MiniMax M1 vs Qwen2.5 72B Instruct
MiniMax M1 leads Qwen2.5 72B Instruct on the Artificial Analysis Intelligence Index, 11.7 to 7.7, and Qwen2.5 72B Instruct costs 5.5x less per output token ($0.40 vs $2.20 per million). Updated October 22, 2026; 28 benchmarks have a result for both.
MiniMax M1 or Qwen2.5 72B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick MiniMax M1 for a larger context window (1M against 33K tokens).
- Shared results
- 28
- MiniMax M1 only
- 1
- Qwen2.5 72B Instruct only
- 25
- Like-for-like categories
- 6 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M1
MiniMax M1 leads, 11.7 against 7.7.
Same board, both measured
Long documents
Listed context window
MiniMax M1
MiniMax M1 takes 1M tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 72B Instruct
MiniMax M1 $0.0015, Qwen2.5 72B Instruct $0.0006 per turn.
List prices
At a glance
- Coding index
- MiniMax M1 not benchmarked, Qwen2.5 72B Instruct not benchmarked.
- Widest category
- Math, 12.6 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: German: MiniMax M1 1350 against Qwen2.5 72B Instruct 1234, 19.4 points apart on a 0 to 100 scale.
- Output price
- MiniMax M1 $2.20 against Qwen2.5 72B Instruct $0.40 per million output tokens, 5.5x apart.
- Context window
- MiniMax M1 takes 1M tokens, Qwen2.5 72B Instruct 33K.
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 | MiniMax M1 | Bars | Qwen2.5 72B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 16 | 0 | ||
| All shared boards | 28 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 27.6% | Only Qwen2.5 72B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 4.5% | Only Qwen2.5 72B Instruct measured |
| WeirdML | Not measured | 16.0% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: coding | 1359 | 1292 | MiniMax M1 |
| LMArena Text: software and IT | 1359 | 1292 | MiniMax M1 |
| Neither model has a result on the other 38 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.7 | 7.7 | MiniMax M1 |
| Epoch Capabilities Index | Not measured | 129.0 | Only Qwen2.5 72B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 34.5% | Only Qwen2.5 72B Instruct measured |
| METR time horizons | Not measured | 35.8% | Only Qwen2.5 72B Instruct measured |
| BALROG | Not measured | 16.2% | Only Qwen2.5 72B Instruct measured |
| TheAgentCompany | Not measured | 5.7% | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 49.1% | Only Qwen2.5 72B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 3.6% | Only Qwen2.5 72B Instruct measured |
| GPQA Diamond (Epoch AI run) | Not measured | 49.1% | Only Qwen2.5 72B Instruct measured |
| BIG-Bench Hard | Not measured | 79.8% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | 1339 | 1271 | MiniMax M1 |
| LMArena Text: expert | 1317 | 1245 | MiniMax M1 |
| LMArena Text: hard prompts in English | 1353 | 1279 | MiniMax M1 |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 14.0 | Only Qwen2.5 72B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 14.0% | Only Qwen2.5 72B Instruct measured |
| OTIS Mock AIME | Not measured | 8.1% | Only Qwen2.5 72B Instruct measured |
| MATH level 5 | Not measured | 63.2% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: math | 1361 | 1283 | MiniMax M1 |
| LMArena Text: mathematical work | 1363 | 1290 | MiniMax M1 |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 72.0% | Only Qwen2.5 72B Instruct measured |
| MMLU | Not measured | 85.3% | Only Qwen2.5 72B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 94.5% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: science | 1354 | 1275 | MiniMax M1 |
| LMArena Text: medicine and healthcare | 1355 | 1258 | MiniMax M1 |
| LMArena Text: legal and government | 1337 | 1288 | MiniMax M1 |
| LMArena Text: business and finance | 1319 | 1253 | MiniMax M1 |
| Neither model has a result on the other 13 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| IFBench | Not measured | 36.9% | Only Qwen2.5 72B Instruct measured |
| DTBench | Not measured | 62.9% | Only Qwen2.5 72B Instruct measured |
| LMCA | Not measured | 13.4% | Only Qwen2.5 72B Instruct measured |
| HellaSwag | Not measured | 84.8% | Only Qwen2.5 72B Instruct measured |
| WinoGrande | Not measured | 82.3% | Only Qwen2.5 72B Instruct measured |
| PIQA | Not measured | 82.6% | Only Qwen2.5 72B Instruct measured |
| LMArena Text | 1343 | 1269 | MiniMax M1 |
| LMArena Text: instruction following | 1312 | 1254 | MiniMax M1 |
| LMArena Text: creative writing | 1297 | 1221 | MiniMax M1 |
| LMArena Text: English | 1363 | 1283 | MiniMax M1 |
| LMArena Text: non-English | 1319 | 1252 | MiniMax M1 |
| LMArena Text: Chinese | 1360 | 1273 | MiniMax M1 |
| LMArena Text: German | 1350 | 1234 | MiniMax M1 |
| LMArena Text: Japanese | 1217 | 1180 | MiniMax M1 |
| LMArena Text: Korean | 1266 | 1188 | MiniMax M1 |
| LMArena Text: French | 1370 | 1280 | MiniMax M1 |
| LMArena Text: Spanish | 1353 | 1255 | MiniMax M1 |
| LMArena Text: Russian | 1329 | 1264 | MiniMax M1 |
| LMArena Text: Polish | 1329 | Not measured | Only MiniMax M1 measured |
| LMArena Text: multi-turn | 1335 | 1272 | MiniMax M1 |
| LMArena Text: longer queries | 1326 | 1281 | MiniMax M1 |
| LMArena Text: writing and language | 1311 | 1247 | MiniMax M1 |
| LMArena Text: entertainment and media | 1303 | 1211 | MiniMax M1 |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Qwen2.5 72B Instruct | 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
Qwen2.5 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 72B Instruct 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 | MiniMax M1 | Qwen2.5 72B Instruct |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | September 19, 2024 |
| Context window | 1M | 33K |
| Input $/Mtok | $0.40 | $0.36 |
| Output $/Mtok | $2.20 | $0.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M1 better than Qwen2.5 72B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M1 for a larger context window (1M against 33K tokens).
Which is cheaper, MiniMax M1 or Qwen2.5 72B Instruct?
MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; Qwen2.5 72B Instruct costs $0.36 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, MiniMax M1 or Qwen2.5 72B Instruct?
MiniMax M1, with 1M tokens against 33K.
How many benchmarks is the MiniMax M1 vs Qwen2.5 72B Instruct comparison based on?
28 benchmarks have a result for both models as of October 22, 2026. MiniMax M1's coding index rests on 0 independent benchmarks and Qwen2.5 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.