Enter opens the highlighted result. Esc closes.

DeepSeek V3.2 Exp vs MiniMax M2.1

MiniMax M2.1 leads DeepSeek V3.2 Exp on the Artificial Analysis Intelligence Index, 20.9 to 16.6, and DeepSeek V3.2 Exp costs 2.9x less per output token ($0.41 vs $1.20 per million). Updated October 23, 2026; 18 benchmarks have a result for both.

Replace DeepSeek V3.2 Exp Replace MiniMax M2.1
DeepSeek V3.2 ExpDeepSeek
Coding
No data
Overall
No data
Output $/M
$0.41
5
MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
13
vs boards won of 18 shared

DeepSeek V3.2 Exp or MiniMax M2.1: which to pick

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

Pick DeepSeek V3.2 Exp for output tokens 2.9x cheaper ($0.41 vs $1.20 per million) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.

Model ADeepSeek V3.2 ExpDeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BMiniMax M2.1MiniMaxNot benchmarked1 independent benchmark$0.59 per solved task
Shared results
18
DeepSeek V3.2 Exp only
42
MiniMax M2.1 only
16
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 V3.2 Exp not benchmarked, MiniMax M2.1 not benchmarked.
Widest category
Agentic work, 51.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.2 Exp 33.9% against MiniMax M2.1 85.4%, 51.5 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against MiniMax M2.1 $1.20 per million output tokens, 2.9x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, MiniMax M2.1 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 V3.2 ExpBarsMiniMax M2.1Ties
Coding11
Intelligence01
Agentic work01
Reasoning02
Math20
Knowledge01
Web design16
General11
All shared boards513
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
Coding benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev1272Not measuredOnly DeepSeek V3.2 Exp measured
LiveCodeBench (Vals AI)Not measured81.8%Only MiniMax M2.1 measured
SWE-bench Verified (Vals AI)Not measured74.8%Only MiniMax M2.1 measured
LiveCodeBench (Artificial Analysis run)78.9%81.0%MiniMax M2.1
Terminal-Bench Hard (Artificial Analysis run)31.1%28.8%DeepSeek V3.2 Exp
Terminal-BenchNot measured36.6%Only MiniMax M2.1 measured
WeirdML39.5%Not measuredOnly DeepSeek V3.2 Exp measured
ALE-BenchNot measured623.8Only MiniMax M2.1 measured
LMArena Text: coding1439Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: software and IT1438Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev: HTML1281Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
AA Intelligence Index16.620.9MiniMax M2.1
Epoch Capabilities Index144.9Not measuredOnly DeepSeek V3.2 Exp measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
τ²-Bench Telecom33.9%85.4%MiniMax M2.1
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Berkeley Function Calling Leaderboard (BFCL)56.7%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
GPQA DiamondNot measured78.5%Only MiniMax M2.1 measured
GPQA Diamond (Artificial Analysis run)79.7%83.0%MiniMax M2.1
Humanity's Last Exam (Artificial Analysis run)14.9%23.2%MiniMax M2.1
LMArena Text: hard prompts1429Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: expert1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: hard prompts in English1444Not measuredOnly DeepSeek V3.2 Exp measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
AIMENot measured77.9%Only MiniMax M2.1 measured
MATH 500 (Vals AI)Not measured89.0%Only MiniMax M2.1 measured
MGSM (Vals AI)Not measured87.8%Only MiniMax M2.1 measured
AA Math Index87.782.7DeepSeek V3.2 Exp
AIME 2025 (Artificial Analysis run)87.7%82.7%DeepSeek V3.2 Exp
LMArena Text: math1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: mathematical work1434Not measuredOnly DeepSeek V3.2 Exp measured
MathArena14.4%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
MMLU ProNot measured87.0%Only MiniMax M2.1 measured
LegalBench (Vals AI)Not measured75.5%Only MiniMax M2.1 measured
CaseLaw (Vals AI)Not measured55.8%Only MiniMax M2.1 measured
CorpFin (Vals AI)Not measured58.9%Only MiniMax M2.1 measured
TaxEval (Vals AI)Not measured66.3%Only MiniMax M2.1 measured
MedQA (Vals AI)Not measured91.2%Only MiniMax M2.1 measured
MedCode (Vals AI)Not measured34.1%Only MiniMax M2.1 measured
MMLU Pro (Artificial Analysis run)85.0%87.5%MiniMax M2.1
LMArena Text: science1444Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: medicine and healthcare1469Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: legal and government1420Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: business and finance1412Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index16
Web design benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
Design Arena: websites11791201MiniMax M2.1
Design Arena: UI components11641220MiniMax M2.1
Design Arena: game dev11441134DeepSeek V3.2 Exp
Design Arena: data viz11521207MiniMax M2.1
Design Arena: 3D11491166MiniMax M2.1
Design Arena: all code categories11701190MiniMax M2.1
Design Arena: SVG10311131MiniMax M2.1
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for DeepSeek V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
MedScribe (Vals AI)Not measured80.8%Only MiniMax M2.1 measured
IFBench54.1%69.9%MiniMax M2.1
Long context reasoning (AA-LCR)72.3%67.7%DeepSeek V3.2 Exp
DTBench87.7%Not measuredOnly DeepSeek V3.2 Exp measured
LMCA29.1%Not measuredOnly DeepSeek V3.2 Exp measured
Fiction.LiveBench83.3%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench13.2%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench Life9.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text1425Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: instruction following1401Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: creative writing1403Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: English1441Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: non-English1405Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Chinese1461Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: German1440Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Japanese1331Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Korean1370Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: French1434Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Spanish1441Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Russian1412Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Polish1435Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: multi-turn1421Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: longer queries1418Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: writing and language1407Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: entertainment and media1407Not measuredOnly DeepSeek V3.2 Exp 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 V3.2 Exp and MiniMax M2.1
BenchmarkDeepSeek V3.2 ExpMiniMax M2.1Leader
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 V3.2 Exp$0.0005Fits in one request
MiniMax M2.1$0.0009Fits in one request

DeepSeek V3.2 Exp costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2 Exp$0.015Fits in one request
MiniMax M2.1$0.019Fits in one request

DeepSeek V3.2 Exp costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2 Exp$0.058Exceeds the context window
MiniMax M2.1$0.072Exceeds the context window

DeepSeek V3.2 Exp 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 V3.2 Exp and MiniMax M2.1
SpecificationDeepSeek V3.2 ExpMiniMax M2.1
MakerDeepSeekMiniMax
WeightsOpen weightsOpen weights
ReleasedSeptember 29, 2025December 23, 2025
Context window164K205K
Input $/Mtok$0.27$0.30
Output $/Mtok$0.41$1.20
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it11
Cost per solved taskNot computable$0.59
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than MiniMax M2.1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.2 Exp for output tokens 2.9x cheaper ($0.41 vs $1.20 per million) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, DeepSeek V3.2 Exp or MiniMax M2.1?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.1 only.

Which has the bigger context window, DeepSeek V3.2 Exp or MiniMax M2.1?

MiniMax M2.1, with 205K tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs MiniMax M2.1 comparison based on?

18 benchmarks have a result for both models as of October 23, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark and MiniMax M2.1's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next