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Ministral 3 3B 2512 vs Qwen3.6 27B

Qwen3.6 27B leads Ministral 3 3B 2512 on the Artificial Analysis Intelligence Index, 21.4 to 4.8, and Ministral 3 3B 2512 costs 27.0x less per output token ($0.10 vs $2.70 per million). Updated October 22, 2026; 3 benchmarks have a result for both.

Ministral 3 3B 2512Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.10
0
Qwen3.6 27BQwen
Coding
36.8
Overall
45.3
Output $/M
$2.70
3
vs boards won of 3 shared

Ministral 3 3B 2512 or Qwen3.6 27B: which to pick

Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Ministral 3 3B 2512 has none, so the two cannot be ranked on coding.

Pick Ministral 3 3B 2512 for output tokens 27.0x cheaper ($0.10 vs $2.70 per million).

Shared results
3
Ministral 3 3B 2512 only
4
Qwen3.6 27B only
22
Like-for-like categories
3 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 3B 2512 not benchmarked, Qwen3.6 27B 36.8 from 2 benchmarks.
Widest category
Coding, 48.9 points apart on average over 1 shared benchmark.
Widest single gap
AA Coding Index: Ministral 3 3B 2512 4.8 against Qwen3.6 27B 53.7, 48.9 points apart on a 0 to 100 scale.
Output price
Ministral 3 3B 2512 $0.10 against Qwen3.6 27B $2.70 per million output tokens, 27.0x apart.
Context window
Ministral 3 3B 2512 takes 131K tokens, Qwen3.6 27B 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
CategoryMinistral 3 3B 2512BarsQwen3.6 27BTies
Coding01
Intelligence01
Agentic work01
All shared boards03
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
AA Coding Index4.853.7Qwen3.6 27B
SWE-bench Verified (Vals AI)Not measured70.0%Only Qwen3.6 27B measured
Vibe Code Bench (Vals AI)Not measured11.9%Only Qwen3.6 27B measured
SciCodeNot measured42.8%Only Qwen3.6 27B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured34.8%Only Qwen3.6 27B measured
Neither model has a result on the other 38 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
AA Intelligence Index4.821.4Qwen3.6 27B
Epoch Capabilities IndexNot measured146.2Only Qwen3.6 27B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
AA Agentic Index0.818.5Qwen3.6 27B
τ²-Bench TelecomNot measured94.2%Only Qwen3.6 27B measured
Neither model has a result on the other 40 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Reasoning benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
GPQA Diamond (Artificial Analysis run)Not measured84.2%Only Qwen3.6 27B measured
Humanity's Last Exam (Artificial Analysis run)Not measured23.1%Only Qwen3.6 27B measured
GPQA Diamond (Epoch AI run)Not measured85.9%Only Qwen3.6 27B measured
Mystery game puzzlesNot measured7.0%Only Qwen3.6 27B measured
Neither model has a result on the other 19 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Math benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
OTIS Mock AIMENot measured91.1%Only Qwen3.6 27B measured
FrontierMath, tiers 1 to 3Not measured35.1%Only Qwen3.6 27B measured
Neither model has a result on the other 12 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
CaseLaw (Vals AI)Not measured53.2%Only Qwen3.6 27B measured
CorpFin (Vals AI)Not measured62.3%Only Qwen3.6 27B measured
TaxEval (Vals AI)Not measured71.3%Only Qwen3.6 27B measured
MortgageTax (Vals AI)Not measured68.3%Only Qwen3.6 27B 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 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
Design Arena: websites1027Not measuredOnly Ministral 3 3B 2512 measured
Design Arena: game dev948Not measuredOnly Ministral 3 3B 2512 measured
Design Arena: 3D962Not measuredOnly Ministral 3 3B 2512 measured
Design Arena: all code categories1009Not measuredOnly Ministral 3 3B 2512 measured
Neither model has a result on the other 5 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
General benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
SAGE (Vals AI)Not measured45.6%Only Qwen3.6 27B measured
IFBenchNot measured67.6%Only Qwen3.6 27B measured
Long context reasoning (AA-LCR)Not measured77.3%Only Qwen3.6 27B measured
DTBenchNot measured78.1%Only Qwen3.6 27B measured
LMCANot measured34.5%Only Qwen3.6 27B measured
EQ-Bench 4Not measured1026Only Qwen3.6 27B measured
Neither model has a result on the other 42 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Ministral 3 3B 2512 and Qwen3.6 27B
BenchmarkMinistral 3 3B 2512Qwen3.6 27BLeader
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 3B 2512$0.0001Fits in one request
Qwen3.6 27B$0.0018Fits in one request

Ministral 3 3B 2512 costs less

Repository review

50K input + 3K output tokens

Ministral 3 3B 2512$0.0053Fits in one request
Qwen3.6 27B$0.031Fits in one request

Ministral 3 3B 2512 costs less

Agent loop

200K input + 10K output tokens

Ministral 3 3B 2512$0.021Exceeds the context window
Qwen3.6 27B$0.117Fits in one request

Ministral 3 3B 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 3B 2512 and Qwen3.6 27B
SpecificationMistral Ministral 3 3B 2512Qwen3.6 27B
MakerMistral AIQwen
WeightsOpen weightsOpen weights
ReleasedDecember 2, 2025April 27, 2026
Context window131K262K
Input $/Mtok$0.10$0.45
Output $/Mtok$0.10$2.70
Coding indexNot benchmarked36.8
Independent measurements behind it02
Cost per solved taskNot computable$1.30
SourceOpenRouter listingOpenRouter listing

Questions

Is Ministral 3 3B 2512 better than Qwen3.6 27B for coding?

Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Ministral 3 3B 2512 has none, so the two cannot be ranked on coding. Pick Ministral 3 3B 2512 for output tokens 27.0x cheaper ($0.10 vs $2.70 per million).

Which is cheaper, Ministral 3 3B 2512 or Qwen3.6 27B?

Ministral 3 3B 2512 costs $0.10 per million input tokens and $0.10 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.

Which has the bigger context window, Ministral 3 3B 2512 or Qwen3.6 27B?

Qwen3.6 27B, with 262K tokens against 131K.

How many benchmarks is the Ministral 3 3B 2512 vs Qwen3.6 27B comparison based on?

3 benchmarks have a result for both models as of October 22, 2026. Ministral 3 3B 2512's coding index rests on 0 independent benchmarks and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.

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