# Llama 3.1-70B vs MiniMax-M2

> MiniMax-M2 is the stronger model overall, scoring 37.4 to 29.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-1-70b-vs-minimax-m2
- Last updated: 2026-10-12
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. Llama 3.1-70B scores higher in 1 category and MiniMax-M2 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where MiniMax-M2 leads 37.3 to 13.5.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.
- MiniMax-M2 accepts more context: 205K tokens versus 128K.

## Snapshot

| | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| Provider | Meta | MiniMax |
| Noometry Index | 29.6 | 37.4 |
| Rank | 308 | 204 |
| Context | 128K | 205K |
| Input $/M | $0.40 | $0.30 |
| Output $/M | $0.40 | $1.20 |
| Weights | Open | Open |

## Coding

- Llama 3.1-70B: 30.3 (#296)
- MiniMax-M2: 39.3 (#159)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Coding | 1260 | 1370 |
| SWE-bench Verified (bash only) | — | 61% |
| LMArena WebDev | — | 1297 |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |

## Agentic & Tool Use

- Llama 3.1-70B: 25.1 (#112)
- MiniMax-M2: 25.1 (#109)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| Terminal-Bench | — | 30% |
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
| Vending-Bench 2 | — | 160.6 |

## Reasoning

- Llama 3.1-70B: 21.6 (#220)
- MiniMax-M2: 19.4 (#258)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1357 |
| Kagi LLM Benchmark | — | 57.8% |
| NYT Connections (extended) | — | 14.8% |
| DTBench | 60% | — |
| LMCA | 14.8% | — |
| Epoch Capabilities Index | 125.92 | — |

## Math

- Llama 3.1-70B: 13.5 (#304)
- MiniMax-M2: 37.3 (#160)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Math | 1252 | 1352 |
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |

## Knowledge

- Llama 3.1-70B: 24.2 (#269)
- MiniMax-M2: 37.0 (#163)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Expert | 1209 | 1337 |
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |

## Multilingual

- Llama 3.1-70B: 38.8 (#225)
- MiniMax-M2: 45.3 (#171)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Non-English | 1219 | 1313 |
| LMArena Chinese | 1215 | 1366 |
| LMArena French | 1261 | 1335 |
| LMArena German | 1222 | 1355 |
| LMArena Russian | 1234 | 1331 |
| LMArena Spanish | 1253 | 1326 |
| LMArena Japanese | 1132 | — |
| LMArena Korean | 1140 | — |

## Instruction Following

- Llama 3.1-70B: 65.3 (#223)
- MiniMax-M2: 70.2 (#166)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Instruction Following | 1231 | 1328 |
| IFEval | 82.1% | — |

## Long Context

- Llama 3.1-70B: 37.6 (#214)
- MiniMax-M2: 40.5 (#153)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Longer Query | 1241 | 1331 |

## Writing & Preference

- Llama 3.1-70B: 35.4 (#267)
- MiniMax-M2: 53.0 (#162)

| Benchmark | Llama 3.1-70B | MiniMax-M2 |
|---|---|---|
| LMArena Text | 1261 | 1340 |
| LMArena Creative Writing | 1232 | 1286 |
| LMArena Multi-Turn | 1256 | 1361 |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |

## FAQ

### Is Llama 3.1-70B better than MiniMax-M2?

MiniMax-M2 is the stronger model overall, scoring 37.4 to 29.6 on the Noometry Index.

### Which is cheaper, Llama 3.1-70B or MiniMax-M2?

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; MiniMax-M2 lists at $0.30 and $1.20.

### Is Llama 3.1-70B or MiniMax-M2 better for coding?

MiniMax-M2 scores higher on coding benchmarks: 39.3 versus 30.3 in the Noometry coding category.

### Which has the bigger context window?

MiniMax-M2 does, with 205K tokens against 128K.

### How many benchmarks do Llama 3.1-70B and MiniMax-M2 share?

15 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and MiniMax-M2 has 21.