Noometry

Model comparison

Llama 3.1-70B vs Qwen3.5-9B

Qwen3.5-9B is the stronger model overall, scoring 33.8 to 29.6 on the Noometry Index.

Last verified . 5 shared benchmarks.

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

Qwen3.5-9B Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

  • They share 5 benchmarks with published results for both. Llama 3.1-70B scores higher in 1 category and Qwen3.5-9B in 4 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 24.2.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 3.6% for Llama 3.1-70B and 61.7% for Qwen3.5-9B.
  • Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.40 / $0.40 for Llama 3.1-70B.
  • Qwen3.5-9B accepts more context: 262K tokens versus 128K.

Side by side

Llama 3.1-70BQwen3.5-9B
ProviderMetaAlibaba (Qwen)
Noometry Index29.633.8
Released2024-07-232026-02-23
WeightsOpenOpen
Context window128K262K
Max output4K66K
Input $ / M tokens$0.40$0.10
Output $ / M tokens$0.40$0.15
Results tracked3510

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Category by category

Coding Qwen3.5-9B leads

Llama 3.1-70B: 30.3 (#296), Qwen3.5-9B: 35.9 (#217)

BenchmarkLlama 3.1-70BQwen3.5-9B
SciCode—27.5%
WeirdML9%—
BigCodeBench Instruct46.1%—
LMArena Coding1260—
BigCodeBench Complete54.8%—

Agentic & Tool Use Llama 3.1-70B leads

Llama 3.1-70B: 25.1 (#112), Qwen3.5-9B: 14.5 (#151)

BenchmarkLlama 3.1-70BQwen3.5-9B
Terminal-Bench—9.2%
TheAgentCompany6.9%—
BALROG27.9%—

Reasoning Qwen3.5-9B leads

Llama 3.1-70B: 21.6 (#220), Qwen3.5-9B: 23.1 (#182)

BenchmarkLlama 3.1-70BQwen3.5-9B
DTBench60%71.2%
LMCA14.8%24.5%
Epoch Capabilities Index125.92139.46
CritPt—0.3%
Chess Puzzles—12%
LMArena Hard Prompts1241—

Math Qwen3.5-9B leads

Llama 3.1-70B: 13.5 (#304), Qwen3.5-9B: 34.8 (#192)

BenchmarkLlama 3.1-70BQwen3.5-9B
OTIS Mock AIME 2024-20253.6%61.7%
MathArena Final-Answer Competitions—48.5%
Omni-MATH21%—
LMArena Math1252—
MATH Level 536.7%—

Knowledge Qwen3.5-9B leads

Llama 3.1-70B: 24.2 (#269), Qwen3.5-9B: 46.0 (#84)

BenchmarkLlama 3.1-70BQwen3.5-9B
GPQA Diamond44.2%79%
MMLU-Pro65.3%—
GPQA (HELM)42.6%—
LMArena Expert1209—
MMLU80.1%—

Multilingual Not comparable

Llama 3.1-70B: 38.8 (#225), Qwen3.5-9B: —

BenchmarkLlama 3.1-70BQwen3.5-9B
LMArena Non-English1219—
LMArena Chinese1215—
LMArena French1261—
LMArena German1222—
LMArena Japanese1132—
LMArena Korean1140—
LMArena Russian1234—
LMArena Spanish1253—

Instruction Following Not comparable

Llama 3.1-70B: 65.3 (#223), Qwen3.5-9B: —

BenchmarkLlama 3.1-70BQwen3.5-9B
IFEval82.1%—
LMArena Instruction Following1231—

Long Context Not comparable

Llama 3.1-70B: 37.6 (#214), Qwen3.5-9B: —

BenchmarkLlama 3.1-70BQwen3.5-9B
LMArena Longer Query1241—

Writing & Preference Not comparable

Llama 3.1-70B: 35.4 (#267), Qwen3.5-9B: —

BenchmarkLlama 3.1-70BQwen3.5-9B
LMArena Text1261—
LMArena Creative Writing1232—
EQ-Bench Creative Writing784—
WildBench75.8%—
LMArena Multi-Turn1256—

Frequently asked questions

Is Llama 3.1-70B better than Qwen3.5-9B?

Qwen3.5-9B is the stronger model overall, scoring 33.8 to 29.6 on the Noometry Index.

Which is cheaper, Llama 3.1-70B or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; Llama 3.1-70B lists at $0.40 and $0.40.

Is Llama 3.1-70B or Qwen3.5-9B better for coding?

Qwen3.5-9B scores higher on coding benchmarks: 35.9 versus 30.3 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 128K.

How many benchmarks do Llama 3.1-70B and Qwen3.5-9B share?

5 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Qwen3.5-9B has 10.

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