Noometry

Model comparison

Llama 3.1-70B vs MiMo-V2-Omni

MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 29.6 on the Noometry Index.

Last verified . 17 shared benchmarks.

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

MiMo-V2-Omni Xiaomi

43.6

Rank #88 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and MiMo-V2-Omni in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where MiMo-V2-Omni leads 61.4 to 35.4.
  • MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.40 / $0.40 for Llama 3.1-70B.
  • MiMo-V2-Omni accepts more context: 262K tokens versus 128K.
  • Llama 3.1-70B has downloadable open weights; the other is API-only.

Side by side

Llama 3.1-70BMiMo-V2-Omni
ProviderMetaXiaomi
Noometry Index29.643.6
Released2024-07-232026-03-18
WeightsOpenProprietary
Context window128K262K
Max output4K131K
Input $ / M tokens$0.40$0.14
Output $ / M tokens$0.40$0.28
Results tracked3518

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Category by category

Coding MiMo-V2-Omni leads

Llama 3.1-70B: 30.3 (#296), MiMo-V2-Omni: 43.3 (#89)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Coding12601466
WeirdML9%—
BigCodeBench Instruct46.1%—
BigCodeBench Complete54.8%—

Agentic & Tool Use Not comparable

Llama 3.1-70B: 25.1 (#112), MiMo-V2-Omni: —

BenchmarkLlama 3.1-70BMiMo-V2-Omni
TheAgentCompany6.9%—
BALROG27.9%—

Reasoning MiMo-V2-Omni leads

Llama 3.1-70B: 21.6 (#220), MiMo-V2-Omni: 29.7 (#88)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Hard Prompts12411445
DTBench60%—
LMCA14.8%—
Epoch Capabilities Index125.92—

Math MiMo-V2-Omni leads

Llama 3.1-70B: 13.5 (#304), MiMo-V2-Omni: 39.1 (#115)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Math12521430
OTIS Mock AIME 2024-20253.6%—
Omni-MATH21%—
MATH Level 536.7%—

Knowledge MiMo-V2-Omni leads

Llama 3.1-70B: 24.2 (#269), MiMo-V2-Omni: 40.5 (#118)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Expert12091449
GPQA Diamond44.2%—
MMLU-Pro65.3%—
GPQA (HELM)42.6%—
MMLU80.1%—

Multimodal Not comparable

Llama 3.1-70B: —, MiMo-V2-Omni: 38.6 (#63)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Vision—1228

Multilingual MiMo-V2-Omni leads

Llama 3.1-70B: 38.8 (#225), MiMo-V2-Omni: 51.8 (#102)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Non-English12191404
LMArena Chinese12151465
LMArena French12611447
LMArena German12221399
LMArena Japanese11321317
LMArena Korean11401355
LMArena Russian12341412
LMArena Spanish12531434

Instruction Following MiMo-V2-Omni leads

Llama 3.1-70B: 65.3 (#223), MiMo-V2-Omni: 75.2 (#66)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Instruction Following12311428
IFEval82.1%—

Long Context MiMo-V2-Omni leads

Llama 3.1-70B: 37.6 (#214), MiMo-V2-Omni: 44.1 (#76)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Longer Query12411442

Writing & Preference MiMo-V2-Omni leads

Llama 3.1-70B: 35.4 (#267), MiMo-V2-Omni: 61.4 (#87)

BenchmarkLlama 3.1-70BMiMo-V2-Omni
LMArena Text12611423
LMArena Creative Writing12321392
LMArena Multi-Turn12561445
EQ-Bench Creative Writing784—
WildBench75.8%—

Frequently asked questions

Is Llama 3.1-70B better than MiMo-V2-Omni?

MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 29.6 on the Noometry Index.

Which is cheaper, Llama 3.1-70B or MiMo-V2-Omni?

MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Llama 3.1-70B lists at $0.40 and $0.40.

Is Llama 3.1-70B or MiMo-V2-Omni better for coding?

MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 30.3 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Omni does, with 262K tokens against 128K.

How many benchmarks do Llama 3.1-70B and MiMo-V2-Omni share?

17 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and MiMo-V2-Omni has 18.

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