Enter opens the highlighted result. Esc closes.

Mercury 2 vs Mistral Medium 3.5

Mistral Medium 3.5 leads Mercury 2 on the Artificial Analysis Intelligence Index, 14.2 to 10.8, and Mercury 2 costs 10.0x less per output token ($0.75 vs $7.50 per million). Updated October 21, 2026; 41 benchmarks have a result for both.

Replace Mercury 2 Replace Mistral Medium 3.5
Mercury 2Inception
Coding
No data
Overall
No data
Output $/M
$0.75
5
Mistral Medium 3.5Mistral AI
Coding
25.5
Overall
37.3
Output $/M
$7.50
36
vs boards won of 41 shared

Mercury 2 or Mistral Medium 3.5: which to pick

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding.

Pick Mercury 2 for output tokens 10.0x cheaper ($0.75 vs $7.50 per million) and work measured by ALE-Bench or GPQA Diamond (Artificial Analysis run), where it leads.

Model AMercury 2InceptionNot benchmarked1 independent benchmarkNo cost per solved taskModel BMistral Medium 3.5Mistral AI25.5/1003 independent benchmarks$6.02 per solved task
Shared results
41
Mercury 2 only
1
Mistral Medium 3.5 only
40
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
Mercury 2 not benchmarked, Mistral Medium 3.5 25.5 from 3 benchmarks.
Widest category
Agentic work, 14.4 points apart on average over 2 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): Mercury 2 43.7% against Mistral Medium 3.5 69.3%, 25.7 points apart on a 0 to 100 scale.
Output price
Mercury 2 $0.75 against Mistral Medium 3.5 $7.50 per million output tokens, 10.0x apart.
Context window
Mercury 2 takes 128K 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
CategoryMercury 2BarsMistral Medium 3.5Ties
Coding18
Intelligence01
Agentic work02
Reasoning23
Knowledge03
Web design17
General112
All shared boards536
CodingLike-for-likeSix of these boards feed the Vibe Coding Index18
Coding benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral Medium 3.5Leader
LMArena WebDev11711264Mistral Medium 3.5
AA Coding Index31.146.9Mistral Medium 3.5
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
SciCode37.7%40.2%Mistral Medium 3.5
Terminal-Bench Hard (Artificial Analysis run)26.5%33.3%Mistral Medium 3.5
WeirdML43.2%Not measuredOnly Mercury 2 measured
ALE-Bench785.6764.0Mercury 2
LMArena Text: coding13901460Mistral Medium 3.5
LMArena Text: software and IT13851458Mistral Medium 3.5
LMArena WebDev: React11601254Mistral Medium 3.5
LMArena WebDev: HTML11991308Mistral Medium 3.5
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral Medium 3.5Leader
AA Intelligence Index10.814.2Mistral Medium 3.5
Epoch Capabilities IndexNot measured141.4Only Mistral Medium 3.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral Medium 3.5Leader
AA Agentic Index1.67.0Mistral Medium 3.5
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 Telecom70.8%94.2%Mistral Medium 3.5
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
Reasoning benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral Medium 3.5Leader
GPQA DiamondNot measured34.9%Only Mistral Medium 3.5 measured
GPQA Diamond (Artificial Analysis run)77.0%74.8%Mercury 2
Humanity's Last Exam (Artificial Analysis run)17.1%13.8%Mercury 2
LMArena Text: hard prompts13621436Mistral Medium 3.5
LMArena Text: expert13581432Mistral Medium 3.5
LMArena Text: hard prompts in English13741445Mistral Medium 3.5
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 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral 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
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index03
Knowledge benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral 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
LMArena Text: science13431428Mistral Medium 3.5
LMArena Text: medicine and healthcare13631409Mistral Medium 3.5
LMArena Text: legal and governmentNot measured1437Only Mistral Medium 3.5 measured
LMArena Text: business and finance13491426Mistral Medium 3.5
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral Medium 3.5Leader
Design Arena: websites10361142Mistral Medium 3.5
Design Arena: UI components9981079Mistral Medium 3.5
Design Arena: game dev9851079Mistral Medium 3.5
Design Arena: data viz10091120Mistral Medium 3.5
Design Arena: 3D9831061Mistral Medium 3.5
Design Arena: all code categories10221121Mistral Medium 3.5
Design Arena: SVG998950Mercury 2
Design Arena: ASCII art9881063Mistral Medium 3.5
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index112
General benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral 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
IFBench69.8%68.8%Mercury 2
Long context reasoning (AA-LCR)43.7%69.3%Mistral Medium 3.5
DTBenchNot measured75.5%Only Mistral Medium 3.5 measured
LMCANot measured26.1%Only Mistral Medium 3.5 measured
Surface Evolver BenchNot measured26.9%Only Mistral Medium 3.5 measured
LMArena Text13541421Mistral Medium 3.5
LMArena Text: instruction following13281415Mistral Medium 3.5
LMArena Text: creative writing12861374Mistral Medium 3.5
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: English13781433Mistral Medium 3.5
LMArena Text: non-English13301404Mistral Medium 3.5
LMArena Text: Chinese14141444Mistral Medium 3.5
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: Russian13041395Mistral Medium 3.5
LMArena Text: PolishNot measured1430Only Mistral Medium 3.5 measured
LMArena Text: multi-turn13571423Mistral Medium 3.5
LMArena Text: longer queries13291415Mistral Medium 3.5
LMArena Text: writing and language13001384Mistral Medium 3.5
LMArena Text: entertainment and media13141382Mistral Medium 3.5
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 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mercury 2 and Mistral Medium 3.5
BenchmarkMercury 2Mistral 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

Mercury 2$0.0006Fits in one request
Mistral Medium 3.5$0.0053Fits in one request

Mercury 2 costs less

Repository review

50K input + 3K output tokens

Mercury 2$0.015Fits in one request
Mistral Medium 3.5$0.098Fits in one request

Mercury 2 costs less

Agent loop

200K input + 10K output tokens

Mercury 2$0.058Exceeds the context window
Mistral Medium 3.5$0.375Fits in one request

Mercury 2 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 Mercury 2 and Mistral Medium 3.5
SpecificationInception Mercury 2Mistral Medium 3.5
MakerInceptionMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedMarch 4, 2026April 30, 2026
Context window128K262K
Input $/Mtok$0.25$1.50
Output $/Mtok$0.75$7.50
Coding indexNot benchmarked25.5
Independent measurements behind it13
Cost per solved taskNot computable$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Mercury 2 better than Mistral Medium 3.5 for coding?

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding. Pick Mercury 2 for output tokens 10.0x cheaper ($0.75 vs $7.50 per million) and work measured by ALE-Bench or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, Mercury 2 or Mistral Medium 3.5?

Mercury 2 costs $0.25 per million input tokens and $0.75 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, Mercury 2 or Mistral Medium 3.5?

Mistral Medium 3.5, with 262K tokens against 128K.

How many benchmarks is the Mercury 2 vs Mistral Medium 3.5 comparison based on?

41 benchmarks have a result for both models as of October 21, 2026. Mercury 2's coding index rests on 1 independent benchmark and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next