Model comparison

Llama 2-70B vs Qwen3.6 Max Preview

Qwen3.6 Max Preview is the stronger model overall, scoring 51.1 to 24.1 on the Noometry Index.

Last verified . 18 shared benchmarks.

Llama 2-70B Meta

24.1

Rank #343 Confirmed

Qwen3.6 Max Preview Alibaba (Qwen)

51.1

Rank #36 Confirmed

Summary

  • They share 18 benchmarks with published results for both. Llama 2-70B scores higher in 0 categories and Qwen3.6 Max Preview in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3.6 Max Preview leads 57.6 to 7.4.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0% for Llama 2-70B and 91.1% for Qwen3.6 Max Preview.
  • Llama 2-70B has downloadable open weights; the other is API-only.

Side by side

Llama 2-70B and Qwen3.6 Max Preview specifications
Llama 2-70BQwen3.6 Max Preview
ProviderMetaAlibaba (Qwen)
Noometry Index24.151.1
Released2023-07-182026-04-20
WeightsOpenProprietary
Context window—262K
Max output—66K
Input $ / M tokens—$1.30
Output $ / M tokens—$7.80
Results tracked3529

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Category by category

Coding Qwen3.6 Max Preview leads

Llama 2-70B: 30.8 (#281), Qwen3.6 Max Preview: 48.6 (#50)

Coding benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
LMArena Coding10791472
SWE-bench Verified—76.7%
LMArena WebDev—1482

Agentic & Tool Use Not comparable

Llama 2-70B: —, Qwen3.6 Max Preview: —

Agentic & Tool Use benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
Vending-Bench 2—4,254

Reasoning Qwen3.6 Max Preview leads

Llama 2-70B: 13.7 (#324), Qwen3.6 Max Preview: 40.8 (#47)

Reasoning benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
LMArena Hard Prompts10731457
DTBench41.6%87.2%
Epoch Capabilities Index113.59149.27
SimpleBench—63%
NYT Connections (extended)—74.1%
Chess Puzzles—20%
Mystery Game Puzzles—19%
LMCA—42.5%
BIG-Bench Hard64.9%—
CommonsenseQA 2.050%—
ForecastBench51.4—
HellaSwag85.3%—
LAMBADA78.9%—
PIQA82.8%—
WinoGrande80.2%—

Math Qwen3.6 Max Preview leads

Llama 2-70B: 7.5 (#320), Qwen3.6 Max Preview: 52.2 (#40)

Math benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
OTIS Mock AIME 2024-20250%91.1%
LMArena Math10911465
MATH Level 53.3%—
FrontierMath (Feb 2025 set)—23.1%
FrontierMath Tier 4 (v1)—4.2%
GSM8K69.6%—

Knowledge Qwen3.6 Max Preview leads

Llama 2-70B: 7.4 (#305), Qwen3.6 Max Preview: 57.6 (#35)

Knowledge benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
GPQA Diamond26.3%87.4%
LMArena Expert10391476
SimpleQA Verified—52%
ARC (AI2) Challenge78.3%—
BoolQ88.6%—
MMLU69.9%—
OpenBookQA60.2%—
TriviaQA87.6%—

Multilingual Qwen3.6 Max Preview leads

Llama 2-70B: 27.9 (#269), Qwen3.6 Max Preview: 54.3 (#46)

Multilingual benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
LMArena Non-English10451436
LMArena Chinese9941487
LMArena French10891449
LMArena Russian10831444
LMArena Spanish11421452
LMArena German1041—
LMArena Japanese927—
LMArena Korean964—

Instruction Following Qwen3.6 Max Preview leads

Llama 2-70B: 55.1 (#273), Qwen3.6 Max Preview: 75.8 (#51)

Instruction Following benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
LMArena Instruction Following10711437

Long Context Qwen3.6 Max Preview leads

Llama 2-70B: 32.2 (#265), Qwen3.6 Max Preview: 44.6 (#59)

Long Context benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
LMArena Longer Query10621457

Writing & Preference Qwen3.6 Max Preview leads

Llama 2-70B: 32.5 (#274), Qwen3.6 Max Preview: 64.0 (#58)

Writing & Preference benchmarks
BenchmarkLlama 2-70BQwen3.6 Max Preview
LMArena Text11151447
LMArena Creative Writing10751435
LMArena Multi-Turn10881456

Frequently asked questions

Is Llama 2-70B better than Qwen3.6 Max Preview?

Qwen3.6 Max Preview is the stronger model overall, scoring 51.1 to 24.1 on the Noometry Index.

Is Llama 2-70B or Qwen3.6 Max Preview better for coding?

Qwen3.6 Max Preview scores higher on coding benchmarks: 48.6 versus 30.8 in the Noometry coding category.

How many benchmarks do Llama 2-70B and Qwen3.6 Max Preview share?

18 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Qwen3.6 Max Preview has 29.

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