Model comparison
MiniMax-M2.1 vs Qwen2.5 7B Instruct
MiniMax-M2.1 is the stronger model overall, scoring 38.9 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 1.7× less per token, which makes it the better buy when MiniMax-M2.1's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
MiniMax
Alibaba (Qwen)Summary
- The widest gap is in math, where MiniMax-M2.1 leads 38.3 to 12.6.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.1.
- MiniMax-M2.1 accepts more context: 205K tokens versus 131K.
Side by side
| MiniMax-M2.1 | Qwen2.5 7B Instruct | |
|---|---|---|
| Provider | MiniMax | Alibaba (Qwen) |
| Noometry Index | 38.9 | 29.0 |
| Released | 2025-12-23 | 2024-09 |
| Weights | Open | Open |
| Context window | 205K | 131K |
| Max output | 131K | 8K |
| Input $ / M tokens | $0.30 | $0.17 |
| Output $ / M tokens | $1.20 | $0.70 |
| Results tracked | 22 | 15 |
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Category by category
Coding MiniMax-M2.1 leads
MiniMax-M2.1: 40.4 (#143), Qwen2.5 7B Instruct: 36.5 (#208)
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena WebDev | 1384 | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1421 | — |
| BigCodeBench Complete | — | 46.1% |
| ALE-Bench | 623.83 | — |
Agentic & Tool Use MiniMax-M2.1 leads
MiniMax-M2.1: 27.9 (#98), Qwen2.5 7B Instruct: 23.8 (#124)
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| Terminal-Bench | 36.6% | — |
| BALROG | — | 7.8% |
Reasoning MiniMax-M2.1 leads
MiniMax-M2.1: 16.6 (#302), Qwen2.5 7B Instruct: 14.8 (#322)
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| NYT Connections (extended) | 11.2% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1411 | — |
| DTBench | — | 47.7% |
| LMCA | — | 6.4% |
| Epoch Capabilities Index | — | 118.51 |
Math MiniMax-M2.1 leads
MiniMax-M2.1: 38.3 (#138), Qwen2.5 7B Instruct: 12.6 (#306)
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.5% |
| Omni-MATH | — | 29.4% |
| LMArena Math | 1397 | — |
Knowledge MiniMax-M2.1 leads
MiniMax-M2.1: 38.3 (#147), Qwen2.5 7B Instruct: 17.0 (#286)
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | — | 35.5% |
| MMLU-Pro | — | 53.9% |
| Vectara Hallucination Rate | 11.8% | — |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1431 | — |
| MMLU | — | 72.9% |
Multilingual Not comparable
MiniMax-M2.1: 50.0 (#128), Qwen2.5 7B Instruct: —
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1378 | — |
| LMArena Chinese | 1430 | — |
| LMArena French | 1404 | — |
| LMArena German | 1381 | — |
| LMArena Japanese | 1287 | — |
| LMArena Korean | 1298 | — |
| LMArena Russian | 1387 | — |
| LMArena Spanish | 1397 | — |
Instruction Following MiniMax-M2.1 leads
MiniMax-M2.1: 73.8 (#112), Qwen2.5 7B Instruct: 63.2 (#231)
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1400 | — |
Long Context Not comparable
MiniMax-M2.1: 43.2 (#101), Qwen2.5 7B Instruct: —
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1416 | — |
Writing & Preference MiniMax-M2.1 leads
MiniMax-M2.1: 58.3 (#120), Qwen2.5 7B Instruct: 48.8 (#195)
| Benchmark | MiniMax-M2.1 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1392 | — |
| LMArena Creative Writing | 1361 | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1396 | — |
Frequently asked questions
Is MiniMax-M2.1 better than Qwen2.5 7B Instruct?
MiniMax-M2.1 is the stronger model overall, scoring 38.9 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 1.7× less per token, which makes it the better buy when MiniMax-M2.1's lead doesn't matter for your workload.
Which is cheaper, MiniMax-M2.1 or Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; MiniMax-M2.1 lists at $0.30 and $1.20.
Is MiniMax-M2.1 or Qwen2.5 7B Instruct better for coding?
MiniMax-M2.1 scores higher on coding benchmarks: 40.4 versus 36.5 in the Noometry coding category.
Which has the bigger context window?
MiniMax-M2.1 does, with 205K tokens against 131K.
How many benchmarks do MiniMax-M2.1 and Qwen2.5 7B Instruct share?
0 benchmarks have published results for both models. MiniMax-M2.1 has 22 scored results on Noometry and Qwen2.5 7B Instruct has 15.