Model comparison
Llama 13b vs MiniMax-M2.7
MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 24.4 on the Noometry Index.
Last verified . 9 shared benchmarks.
Meta
MiniMaxSummary
- They share 9 benchmarks with published results for both. Llama 13b scores higher in 1 category and MiniMax-M2.7 in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiniMax-M2.7 leads 58.9 to 13.8.
Side by side
| Llama 13b | MiniMax-M2.7 | |
|---|---|---|
| Provider | Meta | MiniMax |
| Noometry Index | 24.4 | 37.7 |
| Released | 2023-02-24 | 2026-03-18 |
| Weights | Open | Open |
| Context window | — | 205K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.30 |
| Output $ / M tokens | — | $1.20 |
| Results tracked | 21 | 30 |
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Category by category
Coding MiniMax-M2.7 leads
Llama 13b: 21.4 (#337), MiniMax-M2.7: 41.8 (#120)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| LMArena Coding | 683 | 1454 |
| LMArena WebDev | — | 1398 |
| SciCode | — | 47% |
| WeirdML | — | 37% |
| ALE-Bench | — | 599.25 |
Agentic & Tool Use Not comparable
Llama 13b: —, MiniMax-M2.7: 25.1 (#111)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| Terminal-Bench | — | 45.1% |
| ExploitBench | — | 13.3% |
| GBAEval | — | 0% |
Reasoning MiniMax-M2.7 leads
Llama 13b: 14.0 (#329), MiniMax-M2.7: 19.7 (#253)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| LMArena Hard Prompts | 728 | 1422 |
| Epoch Capabilities Index | 100.58 | 145.85 |
| NYT Connections (extended) | — | 24.7% |
| CritPt | — | 0.6% |
| Thematic Generalization | — | 39.3% |
| BIG-Bench Hard | 37.9% | — |
| HellaSwag | 79.2% | — |
| LAMBADA | 75.2% | — |
| PIQA | 80.1% | — |
| WinoGrande | 73% | — |
Math Too close to call
Llama 13b: 26.7 (#256), MiniMax-M2.7: 25.9 (#263)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| LMArena Math | 838 | 1420 |
| ProofBench | — | 3% |
| GSM8K | 20.6% | — |
Knowledge Not comparable
Llama 13b: —, MiniMax-M2.7: 37.7 (#152)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| Vectara Hallucination Rate | — | 12.9% |
| LMArena Expert | — | 1444 |
| ARC (AI2) Challenge | 52.7% | — |
| BoolQ | 78.7% | — |
| MMLU | 47.7% | — |
| OpenBookQA | 56.4% | — |
| TriviaQA | 77.9% | — |
Multimodal Not comparable
Llama 13b: —, MiniMax-M2.7: —
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| ScienceQA | 43.3% | — |
Multilingual MiniMax-M2.7 leads
Llama 13b: 16.6 (#297), MiniMax-M2.7: 50.3 (#123)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| LMArena Non-English | 819 | 1382 |
| LMArena Chinese | — | 1441 |
| LMArena French | — | 1421 |
| LMArena German | — | 1398 |
| LMArena Japanese | — | 1262 |
| LMArena Korean | — | 1313 |
| LMArena Russian | — | 1383 |
| LMArena Spanish | — | 1403 |
Instruction Following MiniMax-M2.7 leads
Llama 13b: 36.7 (#305), MiniMax-M2.7: 74.1 (#103)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| LMArena Instruction Following | 781 | 1405 |
Long Context Not comparable
Llama 13b: —, MiniMax-M2.7: 43.3 (#99)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| LMArena Longer Query | — | 1419 |
Writing & Preference MiniMax-M2.7 leads
Llama 13b: 13.8 (#312), MiniMax-M2.7: 58.9 (#112)
| Benchmark | Llama 13b | MiniMax-M2.7 |
|---|---|---|
| LMArena Text | 834 | 1405 |
| LMArena Creative Writing | 794 | 1354 |
| LMArena Multi-Turn | 753 | 1412 |
Frequently asked questions
Is Llama 13b better than MiniMax-M2.7?
MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 24.4 on the Noometry Index.
Is Llama 13b or MiniMax-M2.7 better for coding?
MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 21.4 in the Noometry coding category.
How many benchmarks do Llama 13b and MiniMax-M2.7 share?
9 benchmarks have published results for both models. Llama 13b has 21 scored results on Noometry and MiniMax-M2.7 has 30.