DeepSeek V3 0324 vs MiniMax M2.5
MiniMax M2.5 leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 22.8 to 9.7, at about the same output price ($1.20 vs $1.07 per million). Updated October 22, 2026; 16 benchmarks have a result for both.
DeepSeek V3 0324 or MiniMax M2.5: which to pick
Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; DeepSeek V3 0324 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3 0324 for output tokens 1.1x cheaper ($1.07 vs $1.20 per million) and work measured by TaxEval (Vals AI), where it leads.
- Shared results
- 16
- DeepSeek V3 0324 only
- 20
- MiniMax M2.5 only
- 55
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only MiniMax M2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M2.5
MiniMax M2.5 leads, 22.8 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V3 0324 has a AA Agentic Index result, 0.8.
Directional only
Reasoning
GPQA Diamond
MiniMax M2.5
MiniMax M2.5 leads, 82.1% against 61.6%.
Same board, both measured
Math
AIME
MiniMax M2.5
MiniMax M2.5 leads, 88.8% against 52.2%.
Same board, both measured
Knowledge
MMLU Pro
MiniMax M2.5
MiniMax M2.5 leads, 80.1% against 79.5%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiniMax M2.5 has a Design Arena: websites result, 1222.
Directional only
Long documents
Listed context window
MiniMax M2.5
MiniMax M2.5 takes 205K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3 0324
DeepSeek V3 0324 $0.0008, MiniMax M2.5 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.5 has the number, $0.62.
Directional only
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, MiniMax M2.5 37.2 from 3 benchmarks.
- Widest category
- Agentic work, 48.2 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: DeepSeek V3 0324 47.1% against MiniMax M2.5 95.3%, 48.2 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against MiniMax M2.5 $1.20 per million output tokens, 1.1x apart.
- Context window
- DeepSeek V3 0324 takes 164K tokens, MiniMax M2.5 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.
| Category | DeepSeek V3 0324 | Bars | MiniMax M2.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 1 | ||
| Knowledge | 1 | 4 | ||
| General | 0 | 2 | ||
| All shared boards | 1 | 15 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | 75.8% | MiniMax M2.5 |
| SWE-bench Multilingual | Not measured | 68.3% | Only MiniMax M2.5 measured |
| LMArena WebDev | Not measured | 1386 | Only MiniMax M2.5 measured |
| AA Coding Index | 21.2 | Not measured | Only DeepSeek V3 0324 measured |
| LiveCodeBench (Vals AI) | 65.5% | 79.2% | MiniMax M2.5 |
| SWE-bench Verified (Vals AI) | Not measured | 74.2% | Only MiniMax M2.5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 14.8% | Only MiniMax M2.5 measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | Not measured | Only DeepSeek V3 0324 measured |
| SciCode | 39.0% | Not measured | Only DeepSeek V3 0324 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 34.8% | MiniMax M2.5 |
| Terminal-Bench | Not measured | 42.7% | Only MiniMax M2.5 measured |
| WeirdML | 36.1% | Not measured | Only DeepSeek V3 0324 measured |
| ALE-Bench | Not measured | 618.2 | Only MiniMax M2.5 measured |
| LMArena Text: coding | Not measured | 1380 | Only MiniMax M2.5 measured |
| LMArena Text: software and IT | Not measured | 1383 | Only MiniMax M2.5 measured |
| LMArena WebDev: React | Not measured | 1374 | Only MiniMax M2.5 measured |
| LMArena WebDev: HTML | Not measured | 1414 | Only MiniMax M2.5 measured |
| SWE Atlas: Codebase QnA | Not measured | 10.3% | Only MiniMax M2.5 measured |
| SWE Atlas: Refactoring | Not measured | 19.5% | Only MiniMax M2.5 measured |
| SWE Atlas: Test Writing | Not measured | 18.6% | Only MiniMax M2.5 measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 22.8 | MiniMax M2.5 |
| Epoch Capabilities Index | Not measured | 146.6 | Only MiniMax M2.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | Not measured | Only DeepSeek V3 0324 measured |
| τ²-Bench Telecom | 47.1% | 95.3% | MiniMax M2.5 |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| Vending-Bench 2 | Not measured | -$23 | Only MiniMax M2.5 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | 82.1% | MiniMax M2.5 |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 84.8% | MiniMax M2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 20.5% | MiniMax M2.5 |
| GPQA Diamond (Epoch AI run) | 67.6% | Not measured | Only DeepSeek V3 0324 measured |
| ARC-AGI | Not measured | 63.7% | Only MiniMax M2.5 measured |
| ARC-AGI-2 | Not measured | 4.9% | Only MiniMax M2.5 measured |
| SimpleBench | 27.2% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: hard prompts | Not measured | 1372 | Only MiniMax M2.5 measured |
| LMArena Text: expert | Not measured | 1378 | Only MiniMax M2.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1384 | Only MiniMax M2.5 measured |
| Kagi LLM Benchmark | Not measured | 55.2% | Only MiniMax M2.5 measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| AIME | 52.2% | 88.8% | MiniMax M2.5 |
| MATH 500 (Vals AI) | 88.6% | Not measured | Only DeepSeek V3 0324 measured |
| MGSM (Vals AI) | 91.7% | Not measured | Only DeepSeek V3 0324 measured |
| AA Math Index | 41.0 | Not measured | Only DeepSeek V3 0324 measured |
| AIME 2025 (Artificial Analysis run) | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| OTIS Mock AIME | 37.8% | Not measured | Only DeepSeek V3 0324 measured |
| ProofBench | Not measured | 4.0% | Only MiniMax M2.5 measured |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: math | Not measured | 1378 | Only MiniMax M2.5 measured |
| LMArena Text: mathematical work | Not measured | 1378 | Only MiniMax M2.5 measured |
| MathArena | 7.1% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | 80.1% | MiniMax M2.5 |
| LegalBench (Vals AI) | 77.7% | 80.0% | MiniMax M2.5 |
| CaseLaw (Vals AI) | Not measured | 53.5% | Only MiniMax M2.5 measured |
| CorpFin (Vals AI) | 54.7% | 59.6% | MiniMax M2.5 |
| TaxEval (Vals AI) | 71.1% | 68.2% | DeepSeek V3 0324 |
| MedQA (Vals AI) | 82.0% | 92.5% | MiniMax M2.5 |
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: science | Not measured | 1369 | Only MiniMax M2.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1357 | Only MiniMax M2.5 measured |
| LMArena Text: legal and government | Not measured | 1366 | Only MiniMax M2.5 measured |
| LMArena Text: business and finance | Not measured | 1356 | Only MiniMax M2.5 measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1222 | Only MiniMax M2.5 measured |
| Design Arena: UI components | Not measured | 1170 | Only MiniMax M2.5 measured |
| Design Arena: game dev | Not measured | 1176 | Only MiniMax M2.5 measured |
| Design Arena: data viz | Not measured | 1172 | Only MiniMax M2.5 measured |
| Design Arena: 3D | Not measured | 1170 | Only MiniMax M2.5 measured |
| Design Arena: all code categories | Not measured | 1207 | Only MiniMax M2.5 measured |
| Design Arena: SVG | Not measured | 1150 | Only MiniMax M2.5 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| IFBench | 41.0% | 71.6% | MiniMax M2.5 |
| Long context reasoning (AA-LCR) | 40.7% | 73.3% | MiniMax M2.5 |
| DTBench | 64.8% | Not measured | Only DeepSeek V3 0324 measured |
| LMCA | 15.5% | Not measured | Only DeepSeek V3 0324 measured |
| Fiction.LiveBench | 50.0% | Not measured | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | 77.0% | Not measured | Only DeepSeek V3 0324 measured |
| CL-bench | Not measured | 11.4% | Only MiniMax M2.5 measured |
| CL-bench Life | Not measured | 6.3% | Only MiniMax M2.5 measured |
| LMArena Text | Not measured | 1359 | Only MiniMax M2.5 measured |
| LMArena Text: instruction following | Not measured | 1353 | Only MiniMax M2.5 measured |
| LMArena Text: creative writing | Not measured | 1331 | Only MiniMax M2.5 measured |
| LMArena Text: English | Not measured | 1380 | Only MiniMax M2.5 measured |
| LMArena Text: non-English | Not measured | 1338 | Only MiniMax M2.5 measured |
| LMArena Text: Chinese | Not measured | 1393 | Only MiniMax M2.5 measured |
| LMArena Text: German | Not measured | 1361 | Only MiniMax M2.5 measured |
| LMArena Text: Japanese | Not measured | 1171 | Only MiniMax M2.5 measured |
| LMArena Text: Korean | Not measured | 1233 | Only MiniMax M2.5 measured |
| LMArena Text: French | Not measured | 1363 | Only MiniMax M2.5 measured |
| LMArena Text: Spanish | Not measured | 1353 | Only MiniMax M2.5 measured |
| LMArena Text: Russian | Not measured | 1359 | Only MiniMax M2.5 measured |
| LMArena Text: Polish | Not measured | 1334 | Only MiniMax M2.5 measured |
| LMArena Text: multi-turn | Not measured | 1364 | Only MiniMax M2.5 measured |
| LMArena Text: longer queries | Not measured | 1366 | Only MiniMax M2.5 measured |
| LMArena Text: writing and language | Not measured | 1345 | Only MiniMax M2.5 measured |
| LMArena Text: entertainment and media | Not measured | 1329 | Only MiniMax M2.5 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
| Benchmark | DeepSeek V3 0324 | MiniMax M2.5 | Leader |
|---|---|---|---|
| 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 0324 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3 0324 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3 0324 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.
| Specification | DeepSeek V3 0324 | MiniMax M2.5 |
|---|---|---|
| Maker | DeepSeek | MiniMax |
| Weights | Open weights | Open weights |
| Released | March 24, 2025 | February 12, 2026 |
| Context window | 164K | 205K |
| Input $/Mtok | $0.27 | $0.30 |
| Output $/Mtok | $1.07 | $1.20 |
| Coding index | Not benchmarked | 37.2 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $0.62 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than MiniMax M2.5 for coding?
Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; DeepSeek V3 0324 has none, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for output tokens 1.1x cheaper ($1.07 vs $1.20 per million) and work measured by TaxEval (Vals AI), where it leads.
Which is cheaper, DeepSeek V3 0324 or MiniMax M2.5?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; MiniMax M2.5 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.5 only.
Which has the bigger context window, DeepSeek V3 0324 or MiniMax M2.5?
MiniMax M2.5, with 205K tokens against 164K.
How many benchmarks is the DeepSeek V3 0324 vs MiniMax M2.5 comparison based on?
16 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3 0324's coding index rests on 0 independent benchmarks and MiniMax M2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.