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DeepSeek V4 Pro 0423 vs Mistral Medium 3.5

DeepSeek V4 Pro 0423 leads Mistral Medium 3.5 on coding, 38.7 to 25.5 on the Vibe Coding Index, and DeepSeek V4 Pro 0423 costs 2.5x less per output token ($2.976 vs $7.50 per million). Updated October 22, 2026; 63 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0423 Replace Mistral Medium 3.5
DeepSeek V4 Pro 0423DeepSeek
Coding
38.7
Overall
50.0
Output $/M
$2.976
63
Mistral Medium 3.5Mistral AI
Coding
25.5
Overall
37.3
Output $/M
$7.50
0
vs boards won of 63 shared

DeepSeek V4 Pro 0423 or Mistral Medium 3.5: which to pick

Pick DeepSeek V4 Pro 0423 for coding: it scores 38.7 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5.

Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Model ADeepSeek V4 Pro 0423DeepSeek38.7/1005 independent benchmarks$0.57 per solved taskModel BMistral Medium 3.5Mistral AI25.5/1003 independent benchmarks$6.02 per solved task
Shared results
63
DeepSeek V4 Pro 0423 only
21
Mistral Medium 3.5 only
18
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 Pro 0423 38.7 from 5 benchmarks, Mistral Medium 3.5 25.5 from 3 benchmarks.
Widest category
Agentic work, 21.3 points apart on average over 5 shared benchmarks.
Widest single gap
GPQA Diamond: DeepSeek V4 Pro 0423 89.4% against Mistral Medium 3.5 34.9%, 54.5 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0423 $2.976 against Mistral Medium 3.5 $7.50 per million output tokens, 2.5x apart.
Context window
DeepSeek V4 Pro 0423 takes 1.05M tokens, Mistral Medium 3.5 262K.

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 Pro 0423BarsMistral Medium 3.5Ties
Coding110
Intelligence20
Agentic work50
Reasoning50
Math30
Knowledge90
Web design80
General200
All shared boards630
CodingLike-for-likeSix of these boards feed the Vibe Coding Index110
Coding benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
LMArena WebDev14471264DeepSeek V4 Pro 0423
AA Coding Index59.446.9DeepSeek V4 Pro 0423
LiveCodeBench (Vals AI)87.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
SWE-bench Verified (Vals AI)77.4%66.4%DeepSeek V4 Pro 0423
Terminal-Bench 4 (Vals AI)11.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Vibe Code Bench (Vals AI)49.9%2.9%DeepSeek V4 Pro 0423
Code migration (Vals AI)26.2%5.1%DeepSeek V4 Pro 0423
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
Terminal-Bench 2.1 (Vals AI)50.2%39.0%DeepSeek V4 Pro 0423
SkillsBench (Vals AI)51.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
SciCodeNot measured40.2%Only Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured33.3%Only Mistral Medium 3.5 measured
FrontierCode17.6%Not measuredOnly DeepSeek V4 Pro 0423 measured
WeirdML48.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
ALE-Bench1006.1764.0DeepSeek V4 Pro 0423
LMArena Text: coding14701460DeepSeek V4 Pro 0423
LMArena Text: software and IT14691458DeepSeek V4 Pro 0423
LMArena WebDev: React14411254DeepSeek V4 Pro 0423
LMArena WebDev: HTML14351308DeepSeek V4 Pro 0423
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
AA Intelligence Index30.414.2DeepSeek V4 Pro 0423
Epoch Capabilities Index149.1141.4DeepSeek V4 Pro 0423
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
Agentic work benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
AA Agentic Index26.37.0DeepSeek V4 Pro 0423
Design Arena: agents building web apps1000Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: agents building full-stack apps948Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: agents building Godot games1059Not measuredOnly DeepSeek V4 Pro 0423 measured
Finance Agent (Vals AI)44.1%32.1%DeepSeek V4 Pro 0423
Tax Agent Bench (Vals AI)25.2%4.5%DeepSeek V4 Pro 0423
Legal Research Bench (Vals AI)23.1%9.1%DeepSeek V4 Pro 0423
Excel Modeling Benchmark (Vals AI)51.6%11.2%DeepSeek V4 Pro 0423
τ²-Bench TelecomNot measured94.2%Only Mistral Medium 3.5 measured
Vending-Bench 2$3,285Not measuredOnly DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
GPQA Diamond89.4%34.9%DeepSeek V4 Pro 0423
GPQA Diamond (Artificial Analysis run)Not measured74.8%Only Mistral Medium 3.5 measured
Humanity's Last Exam (Artificial Analysis run)Not measured13.8%Only Mistral Medium 3.5 measured
GPQA Diamond (Epoch AI run)90.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
Chess puzzles19.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
Mystery game puzzles17.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: hard prompts14611436DeepSeek V4 Pro 0423
LMArena Text: expert14631432DeepSeek V4 Pro 0423
LMArena Text: hard prompts in English14661445DeepSeek V4 Pro 0423
LMArena Vision: diagramsNot measured1254Only Mistral Medium 3.5 measured
LMArena Vision: homeworkNot measured1230Only Mistral Medium 3.5 measured
Kagi LLM Benchmark53.5%41.4%DeepSeek V4 Pro 0423
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
OTIS Mock AIME96.7%Not measuredOnly DeepSeek V4 Pro 0423 measured
FrontierMath, tiers 1 to 345.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
FrontierMath, tier 42.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
ProofBench16.0%9.0%DeepSeek V4 Pro 0423
LMArena Text: math14431431DeepSeek V4 Pro 0423
LMArena Text: mathematical work14551440DeepSeek V4 Pro 0423
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90
Knowledge benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
MMLU Pro87.3%75.3%DeepSeek V4 Pro 0423
LegalBench (Vals AI)80.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
CaseLaw (Vals AI)59.4%44.2%DeepSeek V4 Pro 0423
CorpFin (Vals AI)61.4%58.8%DeepSeek V4 Pro 0423
TaxEval (Vals AI)72.1%68.0%DeepSeek V4 Pro 0423
MortgageTax (Vals AI)Not measured28.9%Only Mistral Medium 3.5 measured
MedCode (Vals AI)40.5%33.8%DeepSeek V4 Pro 0423
SimpleQA Verified47.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: science14701428DeepSeek V4 Pro 0423
LMArena Text: medicine and healthcare14661409DeepSeek V4 Pro 0423
LMArena Text: legal and government14641437DeepSeek V4 Pro 0423
LMArena Text: business and finance14431426DeepSeek V4 Pro 0423
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
Design Arena: websites12341142DeepSeek V4 Pro 0423
Design Arena: UI components12191076DeepSeek V4 Pro 0423
Design Arena: game dev12281079DeepSeek V4 Pro 0423
Design Arena: data viz12031120DeepSeek V4 Pro 0423
Design Arena: 3D12531060DeepSeek V4 Pro 0423
Design Arena: all code categories12401121DeepSeek V4 Pro 0423
Design Arena: SVG1139949DeepSeek V4 Pro 0423
Design Arena: ASCII art11491062DeepSeek V4 Pro 0423
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index200
General benchmarks for DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
Public Benefits Bench (Vals AI)62.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
SAGE (Vals AI)Not measured37.6%Only Mistral Medium 3.5 measured
MedScribe (Vals AI)75.1%67.7%DeepSeek V4 Pro 0423
Vals Multimodal IndexNot measured34.8%Only Mistral Medium 3.5 measured
IFBenchNot measured68.8%Only Mistral Medium 3.5 measured
Long context reasoning (AA-LCR)Not measured69.3%Only Mistral Medium 3.5 measured
DTBench90.7%75.5%DeepSeek V4 Pro 0423
LMCA41.2%26.1%DeepSeek V4 Pro 0423
Surface Evolver Bench40.0%26.9%DeepSeek V4 Pro 0423
CL-bench Life13.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text14511421DeepSeek V4 Pro 0423
LMArena Text: instruction following14451415DeepSeek V4 Pro 0423
LMArena Text: creative writing14461374DeepSeek V4 Pro 0423
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: English14591433DeepSeek V4 Pro 0423
LMArena Text: non-English14391404DeepSeek V4 Pro 0423
LMArena Text: Chinese14811444DeepSeek V4 Pro 0423
LMArena Text: German14581453DeepSeek V4 Pro 0423
LMArena Text: Japanese1446Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: Korean14091384DeepSeek V4 Pro 0423
LMArena Text: French14731448DeepSeek V4 Pro 0423
LMArena Text: Spanish14571411DeepSeek V4 Pro 0423
LMArena Text: Russian14531395DeepSeek V4 Pro 0423
LMArena Text: Polish14611430DeepSeek V4 Pro 0423
LMArena Text: multi-turn14681423DeepSeek V4 Pro 0423
LMArena Text: longer queries14581415DeepSeek V4 Pro 0423
LMArena Text: writing and language14471384DeepSeek V4 Pro 0423
LMArena Text: entertainment and media14311382DeepSeek V4 Pro 0423
LMArena Vision: EnglishNot measured1240Only Mistral Medium 3.5 measured
LMArena Vision: ChineseNot measured1244Only Mistral Medium 3.5 measured
LMArena Vision: reading textNot measured1233Only Mistral Medium 3.5 measured
LMArena Vision: humorNot measured1216Only Mistral Medium 3.5 measured
LMArena Vision: creative writingNot measured1198Only Mistral Medium 3.5 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 DeepSeek V4 Pro 0423 and Mistral Medium 3.5
BenchmarkDeepSeek V4 Pro 0423Mistral Medium 3.5Leader
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 Pro 0423$0.0028Fits in one request
Mistral Medium 3.5$0.0053Fits in one request

DeepSeek V4 Pro 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0423$0.077Fits in one request
Mistral Medium 3.5$0.098Fits in one request

DeepSeek V4 Pro 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0423$0.301Fits in one request
Mistral Medium 3.5$0.375Fits in one request

DeepSeek V4 Pro 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 Pro 0423 and Mistral Medium 3.5
SpecificationDeepSeek V4 Pro 0423Mistral Medium 3.5
MakerDeepSeekMistral AI
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026April 30, 2026
Context window1.05M262K
Input $/Mtok$1.358$1.50
Output $/Mtok$2.976$7.50
Coding index38.725.5
Independent measurements behind it53
Cost per solved task$0.57$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0423 better than Mistral Medium 3.5 for coding?

Pick DeepSeek V4 Pro 0423 for coding: it scores 38.7 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5. Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Which is cheaper, DeepSeek V4 Pro 0423 or Mistral Medium 3.5?

DeepSeek V4 Pro 0423 costs $1.358 per million input tokens and $2.976 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0423 costs $0.57 and Mistral Medium 3.5 $6.02.

Which has the bigger context window, DeepSeek V4 Pro 0423 or Mistral Medium 3.5?

DeepSeek V4 Pro 0423, with 1.05M tokens against 262K.

How many benchmarks is the DeepSeek V4 Pro 0423 vs Mistral Medium 3.5 comparison based on?

63 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0423's coding index rests on 5 independent benchmarks and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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