Model comparison
Llama 2-7B vs MiniMax-M2.7
MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 29.1 on the Noometry Index.
Last verified . 16 shared benchmarks.
Meta
MiniMaxSummary
- They share 16 benchmarks with published results for both. Llama 2-7B scores higher in 1 category and MiniMax-M2.7 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiniMax-M2.7 leads 58.9 to 28.0.
Side by side
| Llama 2-7B | MiniMax-M2.7 | |
|---|---|---|
| Provider | Meta | MiniMax |
| Noometry Index | 29.1 | 37.7 |
| Released | 2023-07-18 | 2026-03-18 |
| Weights | Open | Open |
| Context window | — | 205K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.30 |
| Output $ / M tokens | — | $1.20 |
| Results tracked | 29 | 30 |
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Category by category
Coding MiniMax-M2.7 leads
Llama 2-7B: 29.2 (#307), MiniMax-M2.7: 41.8 (#120)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Coding | 1002 | 1454 |
| LMArena WebDev | — | 1398 |
| SciCode | — | 47% |
| WeirdML | — | 37% |
| ALE-Bench | — | 599.25 |
Agentic & Tool Use Not comparable
Llama 2-7B: —, MiniMax-M2.7: 25.1 (#111)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| Terminal-Bench | — | 45.1% |
| ExploitBench | — | 13.3% |
| GBAEval | — | 0% |
Reasoning MiniMax-M2.7 leads
Llama 2-7B: 15.7 (#312), MiniMax-M2.7: 19.7 (#253)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Hard Prompts | 1009 | 1422 |
| Epoch Capabilities Index | 99.06 | 145.85 |
| NYT Connections (extended) | — | 24.7% |
| CritPt | — | 0.6% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 39.3% |
| BIG-Bench Hard | 39.2% | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Llama 2-7B leads
Llama 2-7B: 30.7 (#233), MiniMax-M2.7: 25.9 (#263)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Math | 1042 | 1420 |
| ProofBench | — | 3% |
| GSM8K | 16.7% | — |
Knowledge MiniMax-M2.7 leads
Llama 2-7B: 28.2 (#248), MiniMax-M2.7: 37.7 (#152)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Expert | 1036 | 1444 |
| Vectara Hallucination Rate | — | 12.9% |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| MMLU | 45.8% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, MiniMax-M2.7: —
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| ScienceQA | 43.1% | — |
Multilingual MiniMax-M2.7 leads
Llama 2-7B: 23.8 (#293), MiniMax-M2.7: 50.3 (#123)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Non-English | 973 | 1382 |
| LMArena Chinese | 973 | 1441 |
| LMArena French | 970 | 1421 |
| LMArena German | 978 | 1398 |
| LMArena Russian | 995 | 1383 |
| LMArena Spanish | 1007 | 1403 |
| LMArena Japanese | — | 1262 |
| LMArena Korean | — | 1313 |
Instruction Following MiniMax-M2.7 leads
Llama 2-7B: 50.8 (#298), MiniMax-M2.7: 74.1 (#103)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Instruction Following | 1006 | 1405 |
Long Context MiniMax-M2.7 leads
Llama 2-7B: 30.4 (#287), MiniMax-M2.7: 43.3 (#99)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Longer Query | 999 | 1419 |
Writing & Preference MiniMax-M2.7 leads
Llama 2-7B: 28.0 (#298), MiniMax-M2.7: 58.9 (#112)
| Benchmark | Llama 2-7B | MiniMax-M2.7 |
|---|---|---|
| LMArena Text | 1053 | 1405 |
| LMArena Creative Writing | 1033 | 1354 |
| LMArena Multi-Turn | 1029 | 1412 |
Frequently asked questions
Is Llama 2-7B better than MiniMax-M2.7?
MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 29.1 on the Noometry Index.
Is Llama 2-7B or MiniMax-M2.7 better for coding?
MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and MiniMax-M2.7 share?
16 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and MiniMax-M2.7 has 30.