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Devstral 2 2512 vs GPT-5 Mini

Updated October 21, 2026. 4 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Devstral 2 2512Mistral AI
Coding
53.8
Overall
8.6
Output $/M
$2.00
1
GPT-5 MiniOpenAI
Coding
59.8
Overall
20.6
Output $/M
$2.00
3
vs boards won of 4 shared

Decision reading

Pick GPT-5 Mini for coding: it scores 59.8 on the Vibe Coding Index against 53.8 for Devstral 2 2512.

Pick Devstral 2 2512 when the benchmark that matters is SWE-bench Verified (Vals AI), where it leads.

Shared results
4
Devstral 2 2512 only
2
GPT-5 Mini only
94
Like-for-like categories
2 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
Devstral 2 2512 53.8 from 1 benchmark, GPT-5 Mini 59.8 from 1 benchmark.
Widest category
Coding, 14.3 points apart on average over 3 shared benchmarks.
Widest single gap
LiveCodeBench (Vals AI): Devstral 2 2512 51.8% against GPT-5 Mini 86.6%, 34.8 points apart on a 0 to 100 scale.
Output price
Both cost $2.00 per million output tokens.
Context window
Devstral 2 2512 takes 262K tokens, GPT-5 Mini 400K.

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
CategoryDevstral 2 2512BarsGPT-5 MiniTies
Coding12
Intelligence01
All shared boards13
CodingLike-for-likeFour of these boards feed the Vibe Coding Index12
Coding benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
SWE-bench Verified53.8%59.8%GPT-5 Mini
SWE-bench MultilingualNot measured39.7%Only GPT-5 Mini measured
AA Coding Index31.3Not measuredOnly Devstral 2 2512 measured
LiveCodeBench (Vals AI)51.8%86.6%GPT-5 Mini
SWE-bench Verified (Vals AI)62.8%60.8%Devstral 2 2512
Vibe Code Bench (Vals AI)Not measured14.2%Only GPT-5 Mini measured
LiveCodeBench (Artificial Analysis run)Not measured83.8%Only GPT-5 Mini measured
SciCodeNot measured39.0%Only GPT-5 Mini measured
Terminal-Bench Hard (Artificial Analysis run)Not measured33.3%Only GPT-5 Mini measured
Terminal-BenchNot measured34.8%Only GPT-5 Mini measured
WeirdMLNot measured52.7%Only GPT-5 Mini measured
LMArena Text: codingNot measured1406Only GPT-5 Mini measured
LMArena Text: software and ITNot measured1394Only GPT-5 Mini measured
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 Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
AA Intelligence Index8.620.6GPT-5 Mini
Epoch Capabilities IndexNot measured145.3Only GPT-5 Mini measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
AA Agentic Index2.3Not measuredOnly Devstral 2 2512 measured
τ²-Bench TelecomNot measured71.1%Only GPT-5 Mini measured
Vending-Bench 2Not measured-$31Only GPT-5 Mini measured
Neither model has a result on the other 36 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
Reasoning benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
GPQA DiamondNot measured80.3%Only GPT-5 Mini measured
MMMU Pro (Vals AI)Not measured78.9%Only GPT-5 Mini measured
GPQA Diamond (Artificial Analysis run)Not measured82.8%Only GPT-5 Mini measured
Humanity's Last Exam (Artificial Analysis run)Not measured21.5%Only GPT-5 Mini measured
GPQA Diamond (Epoch AI run)Not measured75.0%Only GPT-5 Mini measured
ARC-AGINot measured54.3%Only GPT-5 Mini measured
ARC-AGI-2Not measured4.4%Only GPT-5 Mini measured
Chess puzzlesNot measured24.0%Only GPT-5 Mini measured
Mystery game puzzlesNot measured10.0%Only GPT-5 Mini measured
VPCTNot measured40.2%Only GPT-5 Mini measured
LMArena Text: hard promptsNot measured1380Only GPT-5 Mini measured
LMArena Text: expertNot measured1379Only GPT-5 Mini measured
LMArena Text: hard prompts in EnglishNot measured1383Only GPT-5 Mini measured
LMArena Vision: diagramsNot measured1202Only GPT-5 Mini measured
LMArena Vision: homeworkNot measured1210Only GPT-5 Mini measured
Neither model has a result on the other 6 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Math benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
AIMENot measured91.5%Only GPT-5 Mini measured
MATH 500 (Vals AI)Not measured94.8%Only GPT-5 Mini measured
MGSM (Vals AI)Not measured92.6%Only GPT-5 Mini measured
AA Math IndexNot measured90.7Only GPT-5 Mini measured
AIME 2025 (Artificial Analysis run)Not measured90.7%Only GPT-5 Mini measured
OTIS Mock AIMENot measured86.7%Only GPT-5 Mini measured
FrontierMath, tiers 1 to 3Not measured46.7%Only GPT-5 Mini measured
FrontierMath, tier 4Not measured12.2%Only GPT-5 Mini measured
ProofBenchNot measured9.0%Only GPT-5 Mini measured
MATH level 5Not measured97.8%Only GPT-5 Mini measured
LMArena Text: mathNot measured1378Only GPT-5 Mini measured
LMArena Text: mathematical workNot measured1380Only GPT-5 Mini measured
Neither model has a result on the other 1 board here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
Knowledge benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
MMLU ProNot measured82.2%Only GPT-5 Mini measured
LegalBench (Vals AI)Not measured81.8%Only GPT-5 Mini measured
CaseLaw (Vals AI)Not measured68.5%Only GPT-5 Mini measured
CorpFin (Vals AI)Not measured60.2%Only GPT-5 Mini measured
TaxEval (Vals AI)Not measured75.2%Only GPT-5 Mini measured
MortgageTax (Vals AI)Not measured66.9%Only GPT-5 Mini measured
MedQA (Vals AI)Not measured96.1%Only GPT-5 Mini measured
MedCode (Vals AI)Not measured43.0%Only GPT-5 Mini measured
MMLU Pro (Artificial Analysis run)Not measured83.7%Only GPT-5 Mini measured
SimpleQA VerifiedNot measured21.6%Only GPT-5 Mini measured
LMArena Text: scienceNot measured1371Only GPT-5 Mini measured
LMArena Text: medicine and healthcareNot measured1380Only GPT-5 Mini measured
LMArena Text: legal and governmentNot measured1375Only GPT-5 Mini measured
LMArena Text: business and financeNot measured1358Only GPT-5 Mini measured
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
Design Arena: websitesNot measured1125Only GPT-5 Mini measured
Design Arena: UI componentsNot measured1106Only GPT-5 Mini measured
Design Arena: game devNot measured1130Only GPT-5 Mini measured
Design Arena: data vizNot measured1131Only GPT-5 Mini measured
Design Arena: 3DNot measured1037Only GPT-5 Mini measured
Design Arena: all code categoriesNot measured1115Only GPT-5 Mini measured
Design Arena: SVGNot measured1091Only GPT-5 Mini measured
Design Arena: ASCII artNot measured1124Only GPT-5 Mini measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index33 boards, none shared
General benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
SAGE (Vals AI)Not measured43.0%Only GPT-5 Mini measured
MedScribe (Vals AI)Not measured80.6%Only GPT-5 Mini measured
IFBenchNot measured75.4%Only GPT-5 Mini measured
Long context reasoning (AA-LCR)Not measured72.3%Only GPT-5 Mini measured
DTBenchNot measured80.5%Only GPT-5 Mini measured
LMCANot measured34.2%Only GPT-5 Mini measured
Fiction.LiveBenchNot measured69.4%Only GPT-5 Mini measured
Creative writing (Lech Mazur)Not measured83.1%Only GPT-5 Mini measured
LMArena TextNot measured1373Only GPT-5 Mini measured
LMArena Text: instruction followingNot measured1357Only GPT-5 Mini measured
LMArena Text: creative writingNot measured1325Only GPT-5 Mini measured
LMArena VisionNot measured1202Only GPT-5 Mini measured
LMArena Text: EnglishNot measured1379Only GPT-5 Mini measured
LMArena Text: non-EnglishNot measured1363Only GPT-5 Mini measured
LMArena Text: ChineseNot measured1386Only GPT-5 Mini measured
LMArena Text: GermanNot measured1366Only GPT-5 Mini measured
LMArena Text: JapaneseNot measured1341Only GPT-5 Mini measured
LMArena Text: KoreanNot measured1308Only GPT-5 Mini measured
LMArena Text: FrenchNot measured1386Only GPT-5 Mini measured
LMArena Text: SpanishNot measured1354Only GPT-5 Mini measured
LMArena Text: RussianNot measured1362Only GPT-5 Mini measured
LMArena Text: PolishNot measured1378Only GPT-5 Mini measured
LMArena Text: multi-turnNot measured1363Only GPT-5 Mini measured
LMArena Text: longer queriesNot measured1355Only GPT-5 Mini measured
LMArena Text: writing and languageNot measured1344Only GPT-5 Mini measured
LMArena Text: entertainment and mediaNot measured1340Only GPT-5 Mini measured
LMArena Vision: EnglishNot measured1216Only GPT-5 Mini measured
LMArena Vision: ChineseNot measured1214Only GPT-5 Mini measured
LMArena Vision: reading textNot measured1199Only GPT-5 Mini measured
LMArena Vision: humorNot measured1205Only GPT-5 Mini measured
LMArena Vision: captioningNot measured1217Only GPT-5 Mini measured
LMArena Vision: recognizing thingsNot measured1226Only GPT-5 Mini measured
LMArena Vision: creative writingNot measured1181Only GPT-5 Mini measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Devstral 2 2512 and GPT-5 Mini
BenchmarkDevstral 2 2512GPT-5 MiniLeader
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

Devstral 2 2512$0.0014Fits in one request
GPT-5 Mini$0.0013Fits in one request

GPT-5 Mini costs less

Repository review

50K input + 3K output tokens

Devstral 2 2512$0.026Fits in one request
GPT-5 Mini$0.018Fits in one request

GPT-5 Mini costs less

Agent loop

200K input + 10K output tokens

Devstral 2 2512$0.100Fits in one request
GPT-5 Mini$0.070Fits in one request

GPT-5 Mini 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 Devstral 2 2512 and GPT-5 Mini
SpecificationMistral Devstral 2 2512OpenAI GPT-5 Mini
MakerMistral AIOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 9, 2025August 7, 2025
Context window262K400K
Input $/Mtok$0.40$0.25
Output $/Mtok$2.00$2.00
Coding index53.859.8
Independent measurements behind it11
Cost per solved task$1.19$0.08
SourceOpenRouter listingOpenRouter listing

Questions

Is Devstral 2 2512 better than GPT-5 Mini for coding?

Pick GPT-5 Mini for coding: it scores 59.8 on the Vibe Coding Index against 53.8 for Devstral 2 2512. Pick Devstral 2 2512 when the benchmark that matters is SWE-bench Verified (Vals AI), where it leads.

Which is cheaper, Devstral 2 2512 or GPT-5 Mini?

Devstral 2 2512 costs $0.40 per million input tokens and $2.00 per million output tokens; GPT-5 Mini costs $0.25 and $2.00. Per solved SWE-bench Verified task, Devstral 2 2512 costs $1.19 and GPT-5 Mini $0.08.

Which has the bigger context window, Devstral 2 2512 or GPT-5 Mini?

GPT-5 Mini, with 400K tokens against 262K.

How many benchmarks is the Devstral 2 2512 vs GPT-5 Mini comparison based on?

4 benchmarks have a result for both models as of October 21, 2026. Devstral 2 2512's coding index rests on 1 independent benchmark and GPT-5 Mini's on 1. Where only one model has a result, the page says so instead of naming a winner.

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