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Gemini 2.5 Flash Lite vs Mistral Medium 3.1

Gemini 2.5 Flash Lite leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 10.4 to 9.2, and Gemini 2.5 Flash Lite costs 5.0x less per output token ($0.40 vs $2.00 per million). Updated October 22, 2026; 23 benchmarks have a result for both.

Gemini 2.5 Flash LiteGoogle
Coding
No data
Overall
No data
Output $/M
$0.40
16
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
7
vs boards won of 23 shared

Gemini 2.5 Flash Lite or Mistral Medium 3.1: which to pick

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

Pick Gemini 2.5 Flash Lite for output tokens 5.0x cheaper ($0.40 vs $2.00 per million) and a larger context window (1.05M against 131K tokens).

Shared results
23
Gemini 2.5 Flash Lite only
7
Mistral Medium 3.1 only
51
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 2.5 Flash Lite not benchmarked, Mistral Medium 3.1 not benchmarked.
Widest category
Agentic work, 21.6 points apart on average over 1 shared benchmark.
Widest single gap
LiveCodeBench (Vals AI): Gemini 2.5 Flash Lite 71.4% against Mistral Medium 3.1 44.8%, 26.5 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash Lite $0.40 against Mistral Medium 3.1 $2.00 per million output tokens, 5.0x apart.
Context window
Gemini 2.5 Flash Lite takes 1.05M tokens, Mistral Medium 3.1 131K.

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 2.5 Flash LiteBarsMistral Medium 3.1Ties
Coding21
Intelligence10
Agentic work01
Reasoning30
Math22
Knowledge61
General22
All shared boards167
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
Coding benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
AA Coding IndexNot measured20.5Only Mistral Medium 3.1 measured
LiveCodeBench (Vals AI)71.4%44.8%Gemini 2.5 Flash Lite
LiveCodeBench (Artificial Analysis run)59.3%40.6%Gemini 2.5 Flash Lite
SciCodeNot measured32.4%Only Mistral Medium 3.1 measured
Terminal-Bench Hard (Artificial Analysis run)4.5%10.6%Mistral Medium 3.1
ALE-BenchNot measured210.2Only Mistral Medium 3.1 measured
LMArena Text: codingNot measured1433Only Mistral Medium 3.1 measured
LMArena Text: software and ITNot measured1436Only Mistral Medium 3.1 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 Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
AA Intelligence Index10.49.2Gemini 2.5 Flash Lite
Epoch Capabilities Index133.8Not measuredOnly Gemini 2.5 Flash Lite measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
AA Agentic IndexNot measured1.9Only Mistral Medium 3.1 measured
τ²-Bench Telecom19.0%40.6%Mistral Medium 3.1
Berkeley Function Calling Leaderboard (BFCL)36.9%Not measuredOnly Gemini 2.5 Flash Lite measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
GPQA Diamond70.2%Not measuredOnly Gemini 2.5 Flash Lite measured
MMMU Pro (Vals AI)75.4%63.0%Gemini 2.5 Flash Lite
GPQA Diamond (Artificial Analysis run)62.5%58.8%Gemini 2.5 Flash Lite
Humanity's Last Exam (Artificial Analysis run)6.8%4.7%Gemini 2.5 Flash Lite
LMArena Text: hard promptsNot measured1426Only Mistral Medium 3.1 measured
LMArena Text: expertNot measured1408Only Mistral Medium 3.1 measured
LMArena Text: hard prompts in EnglishNot measured1435Only Mistral Medium 3.1 measured
LMArena Vision: diagramsNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: homeworkNot measured1165Only Mistral Medium 3.1 measured
Kagi LLM Benchmark40.5%Not measuredOnly Gemini 2.5 Flash Lite measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index22
Math benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
AIME42.1%42.3%Mistral Medium 3.1
MATH 500 (Vals AI)Not measured87.0%Only Mistral Medium 3.1 measured
MGSM (Vals AI)89.5%90.9%Mistral Medium 3.1
AA Math Index53.338.3Gemini 2.5 Flash Lite
AIME 2025 (Artificial Analysis run)53.3%38.3%Gemini 2.5 Flash Lite
LMArena Text: mathNot measured1408Only Mistral Medium 3.1 measured
LMArena Text: mathematical workNot measured1412Only Mistral Medium 3.1 measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
Knowledge benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
MMLU Pro79.1%75.3%Gemini 2.5 Flash Lite
LegalBench (Vals AI)82.0%62.0%Gemini 2.5 Flash Lite
CorpFin (Vals AI)57.6%50.7%Gemini 2.5 Flash Lite
TaxEval (Vals AI)66.2%70.3%Mistral Medium 3.1
MortgageTax (Vals AI)57.6%36.5%Gemini 2.5 Flash Lite
MedQA (Vals AI)88.9%78.2%Gemini 2.5 Flash Lite
MedCode (Vals AI)34.2%Not measuredOnly Gemini 2.5 Flash Lite measured
MMLU Pro (Artificial Analysis run)75.9%68.3%Gemini 2.5 Flash Lite
LMArena Text: scienceNot measured1444Only Mistral Medium 3.1 measured
LMArena Text: medicine and healthcareNot measured1449Only Mistral Medium 3.1 measured
LMArena Text: legal and governmentNot measured1439Only Mistral Medium 3.1 measured
LMArena Text: business and financeNot measured1418Only Mistral Medium 3.1 measured
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
Design Arena: websitesNot measured1132Only Mistral Medium 3.1 measured
Design Arena: UI componentsNot measured1097Only Mistral Medium 3.1 measured
Design Arena: game devNot measured1073Only Mistral Medium 3.1 measured
Design Arena: data vizNot measured1144Only Mistral Medium 3.1 measured
Design Arena: 3DNot measured1081Only Mistral Medium 3.1 measured
Design Arena: all code categoriesNot measured1120Only Mistral Medium 3.1 measured
Design Arena: SVGNot measured992Only Mistral Medium 3.1 measured
Design Arena: ASCII artNot measured997Only Mistral Medium 3.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index22
General benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
SAGE (Vals AI)30.8%Not measuredOnly Gemini 2.5 Flash Lite measured
MedScribe (Vals AI)75.8%Not measuredOnly Gemini 2.5 Flash Lite measured
IFBench49.9%39.8%Gemini 2.5 Flash Lite
Long context reasoning (AA-LCR)55.7%42.7%Gemini 2.5 Flash Lite
DTBench62.8%67.5%Mistral Medium 3.1
LMCA18.1%19.1%Mistral Medium 3.1
LMArena TextNot measured1424Only Mistral Medium 3.1 measured
LMArena Text: instruction followingNot measured1398Only Mistral Medium 3.1 measured
LMArena Text: creative writingNot measured1391Only Mistral Medium 3.1 measured
LMArena VisionNot measured1172Only Mistral Medium 3.1 measured
LMArena Text: EnglishNot measured1438Only Mistral Medium 3.1 measured
LMArena Text: non-EnglishNot measured1408Only Mistral Medium 3.1 measured
LMArena Text: ChineseNot measured1447Only Mistral Medium 3.1 measured
LMArena Text: GermanNot measured1432Only Mistral Medium 3.1 measured
LMArena Text: JapaneseNot measured1379Only Mistral Medium 3.1 measured
LMArena Text: KoreanNot measured1380Only Mistral Medium 3.1 measured
LMArena Text: FrenchNot measured1460Only Mistral Medium 3.1 measured
LMArena Text: SpanishNot measured1433Only Mistral Medium 3.1 measured
LMArena Text: RussianNot measured1411Only Mistral Medium 3.1 measured
LMArena Text: PolishNot measured1430Only Mistral Medium 3.1 measured
LMArena Text: multi-turnNot measured1418Only Mistral Medium 3.1 measured
LMArena Text: longer queriesNot measured1406Only Mistral Medium 3.1 measured
LMArena Text: writing and languageNot measured1395Only Mistral Medium 3.1 measured
LMArena Text: entertainment and mediaNot measured1390Only Mistral Medium 3.1 measured
LMArena Vision: EnglishNot measured1179Only Mistral Medium 3.1 measured
LMArena Vision: ChineseNot measured1190Only Mistral Medium 3.1 measured
LMArena Vision: reading textNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: humorNot measured1168Only Mistral Medium 3.1 measured
LMArena Vision: captioningNot measured1145Only Mistral Medium 3.1 measured
LMArena Vision: recognizing thingsNot measured1147Only Mistral Medium 3.1 measured
LMArena Vision: creative writingNot measured1200Only Mistral Medium 3.1 measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Flash Lite and Mistral Medium 3.1
BenchmarkGemini 2.5 Flash LiteMistral Medium 3.1Leader
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 2.5 Flash Lite$0.0003Fits in one request
Mistral Medium 3.1$0.0014Fits in one request

Gemini 2.5 Flash Lite costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash Lite$0.0062Fits in one request
Mistral Medium 3.1$0.026Fits in one request

Gemini 2.5 Flash Lite costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash Lite$0.024Fits in one request
Mistral Medium 3.1$0.100Exceeds the context window

Gemini 2.5 Flash Lite 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 2.5 Flash Lite and Mistral Medium 3.1
SpecificationGoogle Gemini 2.5 Flash LiteMistral Medium 3.1
MakerGoogleMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedJuly 22, 2025August 13, 2025
Context window1.05M131K
Input $/Mtok$0.10$0.40
Output $/Mtok$0.40$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash Lite better than Mistral Medium 3.1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash Lite for output tokens 5.0x cheaper ($0.40 vs $2.00 per million) and a larger context window (1.05M against 131K tokens).

Which is cheaper, Gemini 2.5 Flash Lite or Mistral Medium 3.1?

Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; Mistral Medium 3.1 costs $0.40 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemini 2.5 Flash Lite or Mistral Medium 3.1?

Gemini 2.5 Flash Lite, with 1.05M tokens against 131K.

How many benchmarks is the Gemini 2.5 Flash Lite vs Mistral Medium 3.1 comparison based on?

23 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Flash Lite's coding index rests on 0 independent benchmarks and Mistral Medium 3.1's on 0. Where only one model has a result, the page says so instead of naming a winner.

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