Model comparison
Llama 3.2 1B vs Qwen3-30B-A3B
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 20.1 on the Noometry Index. Llama 3.2 1B costs 3.0× less per token, which makes it the better buy when Qwen3-30B-A3B's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. Llama 3.2 1B scores higher in 1 category and Qwen3-30B-A3B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-30B-A3B leads 41.8 to 7.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.6% for Llama 3.2 1B and 70.3% for Qwen3-30B-A3B.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.12 / $0.50 for Qwen3-30B-A3B.
- Llama 3.2 1B accepts more context: 60K tokens versus 41K.
Side by side
| Llama 3.2 1B | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 20.1 | 38.9 |
| Released | 2024-09-24 | 2025-04-28 |
| Weights | Open | Open |
| Context window | 60K | 41K |
| Max output | 54K | 16K |
| Input $ / M tokens | $0.027 | $0.12 |
| Output $ / M tokens | $0.20 | $0.50 |
| Results tracked | 22 | 32 |
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Category by category
Coding Qwen3-30B-A3B leads
Llama 3.2 1B: 21.1 (#338), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Coding | 1070 | 1416 |
| SciCode | — | 33.3% |
| WeirdML | — | 29.8% |
| BigCodeBench Instruct | 8.2% | — |
| BigCodeBench Complete | 11.3% | — |
Agentic & Tool Use Qwen3-30B-A3B leads
Llama 3.2 1B: 14.6 (#150), Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | 41.4% |
| BALROG | 6.6% | — |
Reasoning Qwen3-30B-A3B leads
Llama 3.2 1B: 16.2 (#308), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| Chess Puzzles | 0% | 8% |
| LMArena Hard Prompts | 1044 | 1398 |
| Epoch Capabilities Index | 101.99 | 139.63 |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |
Math Qwen3-30B-A3B leads
Llama 3.2 1B: 10.4 (#313), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | 70.3% |
| LMArena Math | 1086 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
Knowledge Qwen3-30B-A3B leads
Llama 3.2 1B: 7.2 (#312), Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 23.9% | 70.1% |
| LMArena Expert | 1007 | 1396 |
| Confabulations | — | 12.3% |
Multilingual Qwen3-30B-A3B leads
Llama 3.2 1B: 23.8 (#292), Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 973 | 1372 |
| LMArena Chinese | 959 | 1433 |
| LMArena German | 1014 | 1380 |
| LMArena Russian | 941 | 1370 |
| LMArena French | — | 1418 |
| LMArena Japanese | — | 1337 |
| LMArena Korean | — | 1331 |
| LMArena Spanish | — | 1404 |
Instruction Following Qwen3-30B-A3B leads
Llama 3.2 1B: 52.4 (#290), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1031 | 1363 |
Long Context Too close to call
Llama 3.2 1B: 31.9 (#274), Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1050 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Qwen3-30B-A3B leads
Llama 3.2 1B: 21.3 (#310), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | Llama 3.2 1B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1055 | 1384 |
| LMArena Creative Writing | 1033 | 1317 |
| LMArena Multi-Turn | 1030 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench Creative Writing | 200 | — |
Frequently asked questions
Is Llama 3.2 1B better than Qwen3-30B-A3B?
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 20.1 on the Noometry Index. Llama 3.2 1B costs 3.0× less per token, which makes it the better buy when Qwen3-30B-A3B's lead doesn't matter for your workload.
Which is cheaper, Llama 3.2 1B or Qwen3-30B-A3B?
Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Qwen3-30B-A3B lists at $0.12 and $0.50.
Is Llama 3.2 1B or Qwen3-30B-A3B better for coding?
Qwen3-30B-A3B scores higher on coding benchmarks: 37.5 versus 21.1 in the Noometry coding category.
Which has the bigger context window?
Llama 3.2 1B does, with 60K tokens against 41K.
How many benchmarks do Llama 3.2 1B and Qwen3-30B-A3B share?
18 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen3-30B-A3B has 32.