Enter opens the highlighted result. Esc closes.

GPT-5 Nano vs Qwen3.5 397B A17B

Qwen3.5 397B A17B leads GPT-5 Nano on the Artificial Analysis Intelligence Index, 21.4 to 13.0, and GPT-5 Nano costs 5.8x less per output token ($0.40 vs $2.34 per million). Updated October 22, 2026; 55 benchmarks have a result for both.

Replace GPT-5 Nano Replace Qwen3.5 397B A17B
GPT-5 NanoOpenAI
Coding
No data
Overall
35.6
Output $/M
$0.40
0
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
55
vs boards won of 55 shared

GPT-5 Nano 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-5 Nano for output tokens 5.8x cheaper ($0.40 vs $2.34 per million) and a larger context window (400K against 262K tokens).

Model AGPT-5 NanoOpenAINot benchmarkedNo coding benchmark$0.109 per solved taskModel BQwen3.5 397B A17BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
55
GPT-5 Nano only
33
Qwen3.5 397B A17B only
11
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-5 Nano not benchmarked, Qwen3.5 397B A17B not benchmarked.
Widest category
Agentic work, 59.1 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-5 Nano 36.5% against Qwen3.5 397B A17B 95.6%, 59.1 points apart on a 0 to 100 scale.
Output price
GPT-5 Nano $0.40 against Qwen3.5 397B A17B $2.34 per million output tokens, 5.8x apart.
Context window
GPT-5 Nano takes 400K 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-5 NanoBarsQwen3.5 397B A17BTies
Coding03
Intelligence02
Agentic work01
Reasoning09
Math05
Knowledge04
Web design06
General025
All shared boards055
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
SWE-bench Verified34.8%Not measuredOnly GPT-5 Nano measured
LMArena WebDevNot measured1400Only Qwen3.5 397B A17B measured
LiveCodeBench (Vals AI)70.2%Not measuredOnly GPT-5 Nano measured
LiveCodeBench (Artificial Analysis run)78.9%Not measuredOnly GPT-5 Nano measured
SciCodeNot measured44.8%Only Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)17.4%40.9%Qwen3.5 397B A17B
Terminal-Bench21.8%Not measuredOnly GPT-5 Nano measured
WeirdML38.1%Not measuredOnly GPT-5 Nano measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: coding13511464Qwen3.5 397B A17B
LMArena Text: software and IT13451463Qwen3.5 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 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
AA Intelligence Index13.021.4Qwen3.5 397B A17B
Epoch Capabilities Index139.2146.8Qwen3.5 397B A17B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
τ²-Bench Telecom36.5%95.6%Qwen3.5 397B A17B
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
Berkeley Function Calling Leaderboard (BFCL)51.4%Not measuredOnly GPT-5 Nano 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-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
GPQA Diamond63.4%Not measuredOnly GPT-5 Nano measured
MMMU Pro (Vals AI)70.9%Not measuredOnly GPT-5 Nano measured
GPQA Diamond (Artificial Analysis run)67.6%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)9.5%29.0%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)69.4%86.4%Qwen3.5 397B A17B
ARC-AGI20.7%Not measuredOnly GPT-5 Nano measured
ARC-AGI-22.6%Not measuredOnly GPT-5 Nano measured
Chess puzzles22.0%Not measuredOnly GPT-5 Nano measured
Mystery game puzzles9.0%18.0%Qwen3.5 397B A17B
VPCT37.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: hard prompts13281448Qwen3.5 397B A17B
LMArena Text: expert13211462Qwen3.5 397B A17B
LMArena Text: hard prompts in English13381450Qwen3.5 397B A17B
LMArena Vision: diagrams11411277Qwen3.5 397B A17B
LMArena Vision: homework11571292Qwen3.5 397B A17B
Kagi LLM Benchmark62.2%Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index05
Math benchmarks for GPT-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
AIME81.2%Not measuredOnly GPT-5 Nano measured
MATH 500 (Vals AI)93.8%Not measuredOnly GPT-5 Nano measured
MGSM (Vals AI)89.3%Not measuredOnly GPT-5 Nano measured
AA Math Index83.7Not measuredOnly GPT-5 Nano measured
AIME 2025 (Artificial Analysis run)83.7%Not measuredOnly GPT-5 Nano measured
OTIS Mock AIME81.1%88.9%Qwen3.5 397B A17B
FrontierMath, tiers 1 to 320.0%31.2%Qwen3.5 397B A17B
FrontierMath, tier 42.4%Not measuredOnly GPT-5 Nano measured
ProofBench12.0%Not measuredOnly GPT-5 Nano measured
MATH level 595.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: math13171453Qwen3.5 397B A17B
LMArena Text: mathematical work13261454Qwen3.5 397B A17B
MathArena12.8%19.2%Qwen3.5 397B A17B
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
MMLU Pro76.1%Not measuredOnly GPT-5 Nano measured
LegalBench (Vals AI)50.1%Not measuredOnly GPT-5 Nano measured
CaseLaw (Vals AI)52.6%Not measuredOnly GPT-5 Nano measured
TaxEval (Vals AI)67.4%Not measuredOnly GPT-5 Nano measured
MortgageTax (Vals AI)53.6%Not measuredOnly GPT-5 Nano measured
MedQA (Vals AI)93.3%Not measuredOnly GPT-5 Nano measured
MedCode (Vals AI)30.4%Not measuredOnly GPT-5 Nano measured
MMLU Pro (Artificial Analysis run)78.0%Not measuredOnly GPT-5 Nano measured
SimpleQA Verified11.7%Not measuredOnly GPT-5 Nano measured
LMArena Text: science13181457Qwen3.5 397B A17B
LMArena Text: medicine and healthcare13351455Qwen3.5 397B A17B
LMArena Text: legal and government12981441Qwen3.5 397B A17B
LMArena Text: business and finance13111435Qwen3.5 397B A17B
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
Design Arena: websites11011190Qwen3.5 397B A17B
Design Arena: UI components10641161Qwen3.5 397B A17B
Design Arena: game dev10441140Qwen3.5 397B A17B
Design Arena: data viz10561175Qwen3.5 397B A17B
Design Arena: 3D9651160Qwen3.5 397B A17B
Design Arena: all code categories10841179Qwen3.5 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 index025
General benchmarks for GPT-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 397B A17BLeader
SAGE (Vals AI)30.4%Not measuredOnly GPT-5 Nano measured
MedScribe (Vals AI)72.9%Not measuredOnly GPT-5 Nano measured
IFBench67.6%78.8%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)45.0%77.3%Qwen3.5 397B A17B
DTBench62.7%87.5%Qwen3.5 397B A17B
LMCA7.9%37.9%Qwen3.5 397B A17B
Fiction.LiveBench44.4%Not measuredOnly GPT-5 Nano measured
LMArena Text13201437Qwen3.5 397B A17B
LMArena Text: instruction following13061424Qwen3.5 397B A17B
LMArena Text: creative writing12491402Qwen3.5 397B A17B
LMArena Vision11591262Qwen3.5 397B A17B
LMArena Text: English13211443Qwen3.5 397B A17B
LMArena Text: non-English13131430Qwen3.5 397B A17B
LMArena Text: Chinese13561498Qwen3.5 397B A17B
LMArena Text: German13271445Qwen3.5 397B A17B
LMArena Text: Japanese12271429Qwen3.5 397B A17B
LMArena Text: Korean12691384Qwen3.5 397B A17B
LMArena Text: FrenchNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: Spanish13601441Qwen3.5 397B A17B
LMArena Text: Russian12961430Qwen3.5 397B A17B
LMArena Text: Polish13141447Qwen3.5 397B A17B
LMArena Text: multi-turn13111446Qwen3.5 397B A17B
LMArena Text: longer queries13121441Qwen3.5 397B A17B
LMArena Text: writing and language12831415Qwen3.5 397B A17B
LMArena Text: entertainment and media12681399Qwen3.5 397B A17B
LMArena Vision: English11701268Qwen3.5 397B A17B
LMArena Vision: Chinese11761314Qwen3.5 397B A17B
LMArena Vision: reading text11521271Qwen3.5 397B A17B
LMArena Vision: humor11101262Qwen3.5 397B A17B
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writingNot measured1260Only Qwen3.5 397B A17B 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-5 Nano and Qwen3.5 397B A17B
BenchmarkGPT-5 NanoQwen3.5 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-5 Nano$0.0003Fits in one request
Qwen3.5 397B A17B$0.0016Fits in one request

GPT-5 Nano costs less

Repository review

50K input + 3K output tokens

GPT-5 Nano$0.0037Fits in one request
Qwen3.5 397B A17B$0.027Fits in one request

GPT-5 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-5 Nano$0.014Fits in one request
Qwen3.5 397B A17B$0.101Fits in one request

GPT-5 Nano 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-5 Nano and Qwen3.5 397B A17B
SpecificationOpenAI GPT-5 NanoQwen3.5 397B A17B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 7, 2025February 16, 2026
Context window400K262K
Input $/Mtok$0.05$0.39
Output $/Mtok$0.40$2.34
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved task$0.109Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5 Nano 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-5 Nano for output tokens 5.8x cheaper ($0.40 vs $2.34 per million) and a larger context window (400K against 262K tokens).

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

GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for GPT-5 Nano only.

Which has the bigger context window, GPT-5 Nano or Qwen3.5 397B A17B?

GPT-5 Nano, with 400K tokens against 262K.

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

55 benchmarks have a result for both models as of October 22, 2026. GPT-5 Nano'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.

Compare next