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Gemini 3.6 Flash vs Mistral Large 3 2512

Gemini 3.6 Flash leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 34.0 to 9.3, and Mistral Large 3 2512 costs 2.5x less per output token ($1.50 vs $3.75 per million). Updated October 21, 2026; 23 benchmarks have a result for both.

Gemini 3.6 FlashGoogle
Coding
62.5
Overall
68.3
Output $/M
$3.75
23
Mistral Large 3 2512Mistral AI
Coding
No data
Overall
No data
Output $/M
$1.50
0
vs boards won of 23 shared

Gemini 3.6 Flash or Mistral Large 3 2512: which to pick

Only Gemini 3.6 Flash has a coding score, 62.5 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.

Pick Mistral Large 3 2512 for output tokens 2.5x cheaper ($1.50 vs $3.75 per million) and a lower cost per solved task ($0.77 against $1.49).

Shared results
23
Gemini 3.6 Flash only
86
Mistral Large 3 2512 only
5
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
Gemini 3.6 Flash 62.5 from 4 benchmarks, Mistral Large 3 2512 not benchmarked.
Widest category
Coding, 33.8 points apart on average over 4 shared benchmarks.
Widest single gap
AA Coding Index: Gemini 3.6 Flash 69.2 against Mistral Large 3 2512 20.1, 49.1 points apart on a 0 to 100 scale.
Output price
Gemini 3.6 Flash $3.75 against Mistral Large 3 2512 $1.50 per million output tokens, 2.5x apart.
Context window
Gemini 3.6 Flash takes 1.05M tokens, Mistral Large 3 2512 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
CategoryGemini 3.6 FlashBarsMistral Large 3 2512Ties
Coding40
Intelligence10
Agentic work10
Reasoning20
Knowledge50
Web design70
General30
All shared boards230
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
LMArena WebDev1538Not measuredOnly Gemini 3.6 Flash measured
AA Coding Index69.220.1Gemini 3.6 Flash
LiveCodeBench (Vals AI)88.1%55.3%Gemini 3.6 Flash
SWE-bench Verified (Vals AI)79.6%41.4%Gemini 3.6 Flash
Vibe Code Bench (Vals AI)64.0%Not measuredOnly Gemini 3.6 Flash measured
Code migration (Vals AI)30.9%Not measuredOnly Gemini 3.6 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.6 Flash measured
IOI (Vals AI)35.1%Not measuredOnly Gemini 3.6 Flash measured
Terminal-Bench 2.1 (Vals AI)73.8%Not measuredOnly Gemini 3.6 Flash measured
CyberBench (Vals AI)45.4%Not measuredOnly Gemini 3.6 Flash measured
SciCode53.4%Not measuredOnly Gemini 3.6 Flash measured
FrontierCode34.4%Not measuredOnly Gemini 3.6 Flash measured
WeirdML56.1%Not measuredOnly Gemini 3.6 Flash measured
ALE-Bench715.5264.7Gemini 3.6 Flash
LMArena Text: coding1491Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: software and IT1492Not measuredOnly Gemini 3.6 Flash measured
LMArena WebDev: React1528Not measuredOnly Gemini 3.6 Flash measured
LMArena WebDev: HTML1547Not measuredOnly Gemini 3.6 Flash measured
LMArena WebDev: from an image1545Not measuredOnly Gemini 3.6 Flash measured
SciCode10.8%Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
AA Intelligence Index34.09.3Gemini 3.6 Flash
Epoch Capabilities Index154.5Not measuredOnly Gemini 3.6 Flash measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
AA Agentic Index29.01.0Gemini 3.6 Flash
Design Arena: agents building web apps1197Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building full-stack apps1181Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building mobile apps1199Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building Android apps1203Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building games1181Not measuredOnly Gemini 3.6 Flash measured
Design Arena: HTML slides1148Not measuredOnly Gemini 3.6 Flash measured
Design Arena: PowerPoint slides1146Not measuredOnly Gemini 3.6 Flash measured
Design Arena: spreadsheets1034Not measuredOnly Gemini 3.6 Flash measured
Finance Agent (Vals AI)56.3%Not measuredOnly Gemini 3.6 Flash measured
Tax Agent Bench (Vals AI)18.0%Not measuredOnly Gemini 3.6 Flash measured
Legal Research Bench (Vals AI)25.0%Not measuredOnly Gemini 3.6 Flash measured
Excel Modeling Benchmark (Vals AI)65.4%Not measuredOnly Gemini 3.6 Flash measured
BioMysteryBench (Vals AI)58.5%Not measuredOnly Gemini 3.6 Flash measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly Gemini 3.6 Flash measured
APEX-Agents46.9%Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
GPQA Diamond93.4%68.4%Gemini 3.6 Flash
MMMU Pro (Vals AI)88.4%66.2%Gemini 3.6 Flash
GPQA Diamond (Artificial Analysis run)92.8%Not measuredOnly Gemini 3.6 Flash measured
Humanity's Last Exam (Artificial Analysis run)40.8%Not measuredOnly Gemini 3.6 Flash measured
GPQA Diamond (Epoch AI run)94.1%Not measuredOnly Gemini 3.6 Flash measured
ARC-AGI91.2%Not measuredOnly Gemini 3.6 Flash measured
ARC-AGI-260.4%Not measuredOnly Gemini 3.6 Flash measured
Chess puzzles42.0%Not measuredOnly Gemini 3.6 Flash measured
Mystery game puzzles30.0%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: hard prompts1486Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: expert1490Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: hard prompts in English1484Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: diagrams1314Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: homework1314Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 8 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Math benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
AIMENot measured42.9%Only Mistral Large 3 2512 measured
MGSM (Vals AI)Not measured85.4%Only Mistral Large 3 2512 measured
OTIS Mock AIME94.2%Not measuredOnly Gemini 3.6 Flash measured
FrontierMath, tiers 1 to 358.9%Not measuredOnly Gemini 3.6 Flash measured
FrontierMath, tier 422.0%Not measuredOnly Gemini 3.6 Flash measured
ProofBench36.0%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: math1508Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: mathematical work1492Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
MMLU Pro89.3%79.8%Gemini 3.6 Flash
LegalBench (Vals AI)86.7%79.1%Gemini 3.6 Flash
CaseLaw (Vals AI)Not measured61.4%Only Mistral Large 3 2512 measured
CorpFin (Vals AI)63.3%61.0%Gemini 3.6 Flash
TaxEval (Vals AI)74.9%73.1%Gemini 3.6 Flash
MortgageTax (Vals AI)67.6%52.1%Gemini 3.6 Flash
MedQA (Vals AI)Not measured82.2%Only Mistral Large 3 2512 measured
MedCode (Vals AI)53.1%Not measuredOnly Gemini 3.6 Flash measured
SimpleQA Verified66.2%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: science1489Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: medicine and healthcare1469Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: legal and government1479Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: business and finance1464Not measuredOnly Gemini 3.6 Flash measured
FACTS Benchmark Suite65.3%Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
Design Arena: websites13001162Gemini 3.6 Flash
Design Arena: UI components12971102Gemini 3.6 Flash
Design Arena: game dev12631080Gemini 3.6 Flash
Design Arena: data viz12891136Gemini 3.6 Flash
Design Arena: 3D12721100Gemini 3.6 Flash
Design Arena: all code categories12901142Gemini 3.6 Flash
Design Arena: SVGNot measured993Only Mistral Large 3 2512 measured
Design Arena: ASCII art12811069Gemini 3.6 Flash
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
General benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 2512Leader
Public Benefits Bench (Vals AI)56.6%Not measuredOnly Gemini 3.6 Flash measured
SAGE (Vals AI)48.7%24.6%Gemini 3.6 Flash
MedScribe (Vals AI)79.7%Not measuredOnly Gemini 3.6 Flash measured
Vals Multimodal Index65.1%Not measuredOnly Gemini 3.6 Flash measured
Long context reasoning (AA-LCR)80.0%Not measuredOnly Gemini 3.6 Flash measured
DTBench95.5%65.1%Gemini 3.6 Flash
LMCA44.9%16.7%Gemini 3.6 Flash
Furniture assembly23.3%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text1480Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: instruction following1467Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: creative writing1466Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision1299Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: English1482Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: non-English1470Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Chinese1531Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: German1480Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Japanese1475Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Korean1429Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: French1503Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Spanish1476Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Russian1488Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Polish1473Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: multi-turn1481Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: longer queries1475Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: writing and language1470Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: entertainment and media1456Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: English1295Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: Chinese1357Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: reading text1312Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: humor1289Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: creative writing1278Not measuredOnly Gemini 3.6 Flash measured
LMArena Document1456Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.6 Flash and Mistral Large 3 2512
BenchmarkGemini 3.6 FlashMistral Large 3 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

Gemini 3.6 Flash$0.0026Fits in one request
Mistral Large 3 2512$0.0013Fits in one request

Mistral Large 3 2512 costs less

Repository review

50K input + 3K output tokens

Gemini 3.6 Flash$0.049Fits in one request
Mistral Large 3 2512$0.029Fits in one request

Mistral Large 3 2512 costs less

Agent loop

200K input + 10K output tokens

Gemini 3.6 Flash$0.188Fits in one request
Mistral Large 3 2512$0.115Fits in one request

Mistral Large 3 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 Gemini 3.6 Flash and Mistral Large 3 2512
SpecificationGoogle Gemini 3.6 FlashMistral Large 3 2512
MakerGoogleMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedJuly 21, 2026December 1, 2025
Context window1.05M262K
Input $/Mtok$0.75$0.50
Output $/Mtok$3.75$1.50
Coding index62.5Not benchmarked
Independent measurements behind it41
Cost per solved task$1.49$0.77
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.6 Flash better than Mistral Large 3 2512 for coding?

Only Gemini 3.6 Flash has a coding score, 62.5 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for output tokens 2.5x cheaper ($1.50 vs $3.75 per million) and a lower cost per solved task ($0.77 against $1.49).

Which is cheaper, Gemini 3.6 Flash or Mistral Large 3 2512?

Gemini 3.6 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Mistral Large 3 2512 costs $0.50 and $1.50. Per solved SWE-bench Verified task, Gemini 3.6 Flash costs $1.49 and Mistral Large 3 2512 $0.77.

Which has the bigger context window, Gemini 3.6 Flash or Mistral Large 3 2512?

Gemini 3.6 Flash, with 1.05M tokens against 262K.

How many benchmarks is the Gemini 3.6 Flash vs Mistral Large 3 2512 comparison based on?

23 benchmarks have a result for both models as of October 21, 2026. Gemini 3.6 Flash's coding index rests on 4 independent benchmarks and Mistral Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.

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