Noometry

Model comparison

Llama 3.1-70B vs MiMo-V2.6-Flash

MiMo-V2.6-Flash is the stronger model overall, scoring 48.5 to 29.6 on the Noometry Index.

Last verified . 14 shared benchmarks.

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

MiMo-V2.6-Flash Xiaomi

48.5

Rank #55 Confirmed

Summary

  • They share 14 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and MiMo-V2.6-Flash in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where MiMo-V2.6-Flash leads 51.9 to 13.5.
  • MiMo-V2.6-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.40 / $0.40 for Llama 3.1-70B.
  • MiMo-V2.6-Flash accepts more context: 1.05M tokens versus 128K.

Side by side

Llama 3.1-70BMiMo-V2.6-Flash
ProviderMetaXiaomi
Noometry Index29.648.5
Released2024-07-232026-09-21
WeightsOpenOpen
Context window128K1.05M
Max output4K131K
Input $ / M tokens$0.40$0.14
Output $ / M tokens$0.40$0.28
Results tracked3519

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Category by category

Coding MiMo-V2.6-Flash leads

Llama 3.1-70B: 30.3 (#296), MiMo-V2.6-Flash: 53.4 (#30)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Coding12601504
LMArena WebDev—1637
SciCode—51.3%
WeirdML9%—
BigCodeBench Instruct46.1%—
BigCodeBench Complete54.8%—

Agentic & Tool Use Not comparable

Llama 3.1-70B: 25.1 (#112), MiMo-V2.6-Flash: —

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
TheAgentCompany6.9%—
BALROG27.9%—

Reasoning MiMo-V2.6-Flash leads

Llama 3.1-70B: 21.6 (#220), MiMo-V2.6-Flash: 36.5 (#66)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Hard Prompts12411482
CritPt—12%
DTBench60%—
LMCA14.8%—
Epoch Capabilities Index125.92—

Math MiMo-V2.6-Flash leads

Llama 3.1-70B: 13.5 (#304), MiMo-V2.6-Flash: 51.9 (#52)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Math12521468
OTIS Mock AIME 2024-20253.6%—
ProofBench—63%
Omni-MATH21%—
MATH Level 536.7%—

Knowledge MiMo-V2.6-Flash leads

Llama 3.1-70B: 24.2 (#269), MiMo-V2.6-Flash: 42.2 (#99)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Expert12091501
GPQA Diamond44.2%—
MMLU-Pro65.3%—
GPQA (HELM)42.6%—
MMLU80.1%—

Multimodal Not comparable

Llama 3.1-70B: —, MiMo-V2.6-Flash: 40.5 (#47)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Vision—1259

Multilingual MiMo-V2.6-Flash leads

Llama 3.1-70B: 38.8 (#225), MiMo-V2.6-Flash: 54.0 (#51)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Non-English12191434
LMArena Chinese12151511
LMArena French12611475
LMArena Russian12341409
LMArena Spanish12531456
LMArena German1222—
LMArena Japanese1132—
LMArena Korean1140—

Instruction Following MiMo-V2.6-Flash leads

Llama 3.1-70B: 65.3 (#223), MiMo-V2.6-Flash: 76.8 (#35)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Instruction Following12311463
IFEval82.1%—

Long Context MiMo-V2.6-Flash leads

Llama 3.1-70B: 37.6 (#214), MiMo-V2.6-Flash: 44.8 (#57)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Longer Query12411463

Writing & Preference MiMo-V2.6-Flash leads

Llama 3.1-70B: 35.4 (#267), MiMo-V2.6-Flash: 63.1 (#67)

BenchmarkLlama 3.1-70BMiMo-V2.6-Flash
LMArena Text12611455
LMArena Creative Writing12321400
LMArena Multi-Turn12561451
EQ-Bench Creative Writing784—
WildBench75.8%—

Frequently asked questions

Is Llama 3.1-70B better than MiMo-V2.6-Flash?

MiMo-V2.6-Flash is the stronger model overall, scoring 48.5 to 29.6 on the Noometry Index.

Which is cheaper, Llama 3.1-70B or MiMo-V2.6-Flash?

MiMo-V2.6-Flash 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-V2.6-Flash better for coding?

MiMo-V2.6-Flash scores higher on coding benchmarks: 53.4 versus 30.3 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2.6-Flash does, with 1.05M tokens against 128K.

How many benchmarks do Llama 3.1-70B and MiMo-V2.6-Flash share?

14 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and MiMo-V2.6-Flash has 19.

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