Model comparison
Llama 4 Maverick vs MiniMax-M2.7
MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 30.9 on the Noometry Index. Llama 4 Maverick costs 1.7× less per token, which makes it the better buy when MiniMax-M2.7's lead doesn't matter for your workload.
Last verified . 24 shared benchmarks.
Meta
MiniMaxSummary
- They share 24 benchmarks with published results for both. Llama 4 Maverick scores higher in 2 categories 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 38.8.
- The biggest single-benchmark swing is NYT Connections (extended): 8% for Llama 4 Maverick and 24.7% for MiniMax-M2.7.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.7.
- MiniMax-M2.7 accepts more context: 205K tokens versus 128K.
Side by side
| Llama 4 Maverick | MiniMax-M2.7 | |
|---|---|---|
| Provider | Meta | MiniMax |
| Noometry Index | 30.9 | 37.7 |
| Released | 2025-04-05 | 2026-03-18 |
| Weights | Open | Open |
| Context window | 128K | 205K |
| Max output | 4K | 131K |
| Input $ / M tokens | $0.19 | $0.30 |
| Output $ / M tokens | $0.65 | $1.20 |
| Results tracked | 54 | 30 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding MiniMax-M2.7 leads
Llama 4 Maverick: 26.6 (#324), MiniMax-M2.7: 41.8 (#120)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| SciCode | 33.1% | 47% |
| WeirdML | 24.5% | 37% |
| LMArena Coding | 1302 | 1454 |
| ALE-Bench | 172.97 | 599.25 |
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| LMArena WebDev | — | 1398 |
| BigCodeBench Instruct | 49.7% | — |
| BigCodeBench Complete | 61.4% | — |
Agentic & Tool Use Llama 4 Maverick leads
Llama 4 Maverick: 28.2 (#91), MiniMax-M2.7: 25.1 (#111)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| Terminal-Bench | — | 45.1% |
| Berkeley Function Calling Leaderboard | 37.3% | — |
| ExploitBench | — | 13.3% |
| GBAEval | — | 0% |
Reasoning MiniMax-M2.7 leads
Llama 4 Maverick: 10.1 (#342), MiniMax-M2.7: 19.7 (#253)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| NYT Connections (extended) | 8% | 24.7% |
| CritPt | 0% | 0.6% |
| LMArena Hard Prompts | 1281 | 1422 |
| Epoch Capabilities Index | 132.2 | 145.85 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| Kagi LLM Benchmark | 55.9% | — |
| ARC-AGI-1 | 4.4% | — |
| EnigmaEval | 0.6% | — |
| Thematic Generalization | — | 39.3% |
| DTBench | 61.9% | — |
| LMCA | 15.9% | — |
| ForecastBench | 57.5 | — |
Math Too close to call
Llama 4 Maverick: 26.0 (#262), MiniMax-M2.7: 25.9 (#263)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Math | 1299 | 1420 |
| OTIS Mock AIME 2024-2025 | 20.6% | — |
| ProofBench | — | 3% |
| Omni-MATH | 42.2% | — |
| MATH Level 5 | 73% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |
Knowledge MiniMax-M2.7 leads
Llama 4 Maverick: 33.4 (#204), MiniMax-M2.7: 37.7 (#152)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| Vectara Hallucination Rate | 8.2% | 12.9% |
| LMArena Expert | 1259 | 1444 |
| GPQA Diamond | 67% | — |
| Humanity's Last Exam | 5.7% | — |
| MMLU-Pro | 81% | — |
| Confabulations | 22.6% | — |
| GPQA (HELM) | 65% | — |
Multimodal Not comparable
Llama 4 Maverick: 31.6 (#105), MiniMax-M2.7: —
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Vision | 1142 | — |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |
Multilingual MiniMax-M2.7 leads
Llama 4 Maverick: 42.2 (#195), MiniMax-M2.7: 50.3 (#123)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Non-English | 1269 | 1382 |
| LMArena Chinese | 1277 | 1441 |
| LMArena French | 1259 | 1421 |
| LMArena German | 1291 | 1398 |
| LMArena Japanese | 1207 | 1262 |
| LMArena Korean | 1203 | 1313 |
| LMArena Russian | 1286 | 1383 |
| LMArena Spanish | 1293 | 1403 |
Instruction Following MiniMax-M2.7 leads
Llama 4 Maverick: 71.7 (#146), MiniMax-M2.7: 74.1 (#103)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1405 |
| IFEval | 90.8% | — |
Long Context MiniMax-M2.7 leads
Llama 4 Maverick: 31.4 (#279), MiniMax-M2.7: 43.3 (#99)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Longer Query | 1280 | 1419 |
| Fiction.LiveBench | 46.2% | — |
Writing & Preference MiniMax-M2.7 leads
Llama 4 Maverick: 38.8 (#252), MiniMax-M2.7: 58.9 (#112)
| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Text | 1287 | 1405 |
| LMArena Creative Writing | 1267 | 1354 |
| LMArena Multi-Turn | 1289 | 1412 |
| Short-Story Creative Writing | 62% | — |
| EQ-Bench Creative Writing | 860 | — |
| WildBench | 80% | — |
Frequently asked questions
Is Llama 4 Maverick better than MiniMax-M2.7?
MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 30.9 on the Noometry Index. Llama 4 Maverick costs 1.7× less per token, which makes it the better buy when MiniMax-M2.7's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Maverick or MiniMax-M2.7?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; MiniMax-M2.7 lists at $0.30 and $1.20.
Is Llama 4 Maverick or MiniMax-M2.7 better for coding?
MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 26.6 in the Noometry coding category.
Which has the bigger context window?
MiniMax-M2.7 does, with 205K tokens against 128K.
How many benchmarks do Llama 4 Maverick and MiniMax-M2.7 share?
24 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and MiniMax-M2.7 has 30.