Noometry

Model comparison

Llama-3.3-70B-Instruct vs MiMo-V2-Omni

MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 30.6 on the Noometry Index.

Last verified . 17 shared benchmarks.

Llama-3.3-70B-Instruct Meta

30.6

Rank #291 Confirmed

MiMo-V2-Omni Xiaomi

43.6

Rank #88 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 0 categories and MiMo-V2-Omni in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where MiMo-V2-Omni leads 39.1 to 15.3.
  • Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.14 / $0.28 for MiMo-V2-Omni.
  • MiMo-V2-Omni accepts more context: 262K tokens versus 128K.
  • Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

Side by side

Llama-3.3-70B-InstructMiMo-V2-Omni
ProviderMetaXiaomi
Noometry Index30.643.6
Released2024-12-062026-03-18
WeightsOpenProprietary
Context window128K262K
Max output4K131K
Input $ / M tokens$0.10$0.14
Output $ / M tokens$0.32$0.28
Results tracked4318

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 31.0 (#290), MiMo-V2-Omni: 43.3 (#89)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Coding12681466
SciCode26%—
WeirdML14.4%—
BigCodeBench Instruct46.9%—
LiveBench Coding36.6%—
BigCodeBench Complete57.5%—

Agentic & Tool Use Not comparable

Llama-3.3-70B-Instruct: 25.8 (#105), MiMo-V2-Omni: —

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
Berkeley Function Calling Leaderboard31.9%—
BALROG23%—

Reasoning MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 14.1 (#327), MiMo-V2-Omni: 29.7 (#88)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Hard Prompts12571445
SimpleBench19.9%—
CritPt0%—
LiveBench Reasoning50.8%—
DTBench59.5%—
LiveBench Data Analysis49.5%—
LMCA17.5%—
Epoch Capabilities Index127.33—
ForecastBench58.6—
LiveBench50.2%—

Math MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 15.3 (#298), MiMo-V2-Omni: 39.1 (#115)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Math12671430
OTIS Mock AIME 2024-20255.1%—
LiveBench Math42.2%—
MATH Level 541.6%—

Knowledge MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 30.6 (#226), MiMo-V2-Omni: 40.5 (#118)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Expert12251449
GPQA Diamond47.4%—
Confabulations22.8%—
Vectara Hallucination Rate4.1%—
MMLU86.3%—

Multimodal Not comparable

Llama-3.3-70B-Instruct: —, MiMo-V2-Omni: 38.6 (#63)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Vision—1228

Multilingual MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 39.9 (#220), MiMo-V2-Omni: 51.8 (#102)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Non-English12361404
LMArena Chinese12171465
LMArena French12811447
LMArena German12511399
LMArena Japanese11501317
LMArena Korean11431355
LMArena Russian12521412
LMArena Spanish12701434

Instruction Following MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 71.1 (#157), MiMo-V2-Omni: 75.2 (#66)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Instruction Following12421428
LiveBench Instruction Following82.7%—

Long Context MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 26.4 (#295), MiMo-V2-Omni: 44.1 (#76)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Longer Query12561442
Fiction.LiveBench33.3%—

Writing & Preference MiMo-V2-Omni leads

Llama-3.3-70B-Instruct: 47.6 (#207), MiMo-V2-Omni: 61.4 (#87)

BenchmarkLlama-3.3-70B-InstructMiMo-V2-Omni
LMArena Text12741423
LMArena Creative Writing12501392
LMArena Multi-Turn12801445
LiveBench Language39.2%—

Frequently asked questions

Is Llama-3.3-70B-Instruct better than MiMo-V2-Omni?

MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 30.6 on the Noometry Index.

Which is cheaper, Llama-3.3-70B-Instruct or MiMo-V2-Omni?

Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; MiMo-V2-Omni lists at $0.14 and $0.28.

Is Llama-3.3-70B-Instruct or MiMo-V2-Omni better for coding?

MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 31.0 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-3.3-70B-Instruct and MiMo-V2-Omni share?

17 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and MiMo-V2-Omni has 18.

Related comparisons

Go deeper