Noometry

Model comparison

Llama-3.3-70B-Instruct vs Qwen2.5-Max

Qwen2.5-Max is the stronger model overall, scoring 40.1 to 30.3 on the Noometry Index.

Last verified . 26 shared benchmarks.

Llama-3.3-70B-Instruct Meta

30.3

Rank #283 Confirmed

Qwen2.5-Max Alibaba (Qwen)

40.1

Rank #142 Confirmed

Summary

  • They share 26 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 0 categories and Qwen2.5-Max in 8 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen2.5-Max leads 34.3 to 14.3.
  • The biggest single-benchmark swing is LiveBench Coding: 36.6% for Llama-3.3-70B-Instruct and 64.4% for Qwen2.5-Max.
  • Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

Side by side

Llama-3.3-70B-InstructQwen2.5-Max
ProviderMetaAlibaba (Qwen)
Noometry Index30.340.1
Released2024-12-062025-01-25
WeightsOpenProprietary
Context window128K—
Max output4K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.32—
Results tracked4327

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Category by category

Coding Qwen2.5-Max leads

Llama-3.3-70B-Instruct: 30.6 (#284), Qwen2.5-Max: 41.2 (#118)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
LiveBench Coding36.6%64.4%
LMArena Coding12681359
SciCode26%—
WeirdML14.4%—
BigCodeBench Instruct46.9%—
BigCodeBench Complete57.5%—

Agentic & Tool Use Not comparable

Llama-3.3-70B-Instruct: 25.6 (#100), Qwen2.5-Max: —

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
Berkeley Function Calling Leaderboard31.9%—
BALROG23%—

Reasoning Qwen2.5-Max leads

Llama-3.3-70B-Instruct: 13.7 (#325), Qwen2.5-Max: 24.6 (#144)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
LiveBench Reasoning50.8%51.4%
LMArena Hard Prompts12571360
LiveBench Data Analysis49.5%67.9%
Epoch Capabilities Index127.32132.54
LiveBench50.2%62.3%
SimpleBench19.9%—
CritPt0%—
DTBench59.5%—
LMCA17.5%—
ForecastBench58.6—

Math Qwen2.5-Max leads

Llama-3.3-70B-Instruct: 14.3 (#292), Qwen2.5-Max: 34.3 (#162)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
LiveBench Math42.2%58.4%
LMArena Math12681369
OTIS Mock AIME 2024-20255.1%—
MATH Level 541.6%—

Knowledge Qwen2.5-Max leads

Llama-3.3-70B-Instruct: 30.5 (#220), Qwen2.5-Max: 34.8 (#181)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
Confabulations22.8%21.8%
LMArena Expert12251337
GPQA Diamond47.4%—
Vectara Hallucination Rate4.1%—
MMLU86.3%—

Multilingual Qwen2.5-Max leads

Llama-3.3-70B-Instruct: 40.1 (#215), Qwen2.5-Max: 48.3 (#140)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
LMArena Non-English12361352
LMArena Chinese12171382
LMArena French12801396
LMArena German12511350
LMArena Japanese11491299
LMArena Korean11421304
LMArena Russian12521353
LMArena Spanish12691377

Instruction Following Too close to call

Llama-3.3-70B-Instruct: 71.3 (#152), Qwen2.5-Max: 71.5 (#147)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
LiveBench Instruction Following82.7%75.3%
LMArena Instruction Following12421335

Long Context Qwen2.5-Max leads

Llama-3.3-70B-Instruct: 26.4 (#290), Qwen2.5-Max: 41.3 (#137)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
LMArena Longer Query12561358
Fiction.LiveBench33.3%—

Writing & Preference Qwen2.5-Max leads

Llama-3.3-70B-Instruct: 47.8 (#203), Qwen2.5-Max: 55.6 (#141)

BenchmarkLlama-3.3-70B-InstructQwen2.5-Max
LMArena Text12741367
LMArena Creative Writing12501339
LMArena Multi-Turn12791364
LiveBench Language39.2%56.3%
Short-Story Creative Writing—72.9%

Frequently asked questions

Is Llama-3.3-70B-Instruct better than Qwen2.5-Max?

Qwen2.5-Max is the stronger model overall, scoring 40.1 to 30.3 on the Noometry Index.

Is Llama-3.3-70B-Instruct or Qwen2.5-Max better for coding?

Qwen2.5-Max scores higher on coding benchmarks: 41.2 versus 30.6 in the Noometry coding category.

How many benchmarks do Llama-3.3-70B-Instruct and Qwen2.5-Max share?

26 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Qwen2.5-Max has 27.

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