Enter opens the highlighted result. Esc closes.

Gemma 4 31B vs Ministral 3 8B 2512

Gemma 4 31B leads Ministral 3 8B 2512 on the Artificial Analysis Intelligence Index, 14.7 to 5.5, and Ministral 3 8B 2512 costs 2.7x less per output token ($0.15 vs $0.40 per million). Updated October 22, 2026; 3 benchmarks have a result for both.

Gemma 4 31BGoogle
Coding
39.0
Overall
42.1
Output $/M
$0.40
3
Ministral 3 8B 2512Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.15
0
vs boards won of 3 shared

Gemma 4 31B or Ministral 3 8B 2512: which to pick

Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Ministral 3 8B 2512 has none, so the two cannot be ranked on coding.

Pick Ministral 3 8B 2512 for output tokens 2.7x cheaper ($0.15 vs $0.40 per million).

Shared results
3
Gemma 4 31B only
69
Ministral 3 8B 2512 only
4
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
Gemma 4 31B 39.0 from 2 benchmarks, Ministral 3 8B 2512 not benchmarked.
Widest category
Coding, 33.7 points apart on average over 1 shared benchmark.
Widest single gap
AA Coding Index: Gemma 4 31B 43.4 against Ministral 3 8B 2512 9.7, 33.7 points apart on a 0 to 100 scale.
Output price
Gemma 4 31B $0.40 against Ministral 3 8B 2512 $0.15 per million output tokens, 2.7x 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
CategoryGemma 4 31BBarsMinistral 3 8B 2512Ties
Coding10
Intelligence10
Agentic work10
All shared boards30
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
LiveBench coding49.0%Not measuredOnly Gemma 4 31B measured
LMArena WebDev1367Not measuredOnly Gemma 4 31B measured
AA Coding Index43.49.7Gemma 4 31B
SciCode45.5%Not measuredOnly Gemma 4 31B measured
Terminal-Bench Hard (Artificial Analysis run)36.4%Not measuredOnly Gemma 4 31B measured
WeirdML52.3%Not measuredOnly Gemma 4 31B measured
ALE-Bench925.5Not measuredOnly Gemma 4 31B measured
LMArena Text: coding1459Not measuredOnly Gemma 4 31B measured
LMArena Text: software and IT1463Not measuredOnly Gemma 4 31B measured
LMArena WebDev: React1359Not measuredOnly Gemma 4 31B measured
LMArena WebDev: HTML1380Not measuredOnly Gemma 4 31B measured
SciCode8.9%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
AA Intelligence Index14.75.5Gemma 4 31B
Epoch Capabilities Index143.0Not measuredOnly Gemma 4 31B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
AA Agentic Index4.20.6Gemma 4 31B
LiveBench research44.4%Not measuredOnly Gemma 4 31B measured
LiveBench browser4.0%Not measuredOnly Gemma 4 31B measured
LiveBench long agentic13.3%Not measuredOnly Gemma 4 31B measured
τ²-Bench Telecom65.5%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 37 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Reasoning benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
LiveBench reasoning68.3%Not measuredOnly Gemma 4 31B measured
GPQA Diamond (Artificial Analysis run)85.7%Not measuredOnly Gemma 4 31B measured
Humanity's Last Exam (Artificial Analysis run)23.6%Not measuredOnly Gemma 4 31B measured
GPQA Diamond (Epoch AI run)75.8%Not measuredOnly Gemma 4 31B measured
LMArena Text: hard prompts1448Not measuredOnly Gemma 4 31B measured
LMArena Text: expert1464Not measuredOnly Gemma 4 31B measured
LMArena Text: hard prompts in English1456Not measuredOnly Gemma 4 31B measured
LMArena Vision: diagrams1283Not measuredOnly Gemma 4 31B measured
LMArena Vision: homework1310Not measuredOnly Gemma 4 31B measured
Kagi LLM Benchmark63.5%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
OTIS Mock AIME73.3%Not measuredOnly Gemma 4 31B measured
LMArena Text: math1463Not measuredOnly Gemma 4 31B measured
LMArena Text: mathematical work1465Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 11 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Knowledge benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
CaseLaw (Vals AI)52.6%Not measuredOnly Gemma 4 31B measured
MortgageTax (Vals AI)61.4%Not measuredOnly Gemma 4 31B measured
SimpleQA Verified10.4%Not measuredOnly Gemma 4 31B measured
LMArena Text: science1457Not measuredOnly Gemma 4 31B measured
LMArena Text: medicine and healthcare1451Not measuredOnly Gemma 4 31B measured
LMArena Text: legal and government1438Not measuredOnly Gemma 4 31B measured
LMArena Text: business and finance1430Not measuredOnly Gemma 4 31B measured
FACTS Benchmark Suite45.3%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
Design Arena: websitesNot measured1065Only Ministral 3 8B 2512 measured
Design Arena: game devNot measured990Only Ministral 3 8B 2512 measured
Design Arena: 3DNot measured1031Only Ministral 3 8B 2512 measured
Design Arena: all code categoriesNot measured1052Only Ministral 3 8B 2512 measured
LiveBench design58.4%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 4 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
General benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
LiveBench data analysis53.3%Not measuredOnly Gemma 4 31B measured
SAGE (Vals AI)55.0%Not measuredOnly Gemma 4 31B measured
IFBench75.6%Not measuredOnly Gemma 4 31B measured
Long context reasoning (AA-LCR)69.7%Not measuredOnly Gemma 4 31B measured
DTBench82.7%Not measuredOnly Gemma 4 31B measured
LMCA39.3%Not measuredOnly Gemma 4 31B measured
Surface Evolver Bench30.6%Not measuredOnly Gemma 4 31B measured
LMArena Text1443Not measuredOnly Gemma 4 31B measured
LMArena Text: instruction following1433Not measuredOnly Gemma 4 31B measured
LMArena Text: creative writing1417Not measuredOnly Gemma 4 31B measured
LMArena Vision1276Not measuredOnly Gemma 4 31B measured
LMArena Text: English1451Not measuredOnly Gemma 4 31B measured
LMArena Text: non-English1430Not measuredOnly Gemma 4 31B measured
LMArena Text: Chinese1475Not measuredOnly Gemma 4 31B measured
LMArena Text: French1436Not measuredOnly Gemma 4 31B measured
LMArena Text: Spanish1442Not measuredOnly Gemma 4 31B measured
LMArena Text: Russian1460Not measuredOnly Gemma 4 31B measured
LMArena Text: Polish1433Not measuredOnly Gemma 4 31B measured
LMArena Text: multi-turn1452Not measuredOnly Gemma 4 31B measured
LMArena Text: longer queries1446Not measuredOnly Gemma 4 31B measured
LMArena Text: writing and language1432Not measuredOnly Gemma 4 31B measured
LMArena Text: entertainment and media1405Not measuredOnly Gemma 4 31B measured
LMArena Vision: English1271Not measuredOnly Gemma 4 31B measured
LMArena Vision: Chinese1326Not measuredOnly Gemma 4 31B measured
LMArena Vision: reading text1282Not measuredOnly Gemma 4 31B measured
LMArena Vision: humor1280Not measuredOnly Gemma 4 31B measured
LMArena Vision: captioning1218Not measuredOnly Gemma 4 31B measured
LMArena Vision: recognizing things1226Not measuredOnly Gemma 4 31B measured
LMArena Vision: creative writing1285Not measuredOnly Gemma 4 31B measured
LMArena Document1425Not measuredOnly Gemma 4 31B measured
EQ-Bench 41120Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 4 31B and Ministral 3 8B 2512
BenchmarkGemma 4 31BMinistral 3 8B 2512Leader
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

Gemma 4 31B$0.0003Fits in one request
Ministral 3 8B 2512$0.0002Fits in one request

Ministral 3 8B 2512 costs less

Repository review

50K input + 3K output tokens

Gemma 4 31B$0.0082Fits in one request
Ministral 3 8B 2512$0.0080Fits in one request

Ministral 3 8B 2512 costs less

Agent loop

200K input + 10K output tokens

Gemma 4 31B$0.032Fits in one request
Ministral 3 8B 2512$0.032Fits in one request

Ministral 3 8B 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 Gemma 4 31B and Ministral 3 8B 2512
SpecificationGoogle Gemma 4 31BMistral Ministral 3 8B 2512
MakerGoogleMistral AI
WeightsOpen weightsOpen weights
ReleasedApril 2, 2026December 2, 2025
Context window262K262K
Input $/Mtok$0.14$0.15
Output $/Mtok$0.40$0.15
Coding index39.0Not benchmarked
Independent measurements behind it20
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 4 31B better than Ministral 3 8B 2512 for coding?

Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Ministral 3 8B 2512 has none, so the two cannot be ranked on coding. Pick Ministral 3 8B 2512 for output tokens 2.7x cheaper ($0.15 vs $0.40 per million).

Which is cheaper, Gemma 4 31B or Ministral 3 8B 2512?

Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; Ministral 3 8B 2512 costs $0.15 and $0.15. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 4 31B or Ministral 3 8B 2512?

Neither: both take 262K tokens.

How many benchmarks is the Gemma 4 31B vs Ministral 3 8B 2512 comparison based on?

3 benchmarks have a result for both models as of October 22, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and Ministral 3 8B 2512's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next