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GPT-4.1 Mini vs Qwen3 VL 235B A22B Instruct

GPT-4.1 Mini leads Qwen3 VL 235B A22B Instruct on the Artificial Analysis Intelligence Index, 10.2 to 9.9, at about the same output price ($1.60 vs $1.90 per million). Updated October 22, 2026; 49 benchmarks have a result for both.

Replace GPT-4.1 Mini Replace Qwen3 VL 235B A22B Instruct
GPT-4.1 MiniOpenAI
Coding
No data
Overall
31.9
Output $/M
$1.60
1
Qwen3 VL 235B A22B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.90
48
vs boards won of 49 shared

GPT-4.1 Mini or Qwen3 VL 235B A22B Instruct: 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 1.2x cheaper ($1.60 vs $1.90 per million) and a larger context window (1.05M against 262K tokens).

Model AGPT-4.1 MiniOpenAINot benchmarkedNo coding benchmark$1.818 per solved taskModel BQwen3 VL 235B A22B InstructQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
49
GPT-4.1 Mini only
37
Qwen3 VL 235B A22B Instruct only
0
Like-for-like categories
7 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 VL 235B A22B Instruct not benchmarked.
Widest category
Math, 27.5 points apart on average over 4 shared benchmarks.
Widest single gap
AA Math Index: GPT-4.1 Mini 46.3 against Qwen3 VL 235B A22B Instruct 88.3, 42.0 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Mini $1.60 against Qwen3 VL 235B A22B Instruct $1.90 per million output tokens, 1.2x apart.
Context window
GPT-4.1 Mini takes 1.05M tokens, Qwen3 VL 235B A22B Instruct 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 VL 235B A22B InstructTies
Coding04
Intelligence10
Agentic work01
Reasoning07
Math04
Knowledge05
General027
All shared boards148
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GPT-4.1 Mini and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
Aider polyglot32.4%Not measuredOnly GPT-4.1 Mini measured
SWE-bench Verified23.9%Not measuredOnly GPT-4.1 Mini 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%64.6%Qwen3 VL 235B A22B Instruct
Terminal-Bench Hard (Artificial Analysis run)7.6%11.4%Qwen3 VL 235B A22B Instruct
WeirdML37.6%Not measuredOnly GPT-4.1 Mini measured
LMArena Text: coding13671438Qwen3 VL 235B A22B Instruct
LMArena Text: software and IT13601442Qwen3 VL 235B A22B Instruct
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GPT-4.1 Mini and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
AA Intelligence Index10.29.9GPT-4.1 Mini
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 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
τ²-Bench Telecom52.9%54.1%Qwen3 VL 235B A22B Instruct
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 index07
Reasoning benchmarks for GPT-4.1 Mini and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
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%77.2%Qwen3 VL 235B A22B Instruct
Humanity's Last Exam (Artificial Analysis run)5.0%11.9%Qwen3 VL 235B A22B Instruct
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 prompts13491428Qwen3 VL 235B A22B Instruct
LMArena Text: expert13381442Qwen3 VL 235B A22B Instruct
LMArena Text: hard prompts in English13621439Qwen3 VL 235B A22B Instruct
LMArena Vision: diagrams11821255Qwen3 VL 235B A22B Instruct
LMArena Vision: homework12141277Qwen3 VL 235B A22B Instruct
Kagi LLM Benchmark48.6%Not measuredOnly GPT-4.1 Mini measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GPT-4.1 Mini and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
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 Index46.388.3Qwen3 VL 235B A22B Instruct
AIME 2025 (Artificial Analysis run)46.3%88.3%Qwen3 VL 235B A22B Instruct
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: math13431425Qwen3 VL 235B A22B Instruct
LMArena Text: mathematical work13471419Qwen3 VL 235B A22B Instruct
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GPT-4.1 Mini and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
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%83.6%Qwen3 VL 235B A22B Instruct
SimpleQA Verified12.7%Not measuredOnly GPT-4.1 Mini measured
LMArena Text: science13281444Qwen3 VL 235B A22B Instruct
LMArena Text: medicine and healthcare13241431Qwen3 VL 235B A22B Instruct
LMArena Text: legal and government13431438Qwen3 VL 235B A22B Instruct
LMArena Text: business and finance13221433Qwen3 VL 235B A22B Instruct
Neither model has a result on the other 6 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 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
Design Arena: websites997Not measuredOnly GPT-4.1 Mini measured
Design Arena: UI components958Not measuredOnly GPT-4.1 Mini measured
Design Arena: game dev1070Not measuredOnly GPT-4.1 Mini measured
Design Arena: data viz1034Not measuredOnly GPT-4.1 Mini measured
Design Arena: 3D836Not measuredOnly GPT-4.1 Mini measured
Design Arena: all code categories993Not 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 index027
General benchmarks for GPT-4.1 Mini and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B InstructLeader
IFBench38.3%56.5%Qwen3 VL 235B A22B Instruct
Long context reasoning (AA-LCR)44.0%63.7%Qwen3 VL 235B A22B Instruct
DTBench68.8%Not measuredOnly GPT-4.1 Mini measured
LMCA21.1%Not measuredOnly GPT-4.1 Mini measured
Fiction.LiveBench44.4%Not measuredOnly GPT-4.1 Mini measured
LMArena Text13411420Qwen3 VL 235B A22B Instruct
LMArena Text: instruction following13331406Qwen3 VL 235B A22B Instruct
LMArena Text: creative writing12991366Qwen3 VL 235B A22B Instruct
LMArena Vision11811247Qwen3 VL 235B A22B Instruct
LMArena Text: English13561429Qwen3 VL 235B A22B Instruct
LMArena Text: non-English13181405Qwen3 VL 235B A22B Instruct
LMArena Text: Chinese13291463Qwen3 VL 235B A22B Instruct
LMArena Text: German13501424Qwen3 VL 235B A22B Instruct
LMArena Text: Japanese12901385Qwen3 VL 235B A22B Instruct
LMArena Text: Korean12981394Qwen3 VL 235B A22B Instruct
LMArena Text: French13581452Qwen3 VL 235B A22B Instruct
LMArena Text: Spanish13191428Qwen3 VL 235B A22B Instruct
LMArena Text: Russian13241408Qwen3 VL 235B A22B Instruct
LMArena Text: Polish13261419Qwen3 VL 235B A22B Instruct
LMArena Text: multi-turn13541428Qwen3 VL 235B A22B Instruct
LMArena Text: longer queries13441419Qwen3 VL 235B A22B Instruct
LMArena Text: writing and language13191392Qwen3 VL 235B A22B Instruct
LMArena Text: entertainment and media13001368Qwen3 VL 235B A22B Instruct
LMArena Vision: English11911256Qwen3 VL 235B A22B Instruct
LMArena Vision: Chinese11861283Qwen3 VL 235B A22B Instruct
LMArena Vision: reading text11881253Qwen3 VL 235B A22B Instruct
LMArena Vision: humor11821209Qwen3 VL 235B A22B Instruct
LMArena Vision: captioning11741281Qwen3 VL 235B A22B Instruct
LMArena Vision: recognizing things11871249Qwen3 VL 235B A22B Instruct
LMArena Vision: creative writing11821220Qwen3 VL 235B A22B Instruct
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 VL 235B A22B Instruct
BenchmarkGPT-4.1 MiniQwen3 VL 235B A22B 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-4.1 Mini$0.0012Fits in one request
Qwen3 VL 235B A22B Instruct$0.0012Fits in one request

Qwen3 VL 235B A22B Instruct costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Mini$0.025Fits in one request
Qwen3 VL 235B A22B Instruct$0.016Fits in one request

Qwen3 VL 235B A22B Instruct costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Mini$0.096Fits in one request
Qwen3 VL 235B A22B Instruct$0.061Fits in one request

Qwen3 VL 235B A22B Instruct 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 VL 235B A22B Instruct
SpecificationOpenAI GPT-4.1 MiniQwen3 VL 235B A22B Instruct
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025September 23, 2025
Context window1.05M262K
Input $/Mtok$0.40$0.21
Output $/Mtok$1.60$1.90
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved task$1.818Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Mini better than Qwen3 VL 235B A22B Instruct 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 1.2x cheaper ($1.60 vs $1.90 per million) and a larger context window (1.05M against 262K tokens).

Which is cheaper, GPT-4.1 Mini or Qwen3 VL 235B A22B Instruct?

GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; Qwen3 VL 235B A22B Instruct costs $0.21 and $1.90. Cost per solved task is known for GPT-4.1 Mini only.

Which has the bigger context window, GPT-4.1 Mini or Qwen3 VL 235B A22B Instruct?

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

How many benchmarks is the GPT-4.1 Mini vs Qwen3 VL 235B A22B Instruct comparison based on?

49 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 VL 235B A22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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