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GPT-5 Nano vs Qwen3.5-122B-A10B

Qwen3.5-122B-A10B leads GPT-5 Nano on the Artificial Analysis Intelligence Index, 17.7 to 13.0, and GPT-5 Nano costs 5.2x less per output token ($0.40 vs $2.08 per million). Updated October 22, 2026; 44 benchmarks have a result for both.

Replace GPT-5 Nano Replace Qwen3.5-122B-A10B
GPT-5 NanoOpenAI
Coding
No data
Overall
35.6
Output $/M
$0.40
0
Qwen3.5-122B-A10BQwen
Coding
No data
Overall
No data
Output $/M
$2.08
44
vs boards won of 44 shared

GPT-5 Nano or Qwen3.5-122B-A10B: 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 5.2x cheaper ($0.40 vs $2.08 per million) and a larger context window (400K against 262K tokens).

Model AGPT-5 NanoOpenAINot benchmarkedNo coding benchmark$0.109 per solved taskModel BQwen3.5-122B-A10BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
44
GPT-5 Nano only
44
Qwen3.5-122B-A10B only
7
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-5 Nano not benchmarked, Qwen3.5-122B-A10B not benchmarked.
Widest category
Agentic work, 57.0 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-5 Nano 36.5% against Qwen3.5-122B-A10B 93.6%, 57.0 points apart on a 0 to 100 scale.
Output price
GPT-5 Nano $0.40 against Qwen3.5-122B-A10B $2.08 per million output tokens, 5.2x apart.
Context window
GPT-5 Nano takes 400K tokens, Qwen3.5-122B-A10B 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 NanoBarsQwen3.5-122B-A10BTies
Coding03
Intelligence01
Agentic work01
Reasoning08
Math02
Knowledge04
General025
All shared boards044
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
SWE-bench Verified34.8%Not measuredOnly GPT-5 Nano measured
LMArena WebDevNot measured1361Only Qwen3.5-122B-A10B measured
AA Coding IndexNot measured43.3Only Qwen3.5-122B-A10B 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 measured39.7%Only Qwen3.5-122B-A10B measured
Terminal-Bench Hard (Artificial Analysis run)17.4%31.1%Qwen3.5-122B-A10B
Terminal-Bench21.8%Not measuredOnly GPT-5 Nano measured
WeirdML38.1%Not measuredOnly GPT-5 Nano measured
LMArena Text: coding13511436Qwen3.5-122B-A10B
LMArena Text: software and IT13451436Qwen3.5-122B-A10B
LMArena WebDev: ReactNot measured1353Only Qwen3.5-122B-A10B measured
LMArena WebDev: HTMLNot measured1351Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
AA Intelligence Index13.017.7Qwen3.5-122B-A10B
Epoch Capabilities Index139.2Not measuredOnly GPT-5 Nano measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
τ²-Bench Telecom36.5%93.6%Qwen3.5-122B-A10B
Berkeley Function Calling Leaderboard (BFCL)51.4%Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for GPT-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
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%85.7%Qwen3.5-122B-A10B
Humanity's Last Exam (Artificial Analysis run)9.5%25.2%Qwen3.5-122B-A10B
GPQA Diamond (Epoch AI run)69.4%Not measuredOnly GPT-5 Nano measured
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%17.0%Qwen3.5-122B-A10B
VPCT37.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: hard prompts13281421Qwen3.5-122B-A10B
LMArena Text: expert13211431Qwen3.5-122B-A10B
LMArena Text: hard prompts in English13381431Qwen3.5-122B-A10B
LMArena Vision: diagrams11411249Qwen3.5-122B-A10B
LMArena Vision: homework11571261Qwen3.5-122B-A10B
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 index02
Math benchmarks for GPT-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
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%Not measuredOnly GPT-5 Nano measured
FrontierMath, tiers 1 to 320.0%Not measuredOnly GPT-5 Nano measured
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: math13171431Qwen3.5-122B-A10B
LMArena Text: mathematical work13261431Qwen3.5-122B-A10B
MathArena12.8%Not measuredOnly GPT-5 Nano measured
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 Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
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: science13181432Qwen3.5-122B-A10B
LMArena Text: medicine and healthcare13351423Qwen3.5-122B-A10B
LMArena Text: legal and government12981422Qwen3.5-122B-A10B
LMArena Text: business and finance13111414Qwen3.5-122B-A10B
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GPT-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
Design Arena: websites1101Not measuredOnly GPT-5 Nano measured
Design Arena: UI components1064Not measuredOnly GPT-5 Nano measured
Design Arena: game dev1044Not measuredOnly GPT-5 Nano measured
Design Arena: data viz1056Not measuredOnly GPT-5 Nano measured
Design Arena: 3D965Not measuredOnly GPT-5 Nano measured
Design Arena: all code categories1084Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index025
General benchmarks for GPT-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
SAGE (Vals AI)30.4%Not measuredOnly GPT-5 Nano measured
MedScribe (Vals AI)72.9%Not measuredOnly GPT-5 Nano measured
IFBench67.6%75.7%Qwen3.5-122B-A10B
Long context reasoning (AA-LCR)45.0%76.3%Qwen3.5-122B-A10B
DTBench62.7%84.3%Qwen3.5-122B-A10B
LMCA7.9%32.2%Qwen3.5-122B-A10B
Fiction.LiveBench44.4%Not measuredOnly GPT-5 Nano measured
LMArena Text13201417Qwen3.5-122B-A10B
LMArena Text: instruction following13061399Qwen3.5-122B-A10B
LMArena Text: creative writing12491368Qwen3.5-122B-A10B
LMArena Vision11591244Qwen3.5-122B-A10B
LMArena Text: English13211428Qwen3.5-122B-A10B
LMArena Text: non-English13131401Qwen3.5-122B-A10B
LMArena Text: Chinese13561463Qwen3.5-122B-A10B
LMArena Text: German13271425Qwen3.5-122B-A10B
LMArena Text: Japanese12271367Qwen3.5-122B-A10B
LMArena Text: Korean12691353Qwen3.5-122B-A10B
LMArena Text: FrenchNot measured1443Only Qwen3.5-122B-A10B measured
LMArena Text: Spanish13601425Qwen3.5-122B-A10B
LMArena Text: Russian12961400Qwen3.5-122B-A10B
LMArena Text: Polish13141398Qwen3.5-122B-A10B
LMArena Text: multi-turn13111416Qwen3.5-122B-A10B
LMArena Text: longer queries13121410Qwen3.5-122B-A10B
LMArena Text: writing and language12831387Qwen3.5-122B-A10B
LMArena Text: entertainment and media12681366Qwen3.5-122B-A10B
LMArena Vision: English11701249Qwen3.5-122B-A10B
LMArena Vision: Chinese11761301Qwen3.5-122B-A10B
LMArena Vision: reading text11521251Qwen3.5-122B-A10B
LMArena Vision: humor11101243Qwen3.5-122B-A10B
LMArena Vision: creative writingNot measured1220Only Qwen3.5-122B-A10B measured
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-5 Nano and Qwen3.5-122B-A10B
BenchmarkGPT-5 NanoQwen3.5-122B-A10BLeader
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
Qwen3.5-122B-A10B$0.0013Fits in one request

GPT-5 Nano costs less

Repository review

50K input + 3K output tokens

GPT-5 Nano$0.0037Fits in one request
Qwen3.5-122B-A10B$0.019Fits in one request

GPT-5 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-5 Nano$0.014Fits in one request
Qwen3.5-122B-A10B$0.073Fits 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 Qwen3.5-122B-A10B
SpecificationOpenAI GPT-5 NanoQwen3.5-122B-A10B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 7, 2025February 25, 2026
Context window400K262K
Input $/Mtok$0.05$0.26
Output $/Mtok$0.40$2.08
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 Qwen3.5-122B-A10B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5 Nano for output tokens 5.2x cheaper ($0.40 vs $2.08 per million) and a larger context window (400K against 262K tokens).

Which is cheaper, GPT-5 Nano or Qwen3.5-122B-A10B?

GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for GPT-5 Nano only.

Which has the bigger context window, GPT-5 Nano or Qwen3.5-122B-A10B?

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

How many benchmarks is the GPT-5 Nano vs Qwen3.5-122B-A10B comparison based on?

44 benchmarks have a result for both models as of October 22, 2026. GPT-5 Nano's coding index rests on 0 independent benchmarks and Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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