Model comparison
Qwen3-30B-A3B vs Yi-34B
Qwen3-30B-A3B is the stronger model overall, scoring 38.5 to 27.4 on the Noometry Index.
Last verified . 19 shared benchmarks.
Alibaba (Qwen)Summary
- They share 19 benchmarks with published results for both. Qwen3-30B-A3B scores higher in 7 categories and Yi-34B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-30B-A3B leads 41.7 to 7.5.
- The biggest single-benchmark swing is GPQA Diamond: 70.1% for Qwen3-30B-A3B and 14.7% for Yi-34B.
Side by side
| Qwen3-30B-A3B | Yi-34B | |
|---|---|---|
| Provider | Alibaba (Qwen) | 01.AI |
| Noometry Index | 38.5 | 27.4 |
| Released | 2025-04-28 | 2023-11-02 |
| Weights | Open | Open |
| Context window | 41K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.12 | — |
| Output $ / M tokens | $0.50 | — |
| Results tracked | 32 | 23 |
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Category by category
Coding Qwen3-30B-A3B leads
Qwen3-30B-A3B: 37.0 (#188), Yi-34B: 31.8 (#269)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| LMArena Coding | 1416 | 1112 |
| SciCode | 33.3% | — |
| WeirdML | 29.8% | — |
Agentic & Tool Use Not comparable
Qwen3-30B-A3B: 29.5 (#75), Yi-34B: —
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 41.4% | — |
Reasoning Qwen3-30B-A3B leads
Qwen3-30B-A3B: 21.6 (#193), Yi-34B: 20.3 (#222)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| LMArena Hard Prompts | 1398 | 1104 |
| Epoch Capabilities Index | 139.63 | 117.28 |
| Kagi LLM Benchmark | 54.9% | — |
| CritPt | 0.3% | — |
| Chess Puzzles | 8% | — |
| DTBench | 69.3% | — |
| LMCA | 22.4% | — |
| BIG-Bench Hard | — | 71.7% |
Math Qwen3-30B-A3B leads
Qwen3-30B-A3B: 36.0 (#133), Yi-34B: 19.8 (#277)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| LMArena Math | 1394 | 1114 |
| MathArena Final-Answer Competitions | 47.8% | — |
| OTIS Mock AIME 2024-2025 | 70.3% | — |
| MATH Level 5 | — | 5.1% |
| GSM8K | — | 76% |
Knowledge Qwen3-30B-A3B leads
Qwen3-30B-A3B: 41.7 (#96), Yi-34B: 7.5 (#304)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| GPQA Diamond | 70.1% | 14.7% |
| LMArena Expert | 1395 | 1061 |
| Confabulations | 12.3% | — |
| MMLU | — | 76.3% |
Multilingual Qwen3-30B-A3B leads
Qwen3-30B-A3B: 49.8 (#126), Yi-34B: 29.9 (#259)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| LMArena Non-English | 1372 | 1079 |
| LMArena Chinese | 1434 | 1175 |
| LMArena French | 1419 | 1080 |
| LMArena German | 1379 | 1042 |
| LMArena Japanese | 1338 | 993 |
| LMArena Korean | 1333 | 959 |
| LMArena Russian | 1369 | 1050 |
| LMArena Spanish | 1403 | 1070 |
Instruction Following Qwen3-30B-A3B leads
Qwen3-30B-A3B: 72.2 (#137), Yi-34B: 56.4 (#269)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| LMArena Instruction Following | 1364 | 1091 |
Long Context Yi-34B leads
Qwen3-30B-A3B: 31.0 (#278), Yi-34B: 33.2 (#259)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| LMArena Longer Query | 1379 | 1094 |
| Fiction.LiveBench | 40.6% | — |
Writing & Preference Qwen3-30B-A3B leads
Qwen3-30B-A3B: 55.9 (#138), Yi-34B: 34.3 (#268)
| Benchmark | Qwen3-30B-A3B | Yi-34B |
|---|---|---|
| LMArena Text | 1384 | 1129 |
| LMArena Creative Writing | 1318 | 1108 |
| LMArena Multi-Turn | 1378 | 1113 |
| Short-Story Creative Writing | 75.3% | — |
Frequently asked questions
Is Qwen3-30B-A3B better than Yi-34B?
Qwen3-30B-A3B is the stronger model overall, scoring 38.5 to 27.4 on the Noometry Index.
Is Qwen3-30B-A3B or Yi-34B better for coding?
Qwen3-30B-A3B scores higher on coding benchmarks: 37.0 versus 31.8 in the Noometry coding category.
How many benchmarks do Qwen3-30B-A3B and Yi-34B share?
19 benchmarks have published results for both models. Qwen3-30B-A3B has 32 scored results on Noometry and Yi-34B has 23.