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Qwen3.5-122B-A10B vs Step 3.5 Flash

Qwen3.5-122B-A10B leads Step 3.5 Flash on the Artificial Analysis Intelligence Index, 17.7 to 17.0, and Step 3.5 Flash costs 6.9x less per output token ($0.30 vs $2.08 per million). Updated October 23, 2026; 35 benchmarks have a result for both.

Replace Qwen3.5-122B-A10B Replace Step 3.5 Flash
Qwen3.5-122B-A10BQwen
Coding
No data
Overall
No data
Output $/M
$2.08
33
Step 3.5 FlashStepFun
Coding
No data
Overall
No data
Output $/M
$0.30
2
vs boards won of 35 shared

Qwen3.5-122B-A10B or Step 3.5 Flash: which to pick

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

Pick Qwen3.5-122B-A10B for work measured by Terminal-Bench Hard (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Model AQwen3.5-122B-A10BQwenNot benchmarked1 independent benchmarkNo cost per solved taskModel BStep 3.5 FlashStepFunNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
35
Qwen3.5-122B-A10B only
16
Step 3.5 Flash only
1
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
Qwen3.5-122B-A10B not benchmarked, Step 3.5 Flash not benchmarked.
Widest category
General, 3.1 points apart on average over 19 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): Qwen3.5-122B-A10B 76.3% against Step 3.5 Flash 63.0%, 13.3 points apart on a 0 to 100 scale.
Output price
Qwen3.5-122B-A10B $2.08 against Step 3.5 Flash $0.30 per million output tokens, 6.9x apart.
Context window
Both take 262K tokens.

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-A10BBarsStep 3.5 FlashTies
Coding21
Intelligence10
Agentic work01
Reasoning50
Math20
Knowledge40
General190
All shared boards332
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
Coding benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
LMArena WebDev1361Not measuredOnly Qwen3.5-122B-A10B measured
AA Coding Index43.3Not measuredOnly Qwen3.5-122B-A10B measured
SciCode39.7%Not measuredOnly Qwen3.5-122B-A10B measured
Terminal-Bench Hard (Artificial Analysis run)31.1%32.6%Step 3.5 Flash
LMArena Text: coding14361436Qwen3.5-122B-A10B
LMArena Text: software and IT14361434Qwen3.5-122B-A10B
LMArena WebDev: React1352Not measuredOnly Qwen3.5-122B-A10B measured
LMArena WebDev: HTML1352Not measuredOnly Qwen3.5-122B-A10B measured
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
AA Intelligence Index17.717.0Qwen3.5-122B-A10B
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
τ²-Bench Telecom93.6%94.4%Step 3.5 Flash
Neither model has a result on the other 41 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
GPQA Diamond (Artificial Analysis run)85.7%83.1%Qwen3.5-122B-A10B
Humanity's Last Exam (Artificial Analysis run)25.2%24.5%Qwen3.5-122B-A10B
Mystery game puzzles17.0%Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Text: hard prompts14211411Qwen3.5-122B-A10B
LMArena Text: expert14311422Qwen3.5-122B-A10B
LMArena Text: hard prompts in English14311421Qwen3.5-122B-A10B
LMArena Vision: diagrams1249Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: homework1261Not measuredOnly Qwen3.5-122B-A10B measured
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
LMArena Text: math14311408Qwen3.5-122B-A10B
LMArena Text: mathematical work14311421Qwen3.5-122B-A10B
MathArenaNot measured19.4%Only Step 3.5 Flash measured
Neither model has a result on the other 11 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
LMArena Text: science14331415Qwen3.5-122B-A10B
LMArena Text: medicine and healthcare14231409Qwen3.5-122B-A10B
LMArena Text: legal and government14221408Qwen3.5-122B-A10B
LMArena Text: business and finance14141394Qwen3.5-122B-A10B
Neither model has a result on the other 16 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for Qwen3.5-122B-A10B and Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
IFBench75.7%66.5%Qwen3.5-122B-A10B
Long context reasoning (AA-LCR)76.3%63.0%Qwen3.5-122B-A10B
DTBench84.3%Not measuredOnly Qwen3.5-122B-A10B measured
LMCA32.2%Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Text14181403Qwen3.5-122B-A10B
LMArena Text: instruction following14001385Qwen3.5-122B-A10B
LMArena Text: creative writing13681357Qwen3.5-122B-A10B
LMArena Vision1244Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Text: English14281417Qwen3.5-122B-A10B
LMArena Text: non-English14011385Qwen3.5-122B-A10B
LMArena Text: Chinese14631446Qwen3.5-122B-A10B
LMArena Text: German14251405Qwen3.5-122B-A10B
LMArena Text: Japanese13671353Qwen3.5-122B-A10B
LMArena Text: Korean13531350Qwen3.5-122B-A10B
LMArena Text: French14431421Qwen3.5-122B-A10B
LMArena Text: Spanish14251419Qwen3.5-122B-A10B
LMArena Text: Russian14001385Qwen3.5-122B-A10B
LMArena Text: Polish13991389Qwen3.5-122B-A10B
LMArena Text: multi-turn14171405Qwen3.5-122B-A10B
LMArena Text: longer queries14111402Qwen3.5-122B-A10B
LMArena Text: writing and language13871372Qwen3.5-122B-A10B
LMArena Text: entertainment and media13661360Qwen3.5-122B-A10B
LMArena Vision: English1249Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: Chinese1301Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: reading text1251Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: humor1243Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: creative writing1220Not measuredOnly Qwen3.5-122B-A10B measured
Neither model has a result on the other 21 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 Step 3.5 Flash
BenchmarkQwen3.5-122B-A10BStep 3.5 FlashLeader
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
Step 3.5 Flash$0.0003Fits in one request

Step 3.5 Flash costs less

Repository review

50K input + 3K output tokens

Qwen3.5-122B-A10B$0.019Fits in one request
Step 3.5 Flash$0.0059Fits in one request

Step 3.5 Flash costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-122B-A10B$0.073Fits in one request
Step 3.5 Flash$0.023Fits in one request

Step 3.5 Flash 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 Step 3.5 Flash
SpecificationQwen3.5-122B-A10BStepFun Step 3.5 Flash
MakerQwenStepFun
WeightsOpen weightsOpen weights
ReleasedFebruary 25, 2026January 29, 2026
Context window262K262K
Input $/Mtok$0.26$0.10
Output $/Mtok$2.08$0.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5-122B-A10B better than Step 3.5 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3.5-122B-A10B for work measured by Terminal-Bench Hard (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Which is cheaper, Qwen3.5-122B-A10B or Step 3.5 Flash?

Qwen3.5-122B-A10B costs $0.26 per million input tokens and $2.08 per million output tokens; Step 3.5 Flash costs $0.10 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen3.5-122B-A10B or Step 3.5 Flash?

Neither: both take 262K tokens.

How many benchmarks is the Qwen3.5-122B-A10B vs Step 3.5 Flash comparison based on?

35 benchmarks have a result for both models as of October 23, 2026. Qwen3.5-122B-A10B's coding index rests on 1 independent benchmark and Step 3.5 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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