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DeepSeek V4 Flash 0423 vs MiMo-V2.5

DeepSeek V4 Flash 0423 leads MiMo-V2.5 on the Artificial Analysis Intelligence Index, 24.4 to 21.8, and DeepSeek V4 Flash 0423 costs 1.2x less per output token ($0.28 vs $0.336 per million). Updated October 22, 2026; 43 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace MiMo-V2.5
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
20
MiMo-V2.5Xiaomi
Coding
50.0
Overall
50.7
Output $/M
$0.336
23
vs boards won of 43 shared

DeepSeek V4 Flash 0423 or MiMo-V2.5: which to pick

Only MiMo-V2.5 has a coding score, 50.0 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 1.2x cheaper ($0.28 vs $0.336 per million) and work measured by LMArena WebDev or ALE-Bench, where it leads.

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BMiMo-V2.5Xiaomi50.0/1003 independent benchmarks$0.01 per solved task
Shared results
43
DeepSeek V4 Flash 0423 only
6
MiMo-V2.5 only
37
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, MiMo-V2.5 50.0 from 3 benchmarks.
Widest category
Coding, 11.8 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: DeepSeek V4 Flash 0423 1585 against MiMo-V2.5 1425, 26.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against MiMo-V2.5 $0.336 per million output tokens, 1.2x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, MiMo-V2.5 1.05M.

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 0423BarsMiMo-V2.5Ties
Coding43
Intelligence10
Agentic work10
Reasoning03
Math02
Knowledge31
Web design08
General116
All shared boards2023
CodingLike-for-likeSix of these boards feed the Vibe Coding Index43
Coding benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
LMArena WebDev15821438DeepSeek V4 Flash 0423
AA Coding Index52.056.8MiMo-V2.5
LiveCodeBench (Vals AI)Not measured81.5%Only MiMo-V2.5 measured
SWE-bench Verified (Vals AI)Not measured71.0%Only MiMo-V2.5 measured
Vibe Code Bench (Vals AI)Not measured42.2%Only MiMo-V2.5 measured
Code migration (Vals AI)Not measured14.2%Only MiMo-V2.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured60.7%Only MiMo-V2.5 measured
SciCodeNot measured43.9%Only MiMo-V2.5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured41.7%Only MiMo-V2.5 measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2514.0DeepSeek V4 Flash 0423
LMArena Text: coding14571469MiMo-V2.5
LMArena Text: software and IT14531463MiMo-V2.5
LMArena WebDev: React15851425DeepSeek V4 Flash 0423
LMArena WebDev: HTML15581429DeepSeek V4 Flash 0423
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
AA Intelligence Index24.421.8DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V4 Flash 0423 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
AA Agentic Index26.315.8DeepSeek V4 Flash 0423
Finance Agent (Vals AI)Not measured36.7%Only MiMo-V2.5 measured
Tax Agent Bench (Vals AI)Not measured7.8%Only MiMo-V2.5 measured
Legal Research Bench (Vals AI)Not measured9.1%Only MiMo-V2.5 measured
Excel Modeling Benchmark (Vals AI)Not measured55.1%Only MiMo-V2.5 measured
τ²-Bench TelecomNot measured90.6%Only MiMo-V2.5 measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
GPQA DiamondNot measured81.6%Only MiMo-V2.5 measured
MMMU Pro (Vals AI)Not measured80.0%Only MiMo-V2.5 measured
GPQA Diamond (Artificial Analysis run)Not measured84.9%Only MiMo-V2.5 measured
Humanity's Last Exam (Artificial Analysis run)Not measured27.2%Only MiMo-V2.5 measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441450MiMo-V2.5
LMArena Text: expert14411459MiMo-V2.5
LMArena Text: hard prompts in English14491461MiMo-V2.5
LMArena Vision: diagramsNot measured1269Only MiMo-V2.5 measured
LMArena Vision: homeworkNot measured1262Only MiMo-V2.5 measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
ProofBenchNot measured16.0%Only MiMo-V2.5 measured
LMArena Text: math14261436MiMo-V2.5
LMArena Text: mathematical work14321451MiMo-V2.5
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
Knowledge benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
MMLU ProNot measured82.9%Only MiMo-V2.5 measured
LegalBench (Vals AI)Not measured78.9%Only MiMo-V2.5 measured
CorpFin (Vals AI)Not measured59.9%Only MiMo-V2.5 measured
TaxEval (Vals AI)Not measured71.8%Only MiMo-V2.5 measured
MortgageTax (Vals AI)Not measured59.3%Only MiMo-V2.5 measured
MedCode (Vals AI)Not measured31.9%Only MiMo-V2.5 measured
LMArena Text: science14461440DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481432DeepSeek V4 Flash 0423
LMArena Text: legal and government14391425DeepSeek V4 Flash 0423
LMArena Text: business and finance14251432MiMo-V2.5
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
Design Arena: websites12071265MiMo-V2.5
Design Arena: UI components11621255MiMo-V2.5
Design Arena: game dev11961249MiMo-V2.5
Design Arena: data viz11271250MiMo-V2.5
Design Arena: 3D11881215MiMo-V2.5
Design Arena: all code categories12051260MiMo-V2.5
Design Arena: SVG11551179MiMo-V2.5
Design Arena: ASCII art11091140MiMo-V2.5
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index116
General benchmarks for DeepSeek V4 Flash 0423 and MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
SAGE (Vals AI)Not measured43.3%Only MiMo-V2.5 measured
MedScribe (Vals AI)Not measured72.2%Only MiMo-V2.5 measured
Vals Multimodal IndexNot measured52.8%Only MiMo-V2.5 measured
IFBenchNot measured67.1%Only MiMo-V2.5 measured
Long context reasoning (AA-LCR)Not measured73.0%Only MiMo-V2.5 measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text14321428DeepSeek V4 Flash 0423
LMArena Text: instruction following14211435MiMo-V2.5
LMArena Text: creative writing14031393DeepSeek V4 Flash 0423
LMArena VisionNot measured1247Only MiMo-V2.5 measured
LMArena Text: English14411447MiMo-V2.5
LMArena Text: non-English14191405DeepSeek V4 Flash 0423
LMArena Text: Chinese14631469MiMo-V2.5
LMArena Text: German14191421MiMo-V2.5
LMArena Text: Japanese13891306DeepSeek V4 Flash 0423
LMArena Text: Korean13831361DeepSeek V4 Flash 0423
LMArena Text: French14391448MiMo-V2.5
LMArena Text: Spanish14361414DeepSeek V4 Flash 0423
LMArena Text: Russian14271396DeepSeek V4 Flash 0423
LMArena Text: Polish14361413DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491445DeepSeek V4 Flash 0423
LMArena Text: longer queries14341445MiMo-V2.5
LMArena Text: writing and language14101409DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001399DeepSeek V4 Flash 0423
LMArena Vision: EnglishNot measured1259Only MiMo-V2.5 measured
LMArena Vision: ChineseNot measured1326Only MiMo-V2.5 measured
LMArena Vision: reading textNot measured1256Only MiMo-V2.5 measured
LMArena Vision: humorNot measured1226Only MiMo-V2.5 measured
LMArena Vision: recognizing thingsNot measured1189Only MiMo-V2.5 measured
LMArena Vision: creative writingNot measured1230Only MiMo-V2.5 measured
Neither model has a result on the other 15 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 MiMo-V2.5
BenchmarkDeepSeek V4 Flash 0423MiMo-V2.5Leader
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

DeepSeek V4 Flash 0423$0.0003Fits in one request
MiMo-V2.5$0.0003Fits 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
MiMo-V2.5$0.0094Fits 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
MiMo-V2.5$0.037Fits in one request

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 MiMo-V2.5
SpecificationDeepSeek V4 Flash 0423Xiaomi MiMo-V2.5
MakerDeepSeekXiaomi
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026April 22, 2026
Context window1.05M1.05M
Input $/Mtok$0.14$0.168
Output $/Mtok$0.28$0.336
Coding indexNot benchmarked50.0
Independent measurements behind it13
Cost per solved taskNot computable$0.01
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than MiMo-V2.5 for coding?

Only MiMo-V2.5 has a coding score, 50.0 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 1.2x cheaper ($0.28 vs $0.336 per million) and work measured by LMArena WebDev or ALE-Bench, where it leads.

Which is cheaper, DeepSeek V4 Flash 0423 or MiMo-V2.5?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; MiMo-V2.5 costs $0.168 and $0.336. Cost per solved task is known for MiMo-V2.5 only.

Which has the bigger context window, DeepSeek V4 Flash 0423 or MiMo-V2.5?

MiMo-V2.5, with 1.05M tokens against 1.05M.

How many benchmarks is the DeepSeek V4 Flash 0423 vs MiMo-V2.5 comparison based on?

43 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 MiMo-V2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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