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DeepSeek V4 Flash 0731 vs MiniMax M2.7

DeepSeek V4 Flash 0731 leads MiniMax M2.7 on coding, 51.8 to 36.2 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 4.3x less per output token ($0.28 vs $1.20 per million). Updated October 22, 2026; 36 benchmarks have a result for both.

DeepSeek V4 Flash 0731DeepSeek
Coding
51.8
Overall
55.2
Output $/M
$0.28
29
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
6
vs boards won of 36 shared, 1 tied

DeepSeek V4 Flash 0731 or MiniMax M2.7: which to pick

Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 36.2 for MiniMax M2.7.

Pick MiniMax M2.7 for work measured by LegalBench (Vals AI) or Design Arena: websites, where it leads.

Shared results
36
DeepSeek V4 Flash 0731 only
19
MiniMax M2.7 only
38
Like-for-like categories
8 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
DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Math, 53.0 points apart on average over 1 shared benchmark.
Widest single gap
Vibe Code Bench (Vals AI): DeepSeek V4 Flash 0731 74.7% against MiniMax M2.7 11.9%, 62.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0731 $0.28 against MiniMax M2.7 $1.20 per million output tokens, 4.3x apart.
Context window
DeepSeek V4 Flash 0731 takes 1.05M tokens, MiniMax M2.7 205K.

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
CategoryDeepSeek V4 Flash 0731BarsMiniMax M2.7Ties
Coding901 tie
Intelligence20
Agentic work50
Reasoning30
Math10
Knowledge41
Web design35
General20
All shared boards2961 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index90
Coding benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
LMArena WebDevNot measured1399Only MiniMax M2.7 measured
AA Coding Index69.152.6DeepSeek V4 Flash 0731
LiveCodeBench (Vals AI)87.3%79.9%DeepSeek V4 Flash 0731
SWE-bench Verified (Vals AI)88.8%73.8%DeepSeek V4 Flash 0731
Terminal-Bench 4 (Vals AI)18.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Vibe Code Bench (Vals AI)74.7%11.9%DeepSeek V4 Flash 0731
Code migration (Vals AI)38.6%8.7%DeepSeek V4 Flash 0731
ProgramBench (Vals AI)0.0%0.0%Tie
IOI (Vals AI)32.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench 2.1 (Vals AI)67.0%48.7%DeepSeek V4 Flash 0731
SkillsBench (Vals AI)50.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
CyberBench (Vals AI)72.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
SciCode50.3%50.1%DeepSeek V4 Flash 0731
Terminal-Bench Hard (Artificial Analysis run)Not measured39.4%Only MiniMax M2.7 measured
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
FrontierCode18.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
WeirdML63.0%37.0%DeepSeek V4 Flash 0731
ALE-Bench1306.1599.3DeepSeek V4 Flash 0731
LMArena Text: codingNot measured1454Only MiniMax M2.7 measured
LMArena Text: software and ITNot measured1446Only MiniMax M2.7 measured
LMArena WebDev: ReactNot measured1388Only MiniMax M2.7 measured
LMArena WebDev: HTMLNot measured1401Only MiniMax M2.7 measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
AA Intelligence Index34.322.8DeepSeek V4 Flash 0731
Epoch Capabilities Index154.8145.8DeepSeek V4 Flash 0731
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
Agentic work benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
AA Agentic Index41.015.3DeepSeek V4 Flash 0731
Finance Agent (Vals AI)49.5%27.9%DeepSeek V4 Flash 0731
Tax Agent Bench (Vals AI)28.1%6.9%DeepSeek V4 Flash 0731
Legal Research Bench (Vals AI)30.3%10.6%DeepSeek V4 Flash 0731
Excel Modeling Benchmark (Vals AI)57.0%28.4%DeepSeek V4 Flash 0731
BioMysteryBench (Vals AI)64.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
τ²-Bench TelecomNot measured84.8%Only MiniMax M2.7 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
GPQA Diamond89.9%86.6%DeepSeek V4 Flash 0731
GPQA Diamond (Artificial Analysis run)90.8%87.4%DeepSeek V4 Flash 0731
Humanity's Last Exam (Artificial Analysis run)38.6%29.6%DeepSeek V4 Flash 0731
GPQA Diamond (Epoch AI run)91.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI89.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI-261.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
SimpleBench61.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
Chess puzzles32.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
Mystery game puzzles34.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: hard promptsNot measured1422Only MiniMax M2.7 measured
LMArena Text: expertNot measured1443Only MiniMax M2.7 measured
LMArena Text: hard prompts in EnglishNot measured1441Only MiniMax M2.7 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
OTIS Mock AIME94.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tiers 1 to 357.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tier 424.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProofBench56.0%3.0%DeepSeek V4 Flash 0731
LMArena Text: mathNot measured1421Only MiniMax M2.7 measured
LMArena Text: mathematical workNot measured1437Only MiniMax M2.7 measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
MMLU Pro86.2%80.4%DeepSeek V4 Flash 0731
LegalBench (Vals AI)77.7%84.0%MiniMax M2.7
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)61.9%61.2%DeepSeek V4 Flash 0731
TaxEval (Vals AI)70.7%66.6%DeepSeek V4 Flash 0731
MedCode (Vals AI)41.4%34.4%DeepSeek V4 Flash 0731
SimpleQA Verified33.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: scienceNot measured1416Only MiniMax M2.7 measured
LMArena Text: medicine and healthcareNot measured1409Only MiniMax M2.7 measured
LMArena Text: legal and governmentNot measured1403Only MiniMax M2.7 measured
LMArena Text: business and financeNot measured1407Only MiniMax M2.7 measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index35
Web design benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
Design Arena: websites12371242MiniMax M2.7
Design Arena: UI components12331207DeepSeek V4 Flash 0731
Design Arena: game dev12071209MiniMax M2.7
Design Arena: data viz11801233MiniMax M2.7
Design Arena: 3D12081194DeepSeek V4 Flash 0731
Design Arena: all code categories12291233MiniMax M2.7
Design Arena: SVG11831137DeepSeek V4 Flash 0731
Design Arena: ASCII art10901136MiniMax M2.7
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
MedScribe (Vals AI)80.4%79.9%DeepSeek V4 Flash 0731
IFBenchNot measured75.7%Only MiniMax M2.7 measured
Long context reasoning (AA-LCR)79.7%78.3%DeepSeek V4 Flash 0731
DTBench90.9%Not measuredOnly DeepSeek V4 Flash 0731 measured
LMCA41.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena TextNot measured1405Only MiniMax M2.7 measured
LMArena Text: instruction followingNot measured1405Only MiniMax M2.7 measured
LMArena Text: creative writingNot measured1354Only MiniMax M2.7 measured
LMArena Text: EnglishNot measured1426Only MiniMax M2.7 measured
LMArena Text: non-EnglishNot measured1382Only MiniMax M2.7 measured
LMArena Text: ChineseNot measured1442Only MiniMax M2.7 measured
LMArena Text: GermanNot measured1398Only MiniMax M2.7 measured
LMArena Text: JapaneseNot measured1260Only MiniMax M2.7 measured
LMArena Text: KoreanNot measured1314Only MiniMax M2.7 measured
LMArena Text: FrenchNot measured1424Only MiniMax M2.7 measured
LMArena Text: SpanishNot measured1402Only MiniMax M2.7 measured
LMArena Text: RussianNot measured1383Only MiniMax M2.7 measured
LMArena Text: PolishNot measured1387Only MiniMax M2.7 measured
LMArena Text: multi-turnNot measured1412Only MiniMax M2.7 measured
LMArena Text: longer queriesNot measured1418Only MiniMax M2.7 measured
LMArena Text: writing and languageNot measured1376Only MiniMax M2.7 measured
LMArena Text: entertainment and mediaNot measured1360Only MiniMax M2.7 measured
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0731 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0731MiniMax M2.7Leader
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

DeepSeek V4 Flash 0731$0.0003Fits in one request
MiniMax M2.7$0.0009Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0078Fits in one request
MiniMax M2.7$0.019Fits in one request

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.031Fits in one request
MiniMax M2.7$0.072Exceeds the context window

DeepSeek V4 Flash 0731 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 DeepSeek V4 Flash 0731 and MiniMax M2.7
SpecificationDeepSeek V4 Flash 0731MiniMax M2.7
MakerDeepSeekMiniMax
WeightsOpen weightsOpen weights
ReleasedJuly 31, 2026March 18, 2026
Context window1.05M205K
Input $/Mtok$0.14$0.30
Output $/Mtok$0.28$1.20
Coding index51.836.2
Independent measurements behind it43
Cost per solved task$0.01$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than MiniMax M2.7 for coding?

Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 36.2 for MiniMax M2.7. Pick MiniMax M2.7 for work measured by LegalBench (Vals AI) or Design Arena: websites, where it leads.

Which is cheaper, DeepSeek V4 Flash 0731 or MiniMax M2.7?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and MiniMax M2.7 $0.64.

Which has the bigger context window, DeepSeek V4 Flash 0731 or MiniMax M2.7?

DeepSeek V4 Flash 0731, with 1.05M tokens against 205K.

How many benchmarks is the DeepSeek V4 Flash 0731 vs MiniMax M2.7 comparison based on?

36 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and MiniMax M2.7's on 3. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/deepseek-v4-flash-0731-vs-minimax-minimax-m2-7">LLMBenchmark.ai, DeepSeek V4 Flash 0731 vs MiniMax M2.7</a></p>