Noometry

Model comparison

Llama-3.3-70B-Instruct vs Qwen1.5-110B

Qwen1.5-110B is the stronger model overall, scoring 34.2 to 30.6 on the Noometry Index.

Last verified . 20 shared benchmarks.

Llama-3.3-70B-Instruct Meta

30.6

Rank #291 Confirmed

Qwen1.5-110B Alibaba (Qwen)

34.2

Rank #234 Confirmed

Summary

  • They share 20 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 3 categories and Qwen1.5-110B in 5 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen1.5-110B leads 33.7 to 15.3.
  • The biggest single-benchmark swing is BigCodeBench Complete: 57.5% for Llama-3.3-70B-Instruct and 44.4% for Qwen1.5-110B.

Side by side

Llama-3.3-70B-InstructQwen1.5-110B
ProviderMetaAlibaba (Qwen)
Noometry Index30.634.2
Released2024-12-062024-04-25
WeightsOpenOpen
Context window128K—
Max output4K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.32—
Results tracked4320

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Category by category

Coding Qwen1.5-110B leads

Llama-3.3-70B-Instruct: 31.0 (#290), Qwen1.5-110B: 33.0 (#264)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
BigCodeBench Instruct46.9%35%
LMArena Coding12681184
BigCodeBench Complete57.5%44.4%
SciCode26%—
WeirdML14.4%—
LiveBench Coding36.6%—

Agentic & Tool Use Not comparable

Llama-3.3-70B-Instruct: 25.8 (#105), Qwen1.5-110B: —

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
Berkeley Function Calling Leaderboard31.9%—
BALROG23%—

Reasoning Qwen1.5-110B leads

Llama-3.3-70B-Instruct: 14.1 (#327), Qwen1.5-110B: 22.7 (#189)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
LMArena Hard Prompts12571168
ForecastBench58.657.7
SimpleBench19.9%—
CritPt0%—
LiveBench Reasoning50.8%—
DTBench59.5%—
LiveBench Data Analysis49.5%—
LMCA17.5%—
Epoch Capabilities Index127.33—
LiveBench50.2%—

Math Qwen1.5-110B leads

Llama-3.3-70B-Instruct: 15.3 (#298), Qwen1.5-110B: 33.7 (#201)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
LMArena Math12671185
OTIS Mock AIME 2024-20255.1%—
LiveBench Math42.2%—
MATH Level 541.6%—

Knowledge Too close to call

Llama-3.3-70B-Instruct: 30.6 (#226), Qwen1.5-110B: 31.2 (#219)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
LMArena Expert12251144
GPQA Diamond47.4%—
Confabulations22.8%—
Vectara Hallucination Rate4.1%—
MMLU86.3%—

Multilingual Llama-3.3-70B-Instruct leads

Llama-3.3-70B-Instruct: 39.9 (#220), Qwen1.5-110B: 33.6 (#250)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
LMArena Non-English12361142
LMArena Chinese12171206
LMArena French12811151
LMArena German12511123
LMArena Japanese11501074
LMArena Korean11431044
LMArena Russian12521118
LMArena Spanish12701142

Instruction Following Llama-3.3-70B-Instruct leads

Llama-3.3-70B-Instruct: 71.1 (#157), Qwen1.5-110B: 60.3 (#252)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
LMArena Instruction Following12421158
LiveBench Instruction Following82.7%—

Long Context Qwen1.5-110B leads

Llama-3.3-70B-Instruct: 26.4 (#295), Qwen1.5-110B: 35.1 (#242)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
LMArena Longer Query12561157
Fiction.LiveBench33.3%—

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

Llama-3.3-70B-Instruct: 47.6 (#207), Qwen1.5-110B: 38.0 (#255)

BenchmarkLlama-3.3-70B-InstructQwen1.5-110B
LMArena Text12741175
LMArena Creative Writing12501148
LMArena Multi-Turn12801160
LiveBench Language39.2%—

Frequently asked questions

Is Llama-3.3-70B-Instruct better than Qwen1.5-110B?

Qwen1.5-110B is the stronger model overall, scoring 34.2 to 30.6 on the Noometry Index.

Is Llama-3.3-70B-Instruct or Qwen1.5-110B better for coding?

Qwen1.5-110B scores higher on coding benchmarks: 33.0 versus 31.0 in the Noometry coding category.

How many benchmarks do Llama-3.3-70B-Instruct and Qwen1.5-110B share?

20 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Qwen1.5-110B has 20.

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