Model comparison
Llama 3.1-70B vs MiMo-V2.5-Pro
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 29.6 on the Noometry Index.
Last verified . 20 shared benchmarks.
MetaSummary
- They share 20 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and MiMo-V2.5-Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2.5-Pro leads 65.3 to 35.4.
- The biggest single-benchmark swing is DTBench: 60% for Llama 3.1-70B and 84.5% for MiMo-V2.5-Pro.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.5-Pro.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 128K.
Side by side
| Llama 3.1-70B | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | Meta | Xiaomi |
| Noometry Index | 29.6 | 45.2 |
| Released | 2024-07-23 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 128K | 1.05M |
| Max output | 4K | 131K |
| Input $ / M tokens | $0.40 | $0.43 |
| Output $ / M tokens | $0.40 | $0.87 |
| Results tracked | 35 | 27 |
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Category by category
Coding MiMo-V2.5-Pro leads
Llama 3.1-70B: 30.3 (#296), MiMo-V2.5-Pro: 47.4 (#60)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Coding | 1260 | 1503 |
| LMArena WebDev | — | 1479 |
| SciCode | — | 50.2% |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
| ALE-Bench | — | 899.8 |
Agentic & Tool Use Not comparable
Llama 3.1-70B: 25.1 (#112), MiMo-V2.5-Pro: —
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
Reasoning MiMo-V2.5-Pro leads
Llama 3.1-70B: 21.6 (#220), MiMo-V2.5-Pro: 26.8 (#130)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1488 |
| DTBench | 60% | 84.5% |
| LMCA | 14.8% | 29.5% |
| NYT Connections (extended) | — | 34.4% |
| CritPt | — | 4% |
| Epoch Capabilities Index | 125.92 | — |
Math MiMo-V2.5-Pro leads
Llama 3.1-70B: 13.5 (#304), MiMo-V2.5-Pro: 40.0 (#96)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Math | 1252 | 1481 |
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| ProofBench | — | 22% |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |
Knowledge MiMo-V2.5-Pro leads
Llama 3.1-70B: 24.2 (#269), MiMo-V2.5-Pro: 42.2 (#98)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1209 | 1503 |
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |
Multilingual MiMo-V2.5-Pro leads
Llama 3.1-70B: 38.8 (#225), MiMo-V2.5-Pro: 55.1 (#34)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1219 | 1449 |
| LMArena Chinese | 1215 | 1507 |
| LMArena French | 1261 | 1488 |
| LMArena German | 1222 | 1458 |
| LMArena Japanese | 1132 | 1412 |
| LMArena Korean | 1140 | 1437 |
| LMArena Russian | 1234 | 1450 |
| LMArena Spanish | 1253 | 1471 |
Instruction Following MiMo-V2.5-Pro leads
Llama 3.1-70B: 65.3 (#223), MiMo-V2.5-Pro: 77.5 (#21)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1231 | 1477 |
| IFEval | 82.1% | — |
Long Context MiMo-V2.5-Pro leads
Llama 3.1-70B: 37.6 (#214), MiMo-V2.5-Pro: 45.4 (#37)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1241 | 1483 |
Writing & Preference MiMo-V2.5-Pro leads
Llama 3.1-70B: 35.4 (#267), MiMo-V2.5-Pro: 65.3 (#49)
| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1261 | 1465 |
| LMArena Creative Writing | 1232 | 1440 |
| EQ-Bench Creative Writing | 784 | 1493 |
| LMArena Multi-Turn | 1256 | 1477 |
| WildBench | 75.8% | — |
| EQ-Bench 4 | — | 1208 |
Frequently asked questions
Is Llama 3.1-70B better than MiMo-V2.5-Pro?
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 29.6 on the Noometry Index.
Which is cheaper, Llama 3.1-70B or MiMo-V2.5-Pro?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; MiMo-V2.5-Pro lists at $0.43 and $0.87.
Is Llama 3.1-70B or MiMo-V2.5-Pro better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.4 versus 30.3 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 128K.
How many benchmarks do Llama 3.1-70B and MiMo-V2.5-Pro share?
20 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and MiMo-V2.5-Pro has 27.