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DeepSeek V4 Flash 0423 vs MiniMax M2.7

DeepSeek V4 Flash 0423 leads MiniMax M2.7 on the Artificial Analysis Intelligence Index, 24.4 to 22.8, and DeepSeek V4 Flash 0423 costs 4.3x less per output token ($0.28 vs $1.20 per million). Updated October 22, 2026; 45 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace MiniMax M2.7
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
35
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
10
vs boards won of 45 shared

DeepSeek V4 Flash 0423 or MiniMax M2.7: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding.

Pick DeepSeek V4 Flash 0423 for output tokens 4.3x cheaper ($0.28 vs $1.20 per million) and a larger context window (1.05M against 205K tokens).

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
45
DeepSeek V4 Flash 0423 only
4
MiniMax M2.7 only
29
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 0423 not benchmarked, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Coding, 12.4 points apart on average over 8 shared benchmarks.
Widest single gap
LMArena WebDev: React: DeepSeek V4 Flash 0423 1585 against MiniMax M2.7 1388, 32.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against MiniMax M2.7 $1.20 per million output tokens, 4.3x apart.
Context window
DeepSeek V4 Flash 0423 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 0423BarsMiniMax M2.7Ties
Coding71
Intelligence20
Agentic work10
Reasoning21
Math11
Knowledge40
Web design17
General170
All shared boards3510
CodingLike-for-likeSix of these boards feed the Vibe Coding Index71
Coding benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
LMArena WebDev15821399DeepSeek V4 Flash 0423
AA Coding Index52.052.6MiniMax M2.7
LiveCodeBench (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
Vibe Code Bench (Vals AI)Not measured11.9%Only MiniMax M2.7 measured
Code migration (Vals AI)Not measured8.7%Only MiniMax M2.7 measured
ProgramBench (Vals AI)Not measured0.0%Only MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)Not measured48.7%Only MiniMax M2.7 measured
SciCodeNot measured50.1%Only MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured39.4%Only MiniMax M2.7 measured
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdML45.6%37.0%DeepSeek V4 Flash 0423
ALE-Bench678.2599.3DeepSeek V4 Flash 0423
LMArena Text: coding14571454DeepSeek V4 Flash 0423
LMArena Text: software and IT14531446DeepSeek V4 Flash 0423
LMArena WebDev: React15851388DeepSeek V4 Flash 0423
LMArena WebDev: HTML15581401DeepSeek V4 Flash 0423
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
AA Intelligence Index24.422.8DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1145.8DeepSeek V4 Flash 0423
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
AA Agentic Index26.315.3DeepSeek V4 Flash 0423
Finance Agent (Vals AI)Not measured27.9%Only MiniMax M2.7 measured
Tax Agent Bench (Vals AI)Not measured6.9%Only MiniMax M2.7 measured
Legal Research Bench (Vals AI)Not measured10.6%Only MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)Not measured28.4%Only MiniMax M2.7 measured
τ²-Bench TelecomNot measured84.8%Only MiniMax M2.7 measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
Reasoning benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)Not measured87.4%Only MiniMax M2.7 measured
Humanity's Last Exam (Artificial Analysis run)Not measured29.6%Only MiniMax M2.7 measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441422DeepSeek V4 Flash 0423
LMArena Text: expert14411443MiniMax M2.7
LMArena Text: hard prompts in English14491441DeepSeek V4 Flash 0423
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index11
Math benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
LMArena Text: math14261421DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321437MiniMax M2.7
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
MMLU ProNot measured80.4%Only MiniMax M2.7 measured
LegalBench (Vals AI)Not measured84.0%Only MiniMax M2.7 measured
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)Not measured61.2%Only MiniMax M2.7 measured
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 measured
LMArena Text: science14461416DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481409DeepSeek V4 Flash 0423
LMArena Text: legal and government14391403DeepSeek V4 Flash 0423
LMArena Text: business and finance14251407DeepSeek V4 Flash 0423
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 DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
Design Arena: websites12071243MiniMax M2.7
Design Arena: UI components11621210MiniMax M2.7
Design Arena: game dev11961209MiniMax M2.7
Design Arena: data viz11271233MiniMax M2.7
Design Arena: 3D11881195MiniMax M2.7
Design Arena: all code categories12051233MiniMax M2.7
Design Arena: SVG11551137DeepSeek V4 Flash 0423
Design Arena: ASCII art11091136MiniMax M2.7
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
General benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBenchNot measured75.7%Only MiniMax M2.7 measured
Long context reasoning (AA-LCR)Not measured78.3%Only MiniMax M2.7 measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text14321405DeepSeek V4 Flash 0423
LMArena Text: instruction following14211405DeepSeek V4 Flash 0423
LMArena Text: creative writing14031354DeepSeek V4 Flash 0423
LMArena Text: English14411426DeepSeek V4 Flash 0423
LMArena Text: non-English14191382DeepSeek V4 Flash 0423
LMArena Text: Chinese14631442DeepSeek V4 Flash 0423
LMArena Text: German14191398DeepSeek V4 Flash 0423
LMArena Text: Japanese13891260DeepSeek V4 Flash 0423
LMArena Text: Korean13831314DeepSeek V4 Flash 0423
LMArena Text: French14391424DeepSeek V4 Flash 0423
LMArena Text: Spanish14361402DeepSeek V4 Flash 0423
LMArena Text: Russian14271383DeepSeek V4 Flash 0423
LMArena Text: Polish14361387DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491412DeepSeek V4 Flash 0423
LMArena Text: longer queries14341418DeepSeek V4 Flash 0423
LMArena Text: writing and language14101376DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001360DeepSeek V4 Flash 0423
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 0423 and MiniMax M2.7
BenchmarkDeepSeek V4 Flash 0423MiniMax 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 0423$0.0003Fits in one request
MiniMax M2.7$0.0009Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
MiniMax M2.7$0.019Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
MiniMax M2.7$0.072Exceeds the context window

DeepSeek V4 Flash 0423 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 0423 and MiniMax M2.7
SpecificationDeepSeek V4 Flash 0423MiniMax M2.7
MakerDeepSeekMiniMax
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026March 18, 2026
Context window1.05M205K
Input $/Mtok$0.14$0.30
Output $/Mtok$0.28$1.20
Coding indexNot benchmarked36.2
Independent measurements behind it13
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than MiniMax M2.7 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 4.3x cheaper ($0.28 vs $1.20 per million) and a larger context window (1.05M against 205K tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or MiniMax M2.7?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, DeepSeek V4 Flash 0423 or MiniMax M2.7?

DeepSeek V4 Flash 0423, with 1.05M tokens against 205K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs MiniMax M2.7 comparison based on?

45 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark 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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