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GPT-4.1 Mini vs Qwen3.5 397B A17B

Qwen3.5 397B A17B leads GPT-4.1 Mini on the Artificial Analysis Intelligence Index, 21.4 to 10.2, and GPT-4.1 Mini costs 1.5x less per output token ($1.60 vs $2.34 per million). Updated October 22, 2026; 58 benchmarks have a result for both.

GPT-4.1 MiniOpenAI
Coding
No data
Overall
31.9
Output $/M
$1.60
0
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
58
vs boards won of 58 shared

GPT-4.1 Mini or Qwen3.5 397B A17B: which to pick

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

Pick GPT-4.1 Mini for output tokens 1.5x cheaper ($1.60 vs $2.34 per million) and a larger context window (1.05M against 262K tokens).

Shared results
58
GPT-4.1 Mini only
30
Qwen3.5 397B A17B only
8
Like-for-like categories
8 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-4.1 Mini not benchmarked, Qwen3.5 397B A17B not benchmarked.
Widest category
Agentic work, 42.7 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: GPT-4.1 Mini 44.7% against Qwen3.5 397B A17B 88.9%, 44.2 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Mini $1.60 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.5x apart.
Context window
GPT-4.1 Mini takes 1.05M tokens, Qwen3.5 397B A17B 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 397B A17BTies
Coding03
Intelligence02
Agentic work01
Reasoning09
Math04
Knowledge04
Web design06
General029
All shared boards058
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4.1 Mini and Qwen3.5 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
Aider polyglot32.4%Not measuredOnly GPT-4.1 Mini measured
SWE-bench Verified23.9%Not measuredOnly GPT-4.1 Mini measured
LMArena WebDevNot measured1400Only Qwen3.5 397B A17B 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
SciCodeNot measured44.8%Only Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)7.6%40.9%Qwen3.5 397B A17B
WeirdML37.6%Not measuredOnly GPT-4.1 Mini measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: coding13671464Qwen3.5 397B A17B
LMArena Text: software and IT13601463Qwen3.5 397B A17B
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTMLNot measured1410Only Qwen3.5 397B A17B measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4.1 Mini and Qwen3.5 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
AA Intelligence Index10.221.4Qwen3.5 397B A17B
Epoch Capabilities Index134.9146.8Qwen3.5 397B A17B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4.1 Mini and Qwen3.5 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
τ²-Bench Telecom52.9%95.6%Qwen3.5 397B A17B
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
Berkeley Function Calling Leaderboard (BFCL)50.4%Not measuredOnly GPT-4.1 Mini measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for GPT-4.1 Mini and Qwen3.5 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
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%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)5.0%29.0%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)65.8%86.4%Qwen3.5 397B A17B
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%18.0%Qwen3.5 397B A17B
LMArena Text: hard prompts13491448Qwen3.5 397B A17B
LMArena Text: expert13381462Qwen3.5 397B A17B
LMArena Text: hard prompts in English13621450Qwen3.5 397B A17B
LMArena Vision: diagrams11821277Qwen3.5 397B A17B
LMArena Vision: homework12141292Qwen3.5 397B A17B
Kagi LLM Benchmark48.6%Not measuredOnly GPT-4.1 Mini measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GPT-4.1 Mini and Qwen3.5 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
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%88.9%Qwen3.5 397B A17B
FrontierMath, tiers 1 to 36.7%31.2%Qwen3.5 397B A17B
MATH level 587.3%Not measuredOnly GPT-4.1 Mini measured
LMArena Text: math13431453Qwen3.5 397B A17B
LMArena Text: mathematical work13471454Qwen3.5 397B A17B
MathArenaNot measured19.2%Only Qwen3.5 397B A17B measured
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 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
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: science13281457Qwen3.5 397B A17B
LMArena Text: medicine and healthcare13241455Qwen3.5 397B A17B
LMArena Text: legal and government13431441Qwen3.5 397B A17B
LMArena Text: business and finance13221435Qwen3.5 397B A17B
PRBench Finance30.4%Not measuredOnly GPT-4.1 Mini measured
PRBench Legal30.4%Not measuredOnly GPT-4.1 Mini measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-4.1 Mini and Qwen3.5 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
Design Arena: websites9971190Qwen3.5 397B A17B
Design Arena: UI components9591161Qwen3.5 397B A17B
Design Arena: game dev10701140Qwen3.5 397B A17B
Design Arena: data viz10341175Qwen3.5 397B A17B
Design Arena: 3D8361160Qwen3.5 397B A17B
Design Arena: all code categories9931179Qwen3.5 397B A17B
Design Arena: SVGNot measured1139Only Qwen3.5 397B A17B measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index029
General benchmarks for GPT-4.1 Mini and Qwen3.5 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
IFBench38.3%78.8%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)44.0%77.3%Qwen3.5 397B A17B
DTBench68.8%87.5%Qwen3.5 397B A17B
LMCA21.1%37.9%Qwen3.5 397B A17B
Fiction.LiveBench44.4%Not measuredOnly GPT-4.1 Mini measured
LMArena Text13411437Qwen3.5 397B A17B
LMArena Text: instruction following13331424Qwen3.5 397B A17B
LMArena Text: creative writing12991402Qwen3.5 397B A17B
LMArena Vision11811262Qwen3.5 397B A17B
LMArena Text: English13561443Qwen3.5 397B A17B
LMArena Text: non-English13181430Qwen3.5 397B A17B
LMArena Text: Chinese13291498Qwen3.5 397B A17B
LMArena Text: German13501445Qwen3.5 397B A17B
LMArena Text: Japanese12901429Qwen3.5 397B A17B
LMArena Text: Korean12981384Qwen3.5 397B A17B
LMArena Text: French13581462Qwen3.5 397B A17B
LMArena Text: Spanish13191441Qwen3.5 397B A17B
LMArena Text: Russian13241430Qwen3.5 397B A17B
LMArena Text: Polish13261447Qwen3.5 397B A17B
LMArena Text: multi-turn13541446Qwen3.5 397B A17B
LMArena Text: longer queries13441441Qwen3.5 397B A17B
LMArena Text: writing and language13191415Qwen3.5 397B A17B
LMArena Text: entertainment and media13001399Qwen3.5 397B A17B
LMArena Vision: English11911268Qwen3.5 397B A17B
LMArena Vision: Chinese11861314Qwen3.5 397B A17B
LMArena Vision: reading text11881271Qwen3.5 397B A17B
LMArena Vision: humor11821262Qwen3.5 397B A17B
LMArena Vision: captioning11741230Qwen3.5 397B A17B
LMArena Vision: recognizing things11871265Qwen3.5 397B A17B
LMArena Vision: creative writing11821260Qwen3.5 397B A17B
Neither model has a result on the other 18 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 397B A17B
BenchmarkGPT-4.1 MiniQwen3.5 397B A17BLeader
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 397B A17B$0.0016Fits 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 397B A17B$0.027Fits in one request

GPT-4.1 Mini costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Mini$0.096Fits in one request
Qwen3.5 397B A17B$0.101Fits in one request

GPT-4.1 Mini 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 397B A17B
SpecificationOpenAI GPT-4.1 MiniQwen3.5 397B A17B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025February 16, 2026
Context window1.05M262K
Input $/Mtok$0.40$0.39
Output $/Mtok$1.60$2.34
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved task$1.818Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Mini better than Qwen3.5 397B A17B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 Mini for output tokens 1.5x cheaper ($1.60 vs $2.34 per million) and a larger context window (1.05M against 262K tokens).

Which is cheaper, GPT-4.1 Mini or Qwen3.5 397B A17B?

GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. 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 397B A17B?

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

How many benchmarks is the GPT-4.1 Mini vs Qwen3.5 397B A17B comparison based on?

58 benchmarks have a result for both models as of October 22, 2026. GPT-4.1 Mini's coding index rests on 0 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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