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Ministral 3 14B 2512 vs Qwen3.5-35B-A3B

Qwen3.5-35B-A3B leads Ministral 3 14B 2512 on the Artificial Analysis Intelligence Index, 19.3 to 6.0, and Ministral 3 14B 2512 costs 6.5x less per output token ($0.20 vs $1.30 per million). Updated October 22, 2026; 1 benchmarks have a result for both.

Ministral 3 14B 2512Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.20
0
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
1
vs boards won of 1 shared

Ministral 3 14B 2512 or Qwen3.5-35B-A3B: which to pick

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

Pick Ministral 3 14B 2512 for output tokens 6.5x cheaper ($0.20 vs $1.30 per million) and work measured by AA Intelligence Index, where it leads.

Shared results
1
Ministral 3 14B 2512 only
6
Qwen3.5-35B-A3B only
45
Like-for-like categories
1 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
Ministral 3 14B 2512 not benchmarked, Qwen3.5-35B-A3B not benchmarked.
Widest category
Intelligence, 13.3 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: Ministral 3 14B 2512 6.0 against Qwen3.5-35B-A3B 19.3, 13.3 points apart on a 0 to 100 scale.
Output price
Ministral 3 14B 2512 $0.20 against Qwen3.5-35B-A3B $1.30 per million output tokens, 6.5x 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
CategoryMinistral 3 14B 2512BarsQwen3.5-35B-A3BTies
Intelligence01
All shared boards01
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
Coding benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
AA Coding Index14.4Not measuredOnly Ministral 3 14B 2512 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured26.5%Only Qwen3.5-35B-A3B measured
ALE-BenchNot measured221.8Only Qwen3.5-35B-A3B measured
LMArena Text: codingNot measured1410Only Qwen3.5-35B-A3B measured
LMArena Text: software and ITNot measured1415Only Qwen3.5-35B-A3B measured
LMArena WebDev: ReactNot measured1238Only Qwen3.5-35B-A3B measured
LMArena WebDev: HTMLNot measured1301Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
AA Intelligence Index6.019.3Qwen3.5-35B-A3B
Epoch Capabilities IndexNot measured142.5Only Qwen3.5-35B-A3B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
AA Agentic Index1.1Not measuredOnly Ministral 3 14B 2512 measured
τ²-Bench TelecomNot measured89.2%Only Qwen3.5-35B-A3B measured
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Reasoning benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
GPQA Diamond (Artificial Analysis run)Not measured84.5%Only Qwen3.5-35B-A3B measured
Humanity's Last Exam (Artificial Analysis run)Not measured21.0%Only Qwen3.5-35B-A3B measured
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
LMArena Text: hard promptsNot measured1400Only Qwen3.5-35B-A3B measured
LMArena Text: expertNot measured1408Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts in EnglishNot measured1411Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 17 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
OTIS Mock AIMENot measured70.0%Only Qwen3.5-35B-A3B measured
LMArena Text: mathNot measured1404Only Qwen3.5-35B-A3B measured
LMArena Text: mathematical workNot measured1410Only Qwen3.5-35B-A3B measured
MathArenaNot measured14.7%Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
LMArena Text: scienceNot measured1413Only Qwen3.5-35B-A3B measured
LMArena Text: medicine and healthcareNot measured1421Only Qwen3.5-35B-A3B measured
LMArena Text: legal and governmentNot measured1399Only Qwen3.5-35B-A3B measured
LMArena Text: business and financeNot measured1394Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 16 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Web design benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
Design Arena: websites1081Not measuredOnly Ministral 3 14B 2512 measured
Design Arena: game dev1037Not measuredOnly Ministral 3 14B 2512 measured
Design Arena: 3D989Not measuredOnly Ministral 3 14B 2512 measured
Design Arena: all code categories1064Not measuredOnly Ministral 3 14B 2512 measured
Neither model has a result on the other 5 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
General benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-A3BLeader
IFBenchNot measured72.5%Only Qwen3.5-35B-A3B measured
Long context reasoning (AA-LCR)Not measured72.0%Only Qwen3.5-35B-A3B measured
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
LMArena TextNot measured1395Only Qwen3.5-35B-A3B measured
LMArena Text: instruction followingNot measured1379Only Qwen3.5-35B-A3B measured
LMArena Text: creative writingNot measured1347Only Qwen3.5-35B-A3B measured
LMArena Text: EnglishNot measured1407Only Qwen3.5-35B-A3B measured
LMArena Text: non-EnglishNot measured1378Only Qwen3.5-35B-A3B measured
LMArena Text: ChineseNot measured1457Only Qwen3.5-35B-A3B measured
LMArena Text: GermanNot measured1367Only Qwen3.5-35B-A3B measured
LMArena Text: JapaneseNot measured1326Only Qwen3.5-35B-A3B measured
LMArena Text: KoreanNot measured1355Only Qwen3.5-35B-A3B measured
LMArena Text: FrenchNot measured1412Only Qwen3.5-35B-A3B measured
LMArena Text: SpanishNot measured1390Only Qwen3.5-35B-A3B measured
LMArena Text: RussianNot measured1376Only Qwen3.5-35B-A3B measured
LMArena Text: PolishNot measured1385Only Qwen3.5-35B-A3B measured
LMArena Text: multi-turnNot measured1390Only Qwen3.5-35B-A3B measured
LMArena Text: longer queriesNot measured1389Only Qwen3.5-35B-A3B measured
LMArena Text: writing and languageNot measured1365Only Qwen3.5-35B-A3B measured
LMArena Text: entertainment and mediaNot measured1347Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Ministral 3 14B 2512 and Qwen3.5-35B-A3B
BenchmarkMinistral 3 14B 2512Qwen3.5-35B-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

Ministral 3 14B 2512$0.0003Fits in one request
Qwen3.5-35B-A3B$0.0008Fits in one request

Ministral 3 14B 2512 costs less

Repository review

50K input + 3K output tokens

Ministral 3 14B 2512$0.011Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Ministral 3 14B 2512 costs less

Agent loop

200K input + 10K output tokens

Ministral 3 14B 2512$0.042Fits in one request
Qwen3.5-35B-A3B$0.045Fits in one request

Ministral 3 14B 2512 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 Ministral 3 14B 2512 and Qwen3.5-35B-A3B
SpecificationMistral Ministral 3 14B 2512Qwen3.5-35B-A3B
MakerMistral AIQwen
WeightsOpen weightsOpen weights
ReleasedDecember 2, 2025February 25, 2026
Context window262K262K
Input $/Mtok$0.20$0.1625
Output $/Mtok$0.20$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Ministral 3 14B 2512 better than Qwen3.5-35B-A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Ministral 3 14B 2512 for output tokens 6.5x cheaper ($0.20 vs $1.30 per million) and work measured by AA Intelligence Index, where it leads.

Which is cheaper, Ministral 3 14B 2512 or Qwen3.5-35B-A3B?

Ministral 3 14B 2512 costs $0.20 per million input tokens and $0.20 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for neither of them.

Which has the bigger context window, Ministral 3 14B 2512 or Qwen3.5-35B-A3B?

Neither: both take 262K tokens.

How many benchmarks is the Ministral 3 14B 2512 vs Qwen3.5-35B-A3B comparison based on?

1 benchmarks have a result for both models as of October 22, 2026. Ministral 3 14B 2512'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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