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DeepSeek V4 Flash 0423 vs MiniMax M2

DeepSeek V4 Flash 0423 leads MiniMax M2 on the Artificial Analysis Intelligence Index, 24.4 to 18.6, and DeepSeek V4 Flash 0423 costs 3.6x less per output token ($0.28 vs $1.02 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
35
MiniMax M2MiniMax
Coding
No data
Overall
No data
Output $/M
$1.02
2
vs boards won of 37 shared

DeepSeek V4 Flash 0423 or MiniMax M2: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick DeepSeek V4 Flash 0423 for output tokens 3.6x cheaper ($0.28 vs $1.02 per million) and a larger context window (1.05M against 205K tokens).

Shared results
37
DeepSeek V4 Flash 0423 only
12
MiniMax M2 only
13
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
DeepSeek V4 Flash 0423 not benchmarked, MiniMax M2 not benchmarked.
Widest category
Coding, 27.6 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: DeepSeek V4 Flash 0423 1558 against MiniMax M2 1306, 41.9 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against MiniMax M2 $1.02 per million output tokens, 3.6x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, MiniMax M2 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 M2Ties
Coding40
Intelligence10
Reasoning31
Math20
Knowledge40
Web design61
General150
All shared boards352
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
SWE-bench VerifiedNot measured61.0%Only MiniMax M2 measured
LMArena WebDev15821297DeepSeek V4 Flash 0423
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
LiveCodeBench (Artificial Analysis run)Not measured82.6%Only MiniMax M2 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured25.8%Only MiniMax M2 measured
Terminal-BenchNot measured30.0%Only MiniMax M2 measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571371DeepSeek V4 Flash 0423
LMArena Text: software and IT14531373DeepSeek V4 Flash 0423
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML15581306DeepSeek V4 Flash 0423
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
AA Intelligence Index24.418.6DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V4 Flash 0423 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
τ²-Bench TelecomNot measured86.8%Only MiniMax M2 measured
Vending-Bench 2Not measured$161Only MiniMax M2 measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index31
Reasoning benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
GPQA Diamond (Artificial Analysis run)Not measured77.7%Only MiniMax M2 measured
Humanity's Last Exam (Artificial Analysis run)Not measured13.7%Only MiniMax M2 measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441357DeepSeek V4 Flash 0423
LMArena Text: expert14411338DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491376DeepSeek V4 Flash 0423
Kagi LLM Benchmark52.2%57.8%MiniMax M2
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
AA Math IndexNot measured78.3Only MiniMax M2 measured
AIME 2025 (Artificial Analysis run)Not measured78.3%Only MiniMax M2 measured
LMArena Text: math14261351DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321368DeepSeek V4 Flash 0423
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
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
MMLU Pro (Artificial Analysis run)Not measured82.0%Only MiniMax M2 measured
LMArena Text: science14461348DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481367DeepSeek V4 Flash 0423
LMArena Text: legal and government14391349DeepSeek V4 Flash 0423
LMArena Text: business and finance14251336DeepSeek V4 Flash 0423
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index61
Web design benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
Design Arena: websites12071143DeepSeek V4 Flash 0423
Design Arena: UI components11621137DeepSeek V4 Flash 0423
Design Arena: game dev11961118DeepSeek V4 Flash 0423
Design Arena: data viz11271140MiniMax M2
Design Arena: 3D11881098DeepSeek V4 Flash 0423
Design Arena: all code categories12051135DeepSeek V4 Flash 0423
Design Arena: SVG11551100DeepSeek V4 Flash 0423
Design Arena: ASCII art1109Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index150
General benchmarks for DeepSeek V4 Flash 0423 and MiniMax M2
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
IFBenchNot measured72.3%Only MiniMax M2 measured
Long context reasoning (AA-LCR)Not measured64.3%Only MiniMax M2 measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text14321340DeepSeek V4 Flash 0423
LMArena Text: instruction following14211329DeepSeek V4 Flash 0423
LMArena Text: creative writing14031286DeepSeek V4 Flash 0423
LMArena Text: English14411364DeepSeek V4 Flash 0423
LMArena Text: non-English14191313DeepSeek V4 Flash 0423
LMArena Text: Chinese14631366DeepSeek V4 Flash 0423
LMArena Text: German14191357DeepSeek V4 Flash 0423
LMArena Text: Japanese1389Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Korean1383Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: French14391336DeepSeek V4 Flash 0423
LMArena Text: Spanish14361326DeepSeek V4 Flash 0423
LMArena Text: Russian14271330DeepSeek V4 Flash 0423
LMArena Text: Polish14361312DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491361DeepSeek V4 Flash 0423
LMArena Text: longer queries14341331DeepSeek V4 Flash 0423
LMArena Text: writing and language14101295DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001298DeepSeek V4 Flash 0423
Neither model has a result on the other 25 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
BenchmarkDeepSeek V4 Flash 0423MiniMax M2Leader
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$0.0008Fits 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$0.016Fits 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$0.061Exceeds 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
SpecificationDeepSeek V4 Flash 0423MiniMax M2
MakerDeepSeekMiniMax
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026October 23, 2025
Context window1.05M205K
Input $/Mtok$0.14$0.255
Output $/Mtok$0.28$1.02
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it11
Cost per solved taskNot computable$0.702
SourceOpenRouter listingOpenRouter listing

Questions

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

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 3.6x cheaper ($0.28 vs $1.02 per million) and a larger context window (1.05M against 205K tokens).

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

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Cost per solved task is known for MiniMax M2 only.

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

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

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

37 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's on 1. Where only one model has a result, the page says so instead of naming a winner.

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