241390Qwen3.5-27B
LMArena Text: Polish13261375Qwen3.5-27B
LMArena Text: multi-turn13541410Qwen3.5-27B
LMArena Text: longer queries13441413Qwen3.5-27B
LMArena Text: writing and language13191380Qwen3.5-27B
LMArena Text: entertainment and media13001363Qwen3.5-27B
LMArena Vision: English11911246Qwen3.5-27B
LMArena Vision: Chinese11861301Qwen3.5-27B
LMArena Vision: reading text11881246Qwen3.5-27B
LMArena Vision: humor11821227Qwen3.5-27B
LMArena Vision: captioning11741170GPT-4.1 Mini
LMArena Vision: recognizing things11871210Qwen3.5-27B
LMArena Vision: creative writing11821224Qwen3.5-27B
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 Mini and Qwen3.5-27B
BenchmarkGPT-4.1 MiniQwen3.5-27BLeader
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-4.1 Mini$0.0012Fits in one request
Qwen3.5-27B$0.0014Fits in one request

GPT-4.1 Mini costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Mini$0.025Fits in one request
Qwen3.5-27B$0.020Fits in one request

Qwen3.5-27B costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Mini$0.096Fits in one request
Qwen3.5-27B$0.076Fits in one request

Qwen3.5-27B 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-4.1 Mini and Qwen3.5-27B
SpecificationOpenAI GPT-4.1 MiniQwen3.5-27B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025February 25, 2026
Context window1.05M262K
Input $/Mtok$0.40$0.27
Output $/Mtok$1.60$2.16
Coding index28.522.6
Independent measurements behind it21
Cost per solved task$1.818Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Mini better than Qwen3.5-27B for coding?

Pick GPT-4.1 Mini for coding: it scores 28.5 on the Vibe Coding Index against 22.6 for Qwen3.5-27B. Pick Qwen3.5-27B when what matters is Terminal-Bench Hard (Artificial Analysis run) or WeirdML, where it leads.

Which is cheaper, GPT-4.1 Mini or Qwen3.5-27B?

GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; Qwen3.5-27B costs $0.27 and $2.16. Cost per solved task is known for GPT-4.1 Mini only.

Which has the bigger context window, GPT-4.1 Mini or Qwen3.5-27B?

GPT-4.1 Mini, with 1.05M tokens against 262K.

How many benchmarks is the GPT-4.1 Mini vs Qwen3.5-27B comparison based on?

48 benchmarks have a result for both models as of October 21, 2026. GPT-4.1 Mini's coding index rests on 2 independent benchmarks and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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