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Gemini 2.5 Pro Preview 06-05 vs Mistral Medium 3.5

Mistral Medium 3.5 costs 1.3x less per output token than Gemini 2.5 Pro Preview 06-05 ($7.50 vs $10.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.

Gemini 2.5 Pro Preview 06-05Google
Coding
No data
Overall
No data
Output $/M
$10.00
2
Mistral Medium 3.5Mistral AI
Coding
25.5
Overall
37.3
Output $/M
$7.50
0
vs boards won of 2 shared

Gemini 2.5 Pro Preview 06-05 or Mistral Medium 3.5: which to pick

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding.

Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 262K tokens) and work measured by GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.

Shared results
2
Gemini 2.5 Pro Preview 06-05 only
13
Mistral Medium 3.5 only
79
Like-for-like categories
1 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 Medium 3.5 25.5 from 3 benchmarks.
Widest category
Reasoning, 7.4 points apart on average over 2 shared benchmarks.
Widest single gap
GPQA Diamond (Artificial Analysis run): Gemini 2.5 Pro Preview 06-05 83.6% against Mistral Medium 3.5 74.8%, 8.8 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro Preview 06-05 $10.00 against Mistral Medium 3.5 $7.50 per million output tokens, 1.3x apart.
Context window
Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens, Mistral Medium 3.5 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 2.5 Pro Preview 06-05BarsMistral Medium 3.5Ties
Reasoning20
All shared boards20
CodingDirectional onlySix of these boards feed the Vibe Coding Index18 boards, none shared
Coding benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
Aider polyglot83.1%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LMArena WebDevNot measured1264Only Mistral Medium 3.5 measured
AA Coding IndexNot measured46.9Only Mistral Medium 3.5 measured
LiveCodeBench (Vals AI)79.2%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
SWE-bench Verified (Vals AI)Not measured66.4%Only Mistral Medium 3.5 measured
Vibe Code Bench (Vals AI)Not measured2.9%Only Mistral Medium 3.5 measured
Code migration (Vals AI)Not measured5.1%Only Mistral Medium 3.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured39.0%Only Mistral Medium 3.5 measured
LiveCodeBench (Artificial Analysis run)77.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
SciCodeNot measured40.2%Only Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured33.3%Only Mistral Medium 3.5 measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
ALE-BenchNot measured764.0Only Mistral Medium 3.5 measured
LMArena Text: codingNot measured1460Only Mistral Medium 3.5 measured
LMArena Text: software and ITNot measured1458Only Mistral Medium 3.5 measured
LMArena WebDev: ReactNot measured1254Only Mistral Medium 3.5 measured
LMArena WebDev: HTMLNot measured1308Only Mistral Medium 3.5 measured
SciCode7.7%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 21 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 Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
AA Intelligence IndexNot measured14.2Only Mistral Medium 3.5 measured
Epoch Capabilities IndexNot measured141.4Only Mistral Medium 3.5 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Agentic work benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
AA Agentic IndexNot measured7.0Only Mistral Medium 3.5 measured
Finance Agent (Vals AI)Not measured32.1%Only Mistral Medium 3.5 measured
Tax Agent Bench (Vals AI)Not measured4.5%Only Mistral Medium 3.5 measured
Legal Research Bench (Vals AI)Not measured9.1%Only Mistral Medium 3.5 measured
Excel Modeling Benchmark (Vals AI)Not measured11.2%Only Mistral Medium 3.5 measured
τ²-Bench TelecomNot measured94.2%Only Mistral Medium 3.5 measured
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 32 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 Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
GPQA DiamondNot measured34.9%Only Mistral Medium 3.5 measured
GPQA Diamond (Artificial Analysis run)83.6%74.8%Gemini 2.5 Pro Preview 06-05
Humanity's Last Exam (Artificial Analysis run)19.9%13.8%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 measured1436Only Mistral Medium 3.5 measured
LMArena Text: expertNot measured1432Only Mistral Medium 3.5 measured
LMArena Text: hard prompts in EnglishNot measured1445Only Mistral Medium 3.5 measured
LMArena Vision: diagramsNot measured1254Only Mistral Medium 3.5 measured
LMArena Vision: homeworkNot measured1230Only Mistral Medium 3.5 measured
Kagi LLM BenchmarkNot measured41.4%Only Mistral Medium 3.5 measured
Neither model has a result on the other 10 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
ProofBenchNot measured9.0%Only Mistral Medium 3.5 measured
LMArena Text: mathNot measured1431Only Mistral Medium 3.5 measured
LMArena Text: mathematical workNot measured1440Only Mistral Medium 3.5 measured
Neither model has a result on the other 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Knowledge benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
MMLU ProNot measured75.3%Only Mistral Medium 3.5 measured
CaseLaw (Vals AI)Not measured44.2%Only Mistral Medium 3.5 measured
CorpFin (Vals AI)Not measured58.8%Only Mistral Medium 3.5 measured
TaxEval (Vals AI)Not measured68.0%Only Mistral Medium 3.5 measured
MortgageTax (Vals AI)Not measured28.9%Only Mistral Medium 3.5 measured
MedCode (Vals AI)Not measured33.8%Only Mistral Medium 3.5 measured
MMLU Pro (Artificial Analysis run)85.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LMArena Text: scienceNot measured1428Only Mistral Medium 3.5 measured
LMArena Text: medicine and healthcareNot measured1409Only Mistral Medium 3.5 measured
LMArena Text: legal and governmentNot measured1437Only Mistral Medium 3.5 measured
LMArena Text: business and financeNot measured1426Only Mistral Medium 3.5 measured
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
Design Arena: websitesNot measured1142Only Mistral Medium 3.5 measured
Design Arena: UI componentsNot measured1076Only Mistral Medium 3.5 measured
Design Arena: game devNot measured1079Only Mistral Medium 3.5 measured
Design Arena: data vizNot measured1120Only Mistral Medium 3.5 measured
Design Arena: 3DNot measured1060Only Mistral Medium 3.5 measured
Design Arena: all code categoriesNot measured1121Only Mistral Medium 3.5 measured
Design Arena: SVGNot measured949Only Mistral Medium 3.5 measured
Design Arena: ASCII artNot measured1062Only Mistral Medium 3.5 measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
General benchmarks for Gemini 2.5 Pro Preview 06-05 and Mistral Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
SAGE (Vals AI)Not measured37.6%Only Mistral Medium 3.5 measured
MedScribe (Vals AI)Not measured67.7%Only Mistral Medium 3.5 measured
Vals Multimodal IndexNot measured34.8%Only Mistral Medium 3.5 measured
IFBenchNot measured68.8%Only Mistral Medium 3.5 measured
Long context reasoning (AA-LCR)Not measured69.3%Only Mistral Medium 3.5 measured
DTBenchNot measured75.5%Only Mistral Medium 3.5 measured
LMCANot measured26.1%Only Mistral Medium 3.5 measured
Fiction.LiveBench91.7%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Surface Evolver BenchNot measured26.9%Only Mistral Medium 3.5 measured
LMArena TextNot measured1421Only Mistral Medium 3.5 measured
LMArena Text: instruction followingNot measured1415Only Mistral Medium 3.5 measured
LMArena Text: creative writingNot measured1374Only Mistral Medium 3.5 measured
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: EnglishNot measured1433Only Mistral Medium 3.5 measured
LMArena Text: non-EnglishNot measured1404Only Mistral Medium 3.5 measured
LMArena Text: ChineseNot measured1444Only Mistral Medium 3.5 measured
LMArena Text: GermanNot measured1453Only Mistral Medium 3.5 measured
LMArena Text: KoreanNot measured1384Only Mistral Medium 3.5 measured
LMArena Text: FrenchNot measured1448Only Mistral Medium 3.5 measured
LMArena Text: SpanishNot measured1411Only Mistral Medium 3.5 measured
LMArena Text: RussianNot measured1395Only Mistral Medium 3.5 measured
LMArena Text: PolishNot measured1430Only Mistral Medium 3.5 measured
LMArena Text: multi-turnNot measured1423Only Mistral Medium 3.5 measured
LMArena Text: longer queriesNot measured1415Only Mistral Medium 3.5 measured
LMArena Text: writing and languageNot measured1384Only Mistral Medium 3.5 measured
LMArena Text: entertainment and mediaNot measured1382Only Mistral Medium 3.5 measured
LMArena Vision: EnglishNot measured1240Only Mistral Medium 3.5 measured
LMArena Vision: ChineseNot measured1244Only Mistral Medium 3.5 measured
LMArena Vision: reading textNot measured1233Only Mistral Medium 3.5 measured
LMArena Vision: humorNot measured1216Only Mistral Medium 3.5 measured
LMArena Vision: creative writingNot measured1198Only Mistral Medium 3.5 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 Pro Preview 06-05 and Mistral Medium 3.5
BenchmarkGemini 2.5 Pro Preview 06-05Mistral Medium 3.5Leader
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 Medium 3.5$0.0053Fits in one request

Mistral Medium 3.5 costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro Preview 06-05$0.092Fits in one request
Mistral Medium 3.5$0.098Fits 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 Medium 3.5$0.375Fits in one request

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 Medium 3.5
SpecificationGoogle Gemini 2.5 Pro Preview 06-05Mistral Medium 3.5
MakerGoogleMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedJune 5, 2025April 30, 2026
Context window1.05M262K
Input $/Mtok$1.25$1.50
Output $/Mtok$10.00$7.50
Coding indexNot benchmarked25.5
Independent measurements behind it03
Cost per solved taskNot computable$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro Preview 06-05 better than Mistral Medium 3.5 for coding?

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 262K tokens) and work measured by GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.

Which is cheaper, Gemini 2.5 Pro Preview 06-05 or Mistral Medium 3.5?

Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Cost per solved task is known for Mistral Medium 3.5 only.

Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or Mistral Medium 3.5?

Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 262K.

How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs Mistral Medium 3.5 comparison based on?

2 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 0 independent benchmarks and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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