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DeepSeek DeepSeek V3.2 VS MiniMax MiniMax M3

DeepSeek V3.2 vs MiniMax M3: which wins at real work?

22 task areas · same graded test runs · rank comparison only, so 0–100 and Elo collections never mix raw scores.

MiniMax M3 wins 18 of 22 task areas we tested; DeepSeek V3.2 takes 4. DeepSeek V3.2 costs 2.6× less per token ($0.572 vs $1.5 per 1M).

4
Task areas won
18
38
Avg percentile
65
0
Top-3 finishes
4
$0.57
Price / 1M tokens
$1.5
DeepSeek
Provider
MiniMax

DeepSeek V3.2 costs 2.6× less per token ($0.572 vs $1.5 per 1M).

Task by task

Task area DeepSeek V3.2 MiniMax M3 Winner
Sales #91 / 110
Usable
#2 / 110
Strong
MiniMax M3
AI Strategy #102 / 126
Usable
#27 / 126
Strong
MiniMax M3
Data & Analytics #69 / 110
Excellent
#1 / 110
Excellent
MiniMax M3
Content & Brand #95 / 124
Usable
#28 / 124
Strong
MiniMax M3
Legal & HR #90 / 110
Strong
#34 / 110
Excellent
MiniMax M3
Presentations & Decks #81 / 110
Strong
#29 / 110
Excellent
MiniMax M3
Coding #100 / 115
Usable
#49 / 115
Strong
MiniMax M3
Summarization & Meeting Notes #30 / 110
Excellent
#79 / 110
Excellent
DeepSeek V3.2
Landing Pages #48 / 72
Usable
#2 / 72
Strong
MiniMax M3
Executive Assistant #76 / 112
Usable
#39 / 112
Strong
MiniMax M3
Investor & Pitch #46 / 66
Usable
#12 / 66
Strong
MiniMax M3
Translation & Localization #89 / 110
Strong
#55 / 110
Excellent
MiniMax M3
Creative & Comedy #87 / 110 #55 / 110 MiniMax M3
Research & Competitive Analysis #53 / 110
Usable
#33 / 110
Strong
MiniMax M3
Product & Project Management #21 / 110
Excellent
#3 / 110
Excellent
MiniMax M3
RAG, Safety & Grounding #83 / 113
Excellent
#72 / 113
Excellent
MiniMax M3
Customer Support #74 / 113
Usable
#83 / 113
Usable
DeepSeek V3.2
Knowledge & Docs #58 / 110
Usable
#67 / 110
Usable
DeepSeek V3.2
Frontend & Landing Pages #25 / 109
Needs editing
#20 / 109
Needs editing
MiniMax M3
Chef / Home Cooking #78 / 126
Usable
#74 / 126
Usable
MiniMax M3
Training & Education #38 / 110
Excellent
#42 / 110
Excellent
DeepSeek V3.2
Structured Output #67 / 113
Strong
#65 / 113
Strong
MiniMax M3

Rank = position among every model config we tested in that task area (lower is better). Sorted by biggest gap first.

Same task, both models — judged

Both models answered the same test case; an independent judge graded each. Quotes are the judge's actual rationale.

Coding

Unit tests for parser (Code Quality and Testing Test)
DeepSeek V3.2 18/100

“The response contains multiple broken tests that will fail when run against the provided parser. It hallucinates random Chinese text into a JSON string, misunderstands how Python's `dict.get()` handles explicit nulls, misunderstands `str(None)`, and fails to provide the requested brief explanation of reasoning.”

MiniMax M3 99/100

“The response is expert-level and production-ready. It fulfills all requirements perfectly, uses advanced pytest features appropriately, and provides insightful commentary on the function's limitations without overcomplicating the requested tests.”

Frequently asked

Is DeepSeek V3.2 better than MiniMax M3?

Across 22 task areas we benchmarked, MiniMax M3 ranks higher in 18 and DeepSeek V3.2 in 4.

Which is cheaper, DeepSeek V3.2 or MiniMax M3?

DeepSeek V3.2 costs 2.6× less per token ($0.572 vs $1.5 per 1M).

What is DeepSeek V3.2 better at?

DeepSeek V3.2 out-ranks MiniMax M3 at Summarization & Meeting Notes, Customer Support, Knowledge & Docs.

What is MiniMax M3 better at?

MiniMax M3 out-ranks DeepSeek V3.2 at Sales, AI Strategy, Data & Analytics.

Full DeepSeek V3.2 review → Full MiniMax M3 review → Full model leaderboard →

More comparisons

This page is Spring Prompt, running in public

We just did this for every model. Do it for your prompt.

The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.

  • Generate test cases from your prompt — no eval set required to start.
  • Compare models side by side with quality, cost and latency in one matrix.
  • Optimise the winner until the scores say it's ready to ship.
Experiment · Cold outreach email

Prompt × model results

12 test cases · 3 evals
Claude Opus
GPT-5
Gemini
v1
7.1
6.8
7.4
v2
8.3
7.9
8.0
v3
9.2
8.6
8.4
Best combo: v3 × Claude Opus
9.2 quality · $0.004/run · 1.8s