Model comparison
Llama 4 Scout vs MiniMax M1
MiniMax M1 is the stronger model overall, scoring 39.7 to 27.4 on the Noometry Index. Llama 4 Scout costs 5.7× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Meta
MiniMaxSummary
- They share 18 benchmarks with published results for both. Llama 4 Scout scores higher in 0 categories and MiniMax M1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where MiniMax M1 leads 39.2 to 19.9.
- The biggest single-benchmark swing is Fiction.LiveBench: 36% for Llama 4 Scout and 69.4% for MiniMax M1.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.40 / $2.20 for MiniMax M1.
- MiniMax M1 accepts more context: 1M tokens versus 128K.
Side by side
| Llama 4 Scout | MiniMax M1 | |
|---|---|---|
| Provider | Meta | MiniMax |
| Noometry Index | 27.4 | 39.7 |
| Released | 2025-04-05 | 2025-06-13 |
| Weights | Open | Open |
| Context window | 128K | 1M |
| Max output | 4K | 40K |
| Input $ / M tokens | $0.10 | $0.40 |
| Output $ / M tokens | $0.30 | $2.20 |
| Results tracked | 43 | 18 |
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Category by category
Coding MiniMax M1 leads
Llama 4 Scout: 19.9 (#334), MiniMax M1: 39.2 (#149)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Coding | 1286 | 1359 |
| SWE-bench Verified (bash only) | 9.1% | — |
| SciCode | 17% | — |
| BigCodeBench Complete | 43.1% | — |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.4 (#109), MiniMax M1: —
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning MiniMax M1 leads
Llama 4 Scout: 9.2 (#339), MiniMax M1: 25.8 (#125)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Hard Prompts | 1266 | 1340 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 36.9% | — |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| DTBench | 57.9% | — |
| LMCA | 12% | — |
| Epoch Capabilities Index | 129.64 | — |
| ForecastBench | 57.5 | — |
Math MiniMax M1 leads
Llama 4 Scout: 18.4 (#280), MiniMax M1: 34.8 (#152)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Math | 1286 | 1360 |
| OTIS Mock AIME 2024-2025 | 7.8% | — |
| Omni-MATH | 37.3% | — |
| MATH Level 5 | 62.3% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
Knowledge MiniMax M1 leads
Llama 4 Scout: 31.8 (#208), MiniMax M1: 35.7 (#168)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Expert | 1236 | 1316 |
| GPQA Diamond | 51.8% | — |
| MMLU-Pro | 74.2% | — |
| Vectara Hallucination Rate | 7.7% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Not comparable
Llama 4 Scout: 31.6 (#98), MiniMax M1: —
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual MiniMax M1 leads
Llama 4 Scout: 41.3 (#207), MiniMax M1: 46.0 (#157)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Non-English | 1253 | 1320 |
| LMArena Chinese | 1256 | 1361 |
| LMArena French | 1283 | 1369 |
| LMArena German | 1274 | 1350 |
| LMArena Japanese | 1209 | 1220 |
| LMArena Korean | 1207 | 1263 |
| LMArena Russian | 1263 | 1330 |
| LMArena Spanish | 1277 | 1354 |
Instruction Following MiniMax M1 leads
Llama 4 Scout: 66.0 (#212), MiniMax M1: 69.5 (#169)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Instruction Following | 1248 | 1312 |
| IFEval | 81.8% | — |
Long Context MiniMax M1 leads
Llama 4 Scout: 27.5 (#289), MiniMax M1: 41.4 (#136)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| Fiction.LiveBench | 36% | 69.4% |
| LMArena Longer Query | 1265 | 1326 |
Writing & Preference MiniMax M1 leads
Llama 4 Scout: 37.1 (#256), MiniMax M1: 53.3 (#155)
| Benchmark | Llama 4 Scout | MiniMax M1 |
|---|---|---|
| LMArena Text | 1279 | 1343 |
| LMArena Creative Writing | 1249 | 1298 |
| LMArena Multi-Turn | 1281 | 1335 |
| EQ-Bench Creative Writing | 783 | — |
| WildBench | 78% | — |
Frequently asked questions
Is Llama 4 Scout better than MiniMax M1?
MiniMax M1 is the stronger model overall, scoring 39.7 to 27.4 on the Noometry Index. Llama 4 Scout costs 5.7× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Scout or MiniMax M1?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; MiniMax M1 lists at $0.40 and $2.20.
Is Llama 4 Scout or MiniMax M1 better for coding?
MiniMax M1 scores higher on coding benchmarks: 39.2 versus 19.9 in the Noometry coding category.
Which has the bigger context window?
MiniMax M1 does, with 1M tokens against 128K.
How many benchmarks do Llama 4 Scout and MiniMax M1 share?
18 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and MiniMax M1 has 18.