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Qwen3.5-122B-A10B vs Qwen3.8 Max (0902)

Updated October 21, 2026. 48 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Qwen3.5-122B-A10BQwen
Coding
22.9
Overall
17.7
Output $/M
$2.08
0
Qwen3.8 Max (0902)Qwen
Coding
63.5
Overall
45.4
Output $/M
$6.00
48
vs boards won of 48 shared

Decision reading

Pick Qwen3.8 Max (0902) for coding: it scores 63.5 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B.

Pick Qwen3.5-122B-A10B when output tokens cost 2.9x less.

Shared results
48
Qwen3.5-122B-A10B only
3
Qwen3.8 Max (0902) only
65
Like-for-like categories
6 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
Qwen3.5-122B-A10B 22.9 from 1 benchmark, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
Widest category
Coding, 27.9 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: Qwen3.5-122B-A10B 1361 against Qwen3.8 Max (0902) 1674, 44.8 points apart on a 0 to 100 scale.
Output price
Qwen3.5-122B-A10B $2.08 against Qwen3.8 Max (0902) $6.00 per million output tokens, 2.9x apart.
Context window
Qwen3.5-122B-A10B takes 262K tokens, Qwen3.8 Max (0902) 1M.

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
CategoryQwen3.5-122B-A10BBarsQwen3.8 Max (0902)Ties
Coding07
Intelligence01
Reasoning08
Math02
Knowledge04
General026
All shared boards048
CodingLike-for-likeFour of these boards feed the Vibe Coding Index07
Coding benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
LiveBench codingNot measured60.3%Only Qwen3.8 Max (0902) measured
LMArena WebDev13611674Qwen3.8 Max (0902)
AA Coding Index43.376.2Qwen3.8 Max (0902)
LiveCodeBench (Vals AI)Not measured87.8%Only Qwen3.8 Max (0902) measured
SWE-bench Verified (Vals AI)Not measured85.6%Only Qwen3.8 Max (0902) measured
Terminal-Bench 4 (Vals AI)Not measured34.3%Only Qwen3.8 Max (0902) measured
Vibe Code Bench (Vals AI)Not measured64.7%Only Qwen3.8 Max (0902) measured
Code migration (Vals AI)Not measured24.0%Only Qwen3.8 Max (0902) measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 Max (0902) measured
IOI (Vals AI)Not measured68.9%Only Qwen3.8 Max (0902) measured
Terminal-Bench 2.1 (Vals AI)Not measured67.4%Only Qwen3.8 Max (0902) measured
SWE-bench Multimodal (Vals AI)Not measured42.5%Only Qwen3.8 Max (0902) measured
Vibe Code Bench 1-100 (Vals AI)Not measured12.8%Only Qwen3.8 Max (0902) measured
SkillsBench (Vals AI)Not measured42.0%Only Qwen3.8 Max (0902) measured
CyberBench (Vals AI)Not measured28.6%Only Qwen3.8 Max (0902) measured
SciCode39.7%53.2%Qwen3.8 Max (0902)
Terminal-Bench Hard (Artificial Analysis run)31.1%Not measuredOnly Qwen3.5-122B-A10B measured
FrontierSWENot measured17.8%Only Qwen3.8 Max (0902) measured
LMArena Text: coding14361502Qwen3.8 Max (0902)
LMArena Text: software and IT14361498Qwen3.8 Max (0902)
LMArena WebDev: React13531692Qwen3.8 Max (0902)
LMArena WebDev: HTML13511649Qwen3.8 Max (0902)
LMArena WebDev: from an imageNot measured1637Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
AA Intelligence Index17.745.4Qwen3.8 Max (0902)
Epoch Capabilities IndexNot measured157.4Only Qwen3.8 Max (0902) measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
Agentic work benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
AA Agentic IndexNot measured56.0Only Qwen3.8 Max (0902) measured
Design Arena: agents building web appsNot measured1301Only Qwen3.8 Max (0902) measured
Design Arena: agents building full-stack appsNot measured1305Only Qwen3.8 Max (0902) measured
Design Arena: agents building mobile appsNot measured1223Only Qwen3.8 Max (0902) measured
Design Arena: agents building Android appsNot measured1207Only Qwen3.8 Max (0902) measured
Design Arena: agents building Godot gamesNot measured1234Only Qwen3.8 Max (0902) measured
Design Arena: PowerPoint slidesNot measured1257Only Qwen3.8 Max (0902) measured
Design Arena: spreadsheetsNot measured868Only Qwen3.8 Max (0902) measured
LiveBench researchNot measured69.9%Only Qwen3.8 Max (0902) measured
LiveBench browserNot measured32.0%Only Qwen3.8 Max (0902) measured
LiveBench long agenticNot measured42.3%Only Qwen3.8 Max (0902) measured
Finance Agent (Vals AI)Not measured50.6%Only Qwen3.8 Max (0902) measured
Tax Agent Bench (Vals AI)Not measured32.1%Only Qwen3.8 Max (0902) measured
Legal Research Bench (Vals AI)Not measured47.6%Only Qwen3.8 Max (0902) measured
Excel Modeling Benchmark (Vals AI)Not measured60.1%Only Qwen3.8 Max (0902) measured
Terminal-Bench-Science (Vals AI)Not measured12.9%Only Qwen3.8 Max (0902) measured
τ²-Bench Telecom93.6%Not measuredOnly Qwen3.5-122B-A10B measured
APEX-AgentsNot measured63.3%Only Qwen3.8 Max (0902) measured
LMArena SearchNot measured1261Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
GPQA DiamondNot measured93.7%Only Qwen3.8 Max (0902) measured
LiveBench reasoningNot measured88.2%Only Qwen3.8 Max (0902) measured
MysteryMechanism (Vals AI)Not measured23.9%Only Qwen3.8 Max (0902) measured
MMMU Pro (Vals AI)Not measured88.0%Only Qwen3.8 Max (0902) measured
GPQA Diamond (Artificial Analysis run)85.7%92.8%Qwen3.8 Max (0902)
Humanity's Last Exam (Artificial Analysis run)25.2%43.1%Qwen3.8 Max (0902)
GPQA Diamond (Epoch AI run)Not measured92.7%Only Qwen3.8 Max (0902) measured
Chess puzzlesNot measured46.0%Only Qwen3.8 Max (0902) measured
Mystery game puzzles17.0%38.0%Qwen3.8 Max (0902)
LMArena Text: hard prompts14211496Qwen3.8 Max (0902)
LMArena Text: expert14311507Qwen3.8 Max (0902)
LMArena Text: hard prompts in English14311503Qwen3.8 Max (0902)
LMArena Vision: diagrams12491323Qwen3.8 Max (0902)
LMArena Vision: homework12611336Qwen3.8 Max (0902)
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 Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
OTIS Mock AIMENot measured100.0%Only Qwen3.8 Max (0902) measured
FrontierMath, tiers 1 to 3Not measured74.7%Only Qwen3.8 Max (0902) measured
FrontierMath, tier 4Not measured46.3%Only Qwen3.8 Max (0902) measured
ProofBenchNot measured58.0%Only Qwen3.8 Max (0902) measured
LMArena Text: math14311501Qwen3.8 Max (0902)
LMArena Text: mathematical work14311491Qwen3.8 Max (0902)
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
MMLU ProNot measured88.6%Only Qwen3.8 Max (0902) measured
LegalBench (Vals AI)Not measured83.6%Only Qwen3.8 Max (0902) measured
CorpFin (Vals AI)Not measured65.8%Only Qwen3.8 Max (0902) measured
TaxEval (Vals AI)Not measured75.5%Only Qwen3.8 Max (0902) measured
MortgageTax (Vals AI)Not measured64.0%Only Qwen3.8 Max (0902) measured
MedCode (Vals AI)Not measured40.7%Only Qwen3.8 Max (0902) measured
SimpleQA VerifiedNot measured47.3%Only Qwen3.8 Max (0902) measured
LMArena Text: science14321512Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare14231503Qwen3.8 Max (0902)
LMArena Text: legal and government14221492Qwen3.8 Max (0902)
LMArena Text: business and finance14141480Qwen3.8 Max (0902)
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
Design Arena: websitesNot measured1275Only Qwen3.8 Max (0902) measured
Design Arena: UI componentsNot measured1340Only Qwen3.8 Max (0902) measured
Design Arena: game devNot measured1313Only Qwen3.8 Max (0902) measured
Design Arena: data vizNot measured1281Only Qwen3.8 Max (0902) measured
Design Arena: 3DNot measured1337Only Qwen3.8 Max (0902) measured
Design Arena: all code categoriesNot measured1293Only Qwen3.8 Max (0902) measured
Design Arena: ASCII artNot measured1201Only Qwen3.8 Max (0902) measured
LiveBench designNot measured78.6%Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index026
General benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
LiveBench data analysisNot measured78.4%Only Qwen3.8 Max (0902) measured
Public Benefits Bench (Vals AI)Not measured67.1%Only Qwen3.8 Max (0902) measured
SAGE (Vals AI)Not measured51.2%Only Qwen3.8 Max (0902) measured
MedScribe (Vals AI)Not measured85.0%Only Qwen3.8 Max (0902) measured
Vals Multimodal IndexNot measured65.4%Only Qwen3.8 Max (0902) measured
IFBench75.7%Not measuredOnly Qwen3.5-122B-A10B measured
Long context reasoning (AA-LCR)76.3%80.3%Qwen3.8 Max (0902)
DTBench84.3%92.0%Qwen3.8 Max (0902)
LMCA32.2%46.2%Qwen3.8 Max (0902)
Furniture assemblyNot measured20.0%Only Qwen3.8 Max (0902) measured
LMArena Text14171483Qwen3.8 Max (0902)
LMArena Text: instruction following13991481Qwen3.8 Max (0902)
LMArena Text: creative writing13681477Qwen3.8 Max (0902)
LMArena Vision12441313Qwen3.8 Max (0902)
LMArena Text: English14281491Qwen3.8 Max (0902)
LMArena Text: non-English14011473Qwen3.8 Max (0902)
LMArena Text: Chinese14631539Qwen3.8 Max (0902)
LMArena Text: German14251478Qwen3.8 Max (0902)
LMArena Text: Japanese13671473Qwen3.8 Max (0902)
LMArena Text: Korean13531460Qwen3.8 Max (0902)
LMArena Text: French14431498Qwen3.8 Max (0902)
LMArena Text: Spanish14251489Qwen3.8 Max (0902)
LMArena Text: Russian14001482Qwen3.8 Max (0902)
LMArena Text: Polish13981471Qwen3.8 Max (0902)
LMArena Text: multi-turn14161489Qwen3.8 Max (0902)
LMArena Text: longer queries14101488Qwen3.8 Max (0902)
LMArena Text: writing and language13871477Qwen3.8 Max (0902)
LMArena Text: entertainment and media13661464Qwen3.8 Max (0902)
LMArena Vision: English12491311Qwen3.8 Max (0902)
LMArena Vision: Chinese13011358Qwen3.8 Max (0902)
LMArena Vision: reading text12511322Qwen3.8 Max (0902)
LMArena Vision: humor12431304Qwen3.8 Max (0902)
LMArena Vision: creative writing12201312Qwen3.8 Max (0902)
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
BenchmarkQwen3.5-122B-A10BQwen3.8 Max (0902)Leader
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

Qwen3.5-122B-A10B$0.0013Fits in one request
Qwen3.8 Max (0902)$0.0050Fits in one request

Qwen3.5-122B-A10B costs less

Repository review

50K input + 3K output tokens

Qwen3.5-122B-A10B$0.019Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request

Qwen3.5-122B-A10B costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-122B-A10B$0.073Fits in one request
Qwen3.8 Max (0902)$0.460Fits in one request

Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B and Qwen3.8 Max (0902)
SpecificationQwen3.5-122B-A10BQwen3.8 Max (0902)
MakerQwenQwen
WeightsOpen weightsNo public weights listed
ReleasedFebruary 25, 2026September 3, 2026
Context window262K1M
Input $/Mtok$0.26$2.00
Output $/Mtok$2.08$6.00
Coding index22.963.5
Independent measurements behind it12
Cost per solved taskNot computable$1.32
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5-122B-A10B better than Qwen3.8 Max (0902) for coding?

Pick Qwen3.8 Max (0902) for coding: it scores 63.5 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B. Pick Qwen3.5-122B-A10B when output tokens cost 2.9x less.

Which is cheaper, Qwen3.5-122B-A10B or Qwen3.8 Max (0902)?

Qwen3.5-122B-A10B costs $0.26 per million input tokens and $2.08 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Cost per solved task is known for Qwen3.8 Max (0902) only.

Which has the bigger context window, Qwen3.5-122B-A10B or Qwen3.8 Max (0902)?

Qwen3.8 Max (0902), with 1M tokens against 262K.

How many benchmarks is the Qwen3.5-122B-A10B vs Qwen3.8 Max (0902) comparison based on?

48 benchmarks have a result for both models as of October 21, 2026. Qwen3.5-122B-A10B's coding index rests on 1 independent benchmark and Qwen3.8 Max (0902)'s on 2. Where only one model has a result, the page says so instead of naming a winner.

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