Noometry

Model comparison

Llama-3.3-70B-Instruct vs Yi-34B

Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 27.8 on the Noometry Index.

Last verified . 21 shared benchmarks.

Llama-3.3-70B-Instruct Meta

30.6

Rank #291 Confirmed

Yi-34B 01.AI

27.8

Rank #329 Confirmed

Summary

  • They share 21 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 4 categories and Yi-34B in 4 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Llama-3.3-70B-Instruct leads 30.6 to 7.5.
  • The biggest single-benchmark swing is MATH Level 5: 41.6% for Llama-3.3-70B-Instruct and 5.1% for Yi-34B.

Side by side

Llama-3.3-70B-InstructYi-34B
ProviderMeta01.AI
Noometry Index30.627.8
Released2024-12-062023-11-02
WeightsOpenOpen
Context window128K—
Max output4K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.32—
Results tracked4323

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Category by category

Coding Yi-34B leads

Llama-3.3-70B-Instruct: 31.0 (#290), Yi-34B: 32.3 (#274)

BenchmarkLlama-3.3-70B-InstructYi-34B
LMArena Coding12681112
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), Yi-34B: —

BenchmarkLlama-3.3-70B-InstructYi-34B
Berkeley Function Calling Leaderboard31.9%—
BALROG23%—

Reasoning Yi-34B leads

Llama-3.3-70B-Instruct: 14.1 (#327), Yi-34B: 21.2 (#226)

BenchmarkLlama-3.3-70B-InstructYi-34B
LMArena Hard Prompts12571104
Epoch Capabilities Index127.33117.39
SimpleBench19.9%—
CritPt0%—
LiveBench Reasoning50.8%—
DTBench59.5%—
LiveBench Data Analysis49.5%—
LMCA17.5%—
BIG-Bench Hard—71.7%
ForecastBench58.6—
LiveBench50.2%—

Math Yi-34B leads

Llama-3.3-70B-Instruct: 15.3 (#298), Yi-34B: 21.6 (#282)

BenchmarkLlama-3.3-70B-InstructYi-34B
LMArena Math12671114
MATH Level 541.6%5.1%
OTIS Mock AIME 2024-20255.1%—
LiveBench Math42.2%—
GSM8K—76%

Knowledge Llama-3.3-70B-Instruct leads

Llama-3.3-70B-Instruct: 30.6 (#226), Yi-34B: 7.5 (#309)

BenchmarkLlama-3.3-70B-InstructYi-34B
GPQA Diamond47.4%14.7%
LMArena Expert12251061
MMLU86.3%76.3%
Confabulations22.8%—
Vectara Hallucination Rate4.1%—

Multilingual Llama-3.3-70B-Instruct leads

Llama-3.3-70B-Instruct: 39.9 (#220), Yi-34B: 29.7 (#264)

BenchmarkLlama-3.3-70B-InstructYi-34B
LMArena Non-English12361079
LMArena Chinese12171176
LMArena French12811081
LMArena German12511042
LMArena Japanese1150993
LMArena Korean1143959
LMArena Russian12521050
LMArena Spanish12701070

Instruction Following Llama-3.3-70B-Instruct leads

Llama-3.3-70B-Instruct: 71.1 (#157), Yi-34B: 56.2 (#274)

BenchmarkLlama-3.3-70B-InstructYi-34B
LMArena Instruction Following12421091
LiveBench Instruction Following82.7%—

Long Context Yi-34B leads

Llama-3.3-70B-Instruct: 26.4 (#295), Yi-34B: 33.2 (#264)

BenchmarkLlama-3.3-70B-InstructYi-34B
LMArena Longer Query12561094
Fiction.LiveBench33.3%—

Writing & Preference Llama-3.3-70B-Instruct leads

Llama-3.3-70B-Instruct: 47.6 (#207), Yi-34B: 34.1 (#273)

BenchmarkLlama-3.3-70B-InstructYi-34B
LMArena Text12741129
LMArena Creative Writing12501108
LMArena Multi-Turn12801113
LiveBench Language39.2%—

Frequently asked questions

Is Llama-3.3-70B-Instruct better than Yi-34B?

Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 27.8 on the Noometry Index.

Is Llama-3.3-70B-Instruct or Yi-34B better for coding?

Yi-34B scores higher on coding benchmarks: 32.3 versus 31.0 in the Noometry coding category.

How many benchmarks do Llama-3.3-70B-Instruct and Yi-34B share?

21 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Yi-34B has 23.

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