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GPT-4.1 vs Qwen3.5-35B-A3B

Qwen3.5-35B-A3B leads GPT-4.1 on the Artificial Analysis Intelligence Index, 19.3 to 12.7, and Qwen3.5-35B-A3B costs 6.2x less per output token ($1.30 vs $8.00 per million). Updated October 22, 2026; 41 benchmarks have a result for both.

Replace GPT-4.1 Replace Qwen3.5-35B-A3B
GPT-4.1OpenAI
Coding
No data
Overall
36.5
Output $/M
$8.00
9
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
32
vs boards won of 41 shared

GPT-4.1 or Qwen3.5-35B-A3B: which to pick

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

Pick GPT-4.1 for a larger context window (1.05M against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model AGPT-4.1OpenAINot benchmarkedNo coding benchmark$0.37 per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
41
GPT-4.1 only
51
Qwen3.5-35B-A3B only
4
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 not benchmarked, Qwen3.5-35B-A3B not benchmarked.
Widest category
Agentic work, 42.1 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-4.1 47.1% against Qwen3.5-35B-A3B 89.2%, 42.1 points apart on a 0 to 100 scale.
Output price
GPT-4.1 $8.00 against Qwen3.5-35B-A3B $1.30 per million output tokens, 6.2x apart.
Context window
GPT-4.1 takes 1.05M tokens, Qwen3.5-35B-A3B 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-4.1BarsQwen3.5-35B-A3BTies
Coding13
Intelligence02
Agentic work01
Reasoning06
Math03
Knowledge13
General714
All shared boards932
CodingLike-for-likeSix of these boards feed the Vibe Coding Index13
Coding benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
Aider polyglot52.4%Not measuredOnly GPT-4.1 measured
SWE-bench Verified39.6%Not measuredOnly GPT-4.1 measured
SWE-bench Multimodal31.1%Not measuredOnly GPT-4.1 measured
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
LiveCodeBench (Vals AI)54.7%Not measuredOnly GPT-4.1 measured
LiveCodeBench (Artificial Analysis run)45.7%Not measuredOnly GPT-4.1 measured
Terminal-Bench Hard (Artificial Analysis run)13.6%26.5%Qwen3.5-35B-A3B
WeirdML39.0%Not measuredOnly GPT-4.1 measured
ALE-Bench558.1221.8GPT-4.1
LMArena Text: coding13901410Qwen3.5-35B-A3B
LMArena Text: software and IT13911415Qwen3.5-35B-A3B
LMArena WebDev: ReactNot measured1238Only Qwen3.5-35B-A3B measured
LMArena WebDev: HTMLNot measured1301Only Qwen3.5-35B-A3B measured
SciCode4.6%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
AA Intelligence Index12.719.3Qwen3.5-35B-A3B
Epoch Capabilities Index136.7142.5Qwen3.5-35B-A3B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
τ²-Bench Telecom47.1%89.2%Qwen3.5-35B-A3B
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Berkeley Function Calling Leaderboard (BFCL)54.0%Not measuredOnly GPT-4.1 measured
BrowseComp-Plus36.4%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
GPQA Diamond65.4%Not measuredOnly GPT-4.1 measured
MMMU Pro (Vals AI)72.4%Not measuredOnly GPT-4.1 measured
GPQA Diamond (Artificial Analysis run)66.6%84.5%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)4.2%21.0%Qwen3.5-35B-A3B
GPQA Diamond (Epoch AI run)66.9%83.5%Qwen3.5-35B-A3B
ARC-AGI5.5%Not measuredOnly GPT-4.1 measured
ARC-AGI-20.4%Not measuredOnly GPT-4.1 measured
SimpleBench27.0%Not measuredOnly GPT-4.1 measured
Chess puzzles3.0%Not measuredOnly GPT-4.1 measured
LMArena Text: hard prompts13841400Qwen3.5-35B-A3B
LMArena Text: expert13641408Qwen3.5-35B-A3B
LMArena Text: hard prompts in English13931411Qwen3.5-35B-A3B
LMArena Vision: diagrams1215Not measuredOnly GPT-4.1 measured
LMArena Vision: homework1248Not measuredOnly GPT-4.1 measured
Kagi LLM Benchmark52.3%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
AIME39.6%Not measuredOnly GPT-4.1 measured
MATH 500 (Vals AI)87.2%Not measuredOnly GPT-4.1 measured
MGSM (Vals AI)87.7%Not measuredOnly GPT-4.1 measured
AA Math Index34.7Not measuredOnly GPT-4.1 measured
AIME 2025 (Artificial Analysis run)34.7%Not measuredOnly GPT-4.1 measured
OTIS Mock AIME38.3%70.0%Qwen3.5-35B-A3B
FrontierMath, tiers 1 to 36.0%Not measuredOnly GPT-4.1 measured
MATH level 583.0%Not measuredOnly GPT-4.1 measured
LMArena Text: math13691404Qwen3.5-35B-A3B
LMArena Text: mathematical work13601410Qwen3.5-35B-A3B
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
Knowledge benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
MMLU Pro80.5%Not measuredOnly GPT-4.1 measured
LegalBench (Vals AI)83.1%Not measuredOnly GPT-4.1 measured
CaseLaw (Vals AI)69.9%Not measuredOnly GPT-4.1 measured
CorpFin (Vals AI)63.0%Not measuredOnly GPT-4.1 measured
TaxEval (Vals AI)75.1%Not measuredOnly GPT-4.1 measured
MortgageTax (Vals AI)65.9%Not measuredOnly GPT-4.1 measured
MedQA (Vals AI)91.2%Not measuredOnly GPT-4.1 measured
MMLU Pro (Artificial Analysis run)80.6%Not measuredOnly GPT-4.1 measured
SimpleQA Verified31.1%Not measuredOnly GPT-4.1 measured
GeoBench72.0%Not measuredOnly GPT-4.1 measured
LMArena Text: science13821413Qwen3.5-35B-A3B
LMArena Text: medicine and healthcare13791421Qwen3.5-35B-A3B
LMArena Text: legal and government13991399GPT-4.1
LMArena Text: business and finance13691394Qwen3.5-35B-A3B
FACTS Benchmark Suite45.8%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
Design Arena: websites1038Not measuredOnly GPT-4.1 measured
Design Arena: UI components997Not measuredOnly GPT-4.1 measured
Design Arena: game dev1079Not measuredOnly GPT-4.1 measured
Design Arena: data viz1104Not measuredOnly GPT-4.1 measured
Design Arena: 3D849Not measuredOnly GPT-4.1 measured
Design Arena: all code categories1025Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index714
General benchmarks for GPT-4.1 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
IFBench43.0%72.5%Qwen3.5-35B-A3B
Long context reasoning (AA-LCR)68.3%72.0%Qwen3.5-35B-A3B
DTBench68.3%80.0%Qwen3.5-35B-A3B
LMCA25.6%29.5%Qwen3.5-35B-A3B
Fiction.LiveBench63.9%Not measuredOnly GPT-4.1 measured
LMArena Text13831395Qwen3.5-35B-A3B
LMArena Text: instruction following13671379Qwen3.5-35B-A3B
LMArena Text: creative writing13631347GPT-4.1
LMArena Vision1210Not measuredOnly GPT-4.1 measured
LMArena Text: English13921407Qwen3.5-35B-A3B
LMArena Text: non-English13701378Qwen3.5-35B-A3B
LMArena Text: Chinese13821457Qwen3.5-35B-A3B
LMArena Text: German13811367GPT-4.1
LMArena Text: Japanese13191326Qwen3.5-35B-A3B
LMArena Text: Korean13381355Qwen3.5-35B-A3B
LMArena Text: French13821412Qwen3.5-35B-A3B
LMArena Text: Spanish13761390Qwen3.5-35B-A3B
LMArena Text: Russian13771376GPT-4.1
LMArena Text: Polish13891385GPT-4.1
LMArena Text: multi-turn13971390GPT-4.1
LMArena Text: longer queries13851389Qwen3.5-35B-A3B
LMArena Text: writing and language13711365GPT-4.1
LMArena Text: entertainment and media13651347GPT-4.1
LMArena Vision: English1209Not measuredOnly GPT-4.1 measured
LMArena Vision: Chinese1226Not measuredOnly GPT-4.1 measured
LMArena Vision: reading text1218Not measuredOnly GPT-4.1 measured
LMArena Vision: humor1196Not measuredOnly GPT-4.1 measured
LMArena Vision: captioning1207Not measuredOnly GPT-4.1 measured
LMArena Vision: recognizing things1208Not measuredOnly GPT-4.1 measured
LMArena Vision: creative writing1210Not measuredOnly GPT-4.1 measured
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 and Qwen3.5-35B-A3B
BenchmarkGPT-4.1Qwen3.5-35B-A3BLeader
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$0.0060Fits in one request
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

GPT-4.1$0.124Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

GPT-4.1$0.480Fits in one request
Qwen3.5-35B-A3B$0.045Fits in one request

Qwen3.5-35B-A3B 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 and Qwen3.5-35B-A3B
SpecificationOpenAI GPT-4.1Qwen3.5-35B-A3B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025February 25, 2026
Context window1.05M262K
Input $/Mtok$2.00$0.1625
Output $/Mtok$8.00$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved task$0.37Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 better than Qwen3.5-35B-A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 for a larger context window (1.05M against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, GPT-4.1 or Qwen3.5-35B-A3B?

GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for GPT-4.1 only.

Which has the bigger context window, GPT-4.1 or Qwen3.5-35B-A3B?

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

How many benchmarks is the GPT-4.1 vs Qwen3.5-35B-A3B comparison based on?

41 benchmarks have a result for both models as of October 22, 2026. GPT-4.1's coding index rests on 0 independent benchmarks and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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