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Gemini 2.5 Pro Preview 06-05 vs Mistral Large

Mistral Large costs 1.7x less per output token than Gemini 2.5 Pro Preview 06-05 ($6.00 vs $10.00 per million). Updated October 21, 2026; 5 benchmarks have a result for both.

Gemini 2.5 Pro Preview 06-05Google
Coding
No data
Overall
No data
Output $/M
$10.00
5
Mistral LargeMistral AI
Coding
No data
Overall
5.8
Output $/M
$6.00
0
vs boards won of 5 shared

Gemini 2.5 Pro Preview 06-05 or Mistral Large: which to pick

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

Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 128K tokens).

Shared results
5
Gemini 2.5 Pro Preview 06-05 only
9
Mistral Large only
39
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
Gemini 2.5 Pro Preview 06-05 not benchmarked, Mistral Large not benchmarked.
Widest category
Coding, 51.0 points apart on average over 2 shared benchmarks.
Widest single gap
LiveCodeBench (Artificial Analysis run): Gemini 2.5 Pro Preview 06-05 77.8% against Mistral Large 17.8%, 60.0 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro Preview 06-05 $10.00 against Mistral Large $6.00 per million output tokens, 1.7x apart.
Context window
Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens, Mistral Large 128K.

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 Pro Preview 06-05BarsMistral LargeTies
Coding20
Reasoning20
Knowledge10
All shared boards50
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
Aider polyglot83.1%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LiveCodeBench (Vals AI)79.2%37.1%Gemini 2.5 Pro Preview 06-05
LiveCodeBench (Artificial Analysis run)77.8%17.8%Gemini 2.5 Pro Preview 06-05
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LMArena Text: codingNot measured1275Only Mistral Large measured
LMArena Text: software and ITNot measured1274Only Mistral Large measured
Neither model has a result on the other 32 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
AA Intelligence IndexNot measured5.8Only Mistral Large measured
Epoch Capabilities IndexNot measured122.1Only Mistral Large measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
METR time horizons55.4%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Remote Labor Index0.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
DeepResearch Bench42.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
GPQA DiamondNot measured47.7%Only Mistral Large measured
GPQA Diamond (Artificial Analysis run)83.6%35.1%Gemini 2.5 Pro Preview 06-05
Humanity's Last Exam (Artificial Analysis run)19.9%3.5%Gemini 2.5 Pro Preview 06-05
GPQA Diamond (Epoch AI run)84.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
SimpleBench62.4%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
VPCT46.4%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LMArena Text: hard promptsNot measured1257Only Mistral Large measured
LMArena Text: expertNot measured1208Only Mistral Large measured
LMArena Text: hard prompts in EnglishNot measured1268Only Mistral Large measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
AIMENot measured9.2%Only Mistral Large measured
MATH 500 (Vals AI)Not measured74.4%Only Mistral Large measured
MGSM (Vals AI)Not measured87.2%Only Mistral Large measured
LMArena Text: mathNot measured1261Only Mistral Large measured
LMArena Text: mathematical workNot measured1257Only Mistral Large measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
MMLU ProNot measured69.7%Only Mistral Large measured
TaxEval (Vals AI)Not measured63.8%Only Mistral Large measured
MedQA (Vals AI)Not measured76.2%Only Mistral Large measured
MMLU Pro (Artificial Analysis run)85.8%51.5%Gemini 2.5 Pro Preview 06-05
MMLUNot measured68.8%Only Mistral Large measured
LMArena Text: scienceNot measured1260Only Mistral Large measured
LMArena Text: medicine and healthcareNot measured1255Only Mistral Large measured
LMArena Text: legal and governmentNot measured1275Only Mistral Large measured
LMArena Text: business and financeNot measured1238Only Mistral Large measured
Neither model has a result on the other 8 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
General benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
DTBenchNot measured60.8%Only Mistral Large measured
Fiction.LiveBench91.7%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LMArena TextNot measured1265Only Mistral Large measured
LMArena Text: instruction followingNot measured1249Only Mistral Large measured
LMArena Text: creative writingNot measured1242Only Mistral Large measured
LMArena Text: EnglishNot measured1284Only Mistral Large measured
LMArena Text: non-EnglishNot measured1235Only Mistral Large measured
LMArena Text: ChineseNot measured1239Only Mistral Large measured
LMArena Text: GermanNot measured1242Only Mistral Large measured
LMArena Text: JapaneseNot measured1170Only Mistral Large measured
LMArena Text: KoreanNot measured1202Only Mistral Large measured
LMArena Text: FrenchNot measured1325Only Mistral Large measured
LMArena Text: SpanishNot measured1268Only Mistral Large measured
LMArena Text: RussianNot measured1252Only Mistral Large measured
LMArena Text: PolishNot measured1157Only Mistral Large measured
LMArena Text: multi-turnNot measured1260Only Mistral Large measured
LMArena Text: longer queriesNot measured1261Only Mistral Large measured
LMArena Text: writing and languageNot measured1261Only Mistral Large measured
LMArena Text: entertainment and mediaNot measured1230Only Mistral Large 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 Gemini 2.5 Pro Preview 06-05 and Mistral Large
BenchmarkGemini 2.5 Pro Preview 06-05Mistral LargeLeader
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 Pro Preview 06-05$0.0063Fits in one request
Mistral Large$0.0050Fits in one request

Mistral Large costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro Preview 06-05$0.092Fits in one request
Mistral Large$0.118Fits in one request

Gemini 2.5 Pro Preview 06-05 costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro Preview 06-05$0.350Fits in one request
Mistral Large$0.460Exceeds the context window

Gemini 2.5 Pro Preview 06-05 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 Pro Preview 06-05 and Mistral Large
SpecificationGoogle Gemini 2.5 Pro Preview 06-05Mistral Large
MakerGoogleMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedJune 5, 2025February 26, 2024
Context window1.05M128K
Input $/Mtok$1.25$2.00
Output $/Mtok$10.00$6.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro Preview 06-05 better than Mistral Large for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 128K tokens).

Which is cheaper, Gemini 2.5 Pro Preview 06-05 or Mistral Large?

Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or Mistral Large?

Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 128K.

How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs Mistral Large comparison based on?

5 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 0 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.

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