Model comparison
Qwen2.5 7B Instruct vs Qwen3-30B-A3B
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 29.0 on the Noometry Index.
Last verified . 6 shared benchmarks.
Alibaba (Qwen)Summary
- They share 6 benchmarks with published results for both. Qwen2.5 7B Instruct scores higher in 0 categories and Qwen3-30B-A3B in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-30B-A3B leads 37.4 to 12.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 2.5% for Qwen2.5 7B Instruct and 70.3% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.17 / $0.70 for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct accepts more context: 131K tokens versus 41K.
Side by side
| Qwen2.5 7B Instruct | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 29.0 | 38.9 |
| Released | 2024-09 | 2025-04-28 |
| Weights | Open | Open |
| Context window | 131K | 41K |
| Max output | 8K | 16K |
| Input $ / M tokens | $0.17 | $0.12 |
| Output $ / M tokens | $0.70 | $0.50 |
| Results tracked | 15 | 32 |
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Category by category
Coding Qwen3-30B-A3B leads
Qwen2.5 7B Instruct: 36.5 (#208), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| SciCode | — | 33.3% |
| WeirdML | — | 29.8% |
| BigCodeBench Instruct | 37.6% | — |
| LMArena Coding | — | 1416 |
| BigCodeBench Complete | 46.1% | — |
Agentic & Tool Use Qwen3-30B-A3B leads
Qwen2.5 7B Instruct: 23.8 (#124), Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
| BALROG | 7.8% | — |
Reasoning Qwen3-30B-A3B leads
Qwen2.5 7B Instruct: 14.8 (#322), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| Chess Puzzles | 0% | 8% |
| DTBench | 47.7% | 69.3% |
| LMCA | 6.4% | 22.4% |
| Epoch Capabilities Index | 118.51 | 139.63 |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| LMArena Hard Prompts | — | 1398 |
Math Qwen3-30B-A3B leads
Qwen2.5 7B Instruct: 12.6 (#306), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 2.5% | 70.3% |
| MathArena Final-Answer Competitions | — | 47.8% |
| Omni-MATH | 29.4% | — |
| LMArena Math | — | 1394 |
Knowledge Qwen3-30B-A3B leads
Qwen2.5 7B Instruct: 17.0 (#286), Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 35.5% | 70.1% |
| MMLU-Pro | 53.9% | — |
| Confabulations | — | 12.3% |
| GPQA (HELM) | 34.1% | — |
| LMArena Expert | — | 1396 |
| MMLU | 72.9% | — |
Multilingual Not comparable
Qwen2.5 7B Instruct: —, Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | — | 1372 |
| LMArena Chinese | — | 1433 |
| LMArena French | — | 1418 |
| LMArena German | — | 1380 |
| LMArena Japanese | — | 1337 |
| LMArena Korean | — | 1331 |
| LMArena Russian | — | 1370 |
| LMArena Spanish | — | 1404 |
Instruction Following Qwen3-30B-A3B leads
Qwen2.5 7B Instruct: 63.2 (#231), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| IFEval | 74.1% | — |
| LMArena Instruction Following | — | 1363 |
Long Context Not comparable
Qwen2.5 7B Instruct: —, Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| Fiction.LiveBench | — | 40.6% |
| LMArena Longer Query | — | 1379 |
Writing & Preference Qwen3-30B-A3B leads
Qwen2.5 7B Instruct: 48.8 (#195), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | Qwen2.5 7B Instruct | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | — | 1384 |
| LMArena Creative Writing | — | 1317 |
| Short-Story Creative Writing | — | 75.3% |
| WildBench | 73.1% | — |
| LMArena Multi-Turn | — | 1378 |
Frequently asked questions
Is Qwen2.5 7B Instruct better than Qwen3-30B-A3B?
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 29.0 on the Noometry Index.
Which is cheaper, Qwen2.5 7B Instruct or Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; Qwen2.5 7B Instruct lists at $0.17 and $0.70.
Is Qwen2.5 7B Instruct or Qwen3-30B-A3B better for coding?
Qwen3-30B-A3B scores higher on coding benchmarks: 37.5 versus 36.5 in the Noometry coding category.
Which has the bigger context window?
Qwen2.5 7B Instruct does, with 131K tokens against 41K.
How many benchmarks do Qwen2.5 7B Instruct and Qwen3-30B-A3B share?
6 benchmarks have published results for both models. Qwen2.5 7B Instruct has 15 scored results on Noometry and Qwen3-30B-A3B has 32.