Model comparison

Qwen1.5-7B vs Qwen3-30B-A3B

Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 31.4 on the Noometry Index.

Last verified . 12 shared benchmarks.

Qwen1.5-7B Alibaba (Qwen)

31.4

Rank #273 Confirmed

Qwen3-30B-A3B Alibaba (Qwen)

38.9

Rank #179 Confirmed

Summary

  • They share 12 benchmarks with published results for both. Qwen1.5-7B scores higher in 1 category and Qwen3-30B-A3B in 7 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Qwen3-30B-A3B leads 55.6 to 29.6.

Side by side

Qwen1.5-7B and Qwen3-30B-A3B specifications
Qwen1.5-7BQwen3-30B-A3B
ProviderAlibaba (Qwen)Alibaba (Qwen)
Noometry Index31.438.9
Released2024-02-042025-04-28
WeightsOpenOpen
Context window—41K
Max output—16K
Input $ / M tokens—$0.12
Output $ / M tokens—$0.50
Results tracked1332

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Category by category

Coding Qwen3-30B-A3B leads

Qwen1.5-7B: 32.2 (#276), Qwen3-30B-A3B: 37.5 (#194)

Coding benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Coding11071416
SciCode—33.3%
WeirdML—29.8%

Agentic & Tool Use Not comparable

Qwen1.5-7B: —, Qwen3-30B-A3B: 29.8 (#82)

Agentic & Tool Use benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
Berkeley Function Calling Leaderboard—41.4%

Reasoning Qwen3-30B-A3B leads

Qwen1.5-7B: 20.4 (#240), Qwen3-30B-A3B: 22.2 (#204)

Reasoning benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Hard Prompts10651398
Kagi LLM Benchmark—54.9%
CritPt—0.3%
Chess Puzzles—8%
DTBench—69.3%
LMCA—22.4%
Epoch Capabilities Index—139.63

Math Qwen3-30B-A3B leads

Qwen1.5-7B: 31.4 (#224), Qwen3-30B-A3B: 37.4 (#157)

Math benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Math10801394
MathArena Final-Answer Competitions—47.8%
OTIS Mock AIME 2024-2025—70.3%

Knowledge Qwen3-30B-A3B leads

Qwen1.5-7B: 28.7 (#243), Qwen3-30B-A3B: 41.8 (#105)

Knowledge benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Expert10551396
GPQA Diamond—70.1%
Confabulations—12.3%
MMLU62.6%—

Multilingual Qwen3-30B-A3B leads

Qwen1.5-7B: 28.5 (#271), Qwen3-30B-A3B: 49.5 (#132)

Multilingual benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Non-English10581372
LMArena Chinese11411433
LMArena Russian10061370
LMArena French—1418
LMArena German—1380
LMArena Japanese—1337
LMArena Korean—1331
LMArena Spanish—1404

Instruction Following Qwen3-30B-A3B leads

Qwen1.5-7B: 54.1 (#281), Qwen3-30B-A3B: 72.0 (#142)

Instruction Following benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Instruction Following10581363

Long Context Qwen1.5-7B leads

Qwen1.5-7B: 33.1 (#266), Qwen3-30B-A3B: 31.0 (#283)

Long Context benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Longer Query10901379
Fiction.LiveBench—40.6%

Writing & Preference Qwen3-30B-A3B leads

Qwen1.5-7B: 29.6 (#293), Qwen3-30B-A3B: 55.6 (#143)

Writing & Preference benchmarks
BenchmarkQwen1.5-7BQwen3-30B-A3B
LMArena Text10831384
LMArena Creative Writing10351317
LMArena Multi-Turn10621378
Short-Story Creative Writing—75.3%

Frequently asked questions

Is Qwen1.5-7B better than Qwen3-30B-A3B?

Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 31.4 on the Noometry Index.

Is Qwen1.5-7B or Qwen3-30B-A3B better for coding?

Qwen3-30B-A3B scores higher on coding benchmarks: 37.5 versus 32.2 in the Noometry coding category.

How many benchmarks do Qwen1.5-7B and Qwen3-30B-A3B share?

12 benchmarks have published results for both models. Qwen1.5-7B has 13 scored results on Noometry and Qwen3-30B-A3B has 32.

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