Noometry

Model comparison

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

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 29.6 on the Noometry Index.

Last verified . 12 shared benchmarks.

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

MiMo-V2.6-Pro Xiaomi

50.3

Rank #49 Confirmed

Summary

  • They share 12 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and MiMo-V2.6-Pro in 9 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where MiMo-V2.6-Pro leads 54.5 to 13.5.
  • Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.6-Pro.
  • MiMo-V2.6-Pro accepts more context: 1.05M tokens versus 128K.

Side by side

Llama 3.1-70BMiMo-V2.6-Pro
ProviderMetaXiaomi
Noometry Index29.650.3
Released2024-07-232026-09-21
WeightsOpenOpen
Context window128K1.05M
Max output4K131K
Input $ / M tokens$0.40$0.43
Output $ / M tokens$0.40$0.87
Results tracked3519

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Category by category

Coding MiMo-V2.6-Pro leads

Llama 3.1-70B: 30.3 (#296), MiMo-V2.6-Pro: 55.5 (#23)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Coding12601534
LMArena WebDev—1629
SciCode—60.9%
WeirdML9%—
BigCodeBench Instruct46.1%—
BigCodeBench Complete54.8%—
ALE-Bench—1,158

Agentic & Tool Use MiMo-V2.6-Pro leads

Llama 3.1-70B: 25.1 (#112), MiMo-V2.6-Pro: 37.5 (#35)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
APEX-Agents—59.5%
TheAgentCompany6.9%—
BALROG27.9%—

Reasoning MiMo-V2.6-Pro leads

Llama 3.1-70B: 21.6 (#220), MiMo-V2.6-Pro: 43.1 (#50)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Hard Prompts12411512
CritPt—26.6%
DTBench60%—
LMCA14.8%—
Epoch Capabilities Index125.92—

Math MiMo-V2.6-Pro leads

Llama 3.1-70B: 13.5 (#304), MiMo-V2.6-Pro: 54.5 (#45)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Math12521494
OTIS Mock AIME 2024-20253.6%—
ProofBench—70%
Omni-MATH21%—
MATH Level 536.7%—

Knowledge MiMo-V2.6-Pro leads

Llama 3.1-70B: 24.2 (#269), MiMo-V2.6-Pro: 43.5 (#92)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Expert12091543
GPQA Diamond44.2%—
MMLU-Pro65.3%—
GPQA (HELM)42.6%—
MMLU80.1%—

Multimodal Not comparable

Llama 3.1-70B: —, MiMo-V2.6-Pro: 40.8 (#43)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Vision—1264

Multilingual MiMo-V2.6-Pro leads

Llama 3.1-70B: 38.8 (#225), MiMo-V2.6-Pro: 56.9 (#14)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Non-English12191474
LMArena Chinese12151529
LMArena Russian12341480
LMArena French1261—
LMArena German1222—
LMArena Japanese1132—
LMArena Korean1140—
LMArena Spanish1253—

Instruction Following MiMo-V2.6-Pro leads

Llama 3.1-70B: 65.3 (#223), MiMo-V2.6-Pro: 78.2 (#12)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Instruction Following12311493
IFEval82.1%—

Long Context MiMo-V2.6-Pro leads

Llama 3.1-70B: 37.6 (#214), MiMo-V2.6-Pro: 46.0 (#27)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Longer Query12411501

Writing & Preference MiMo-V2.6-Pro leads

Llama 3.1-70B: 35.4 (#267), MiMo-V2.6-Pro: 66.8 (#33)

BenchmarkLlama 3.1-70BMiMo-V2.6-Pro
LMArena Text12611492
LMArena Creative Writing12321468
LMArena Multi-Turn12561464
EQ-Bench Creative Writing784—
WildBench75.8%—

Frequently asked questions

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

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 29.6 on the Noometry Index.

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

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; MiMo-V2.6-Pro lists at $0.43 and $0.87.

Is Llama 3.1-70B or MiMo-V2.6-Pro better for coding?

MiMo-V2.6-Pro scores higher on coding benchmarks: 55.5 versus 30.3 in the Noometry coding category.

Which has the bigger context window?

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

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

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

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