Model comparison
Llama 3.2 1B vs Qwen1.5-14B
Qwen1.5-14B is the stronger model overall, scoring 32.7 to 20.1 on the Noometry Index.
Last verified . 13 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Qwen1.5-14B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen1.5-14B leads 29.8 to 7.2.
Side by side
| Llama 3.2 1B | Qwen1.5-14B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 20.1 | 32.7 |
| Released | 2024-09-24 | 2024-02-04 |
| Weights | Open | Open |
| Context window | 60K | — |
| Max output | 54K | — |
| Input $ / M tokens | $0.027 | — |
| Output $ / M tokens | $0.20 | — |
| Results tracked | 22 | 17 |
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Category by category
Coding Qwen1.5-14B leads
Llama 3.2 1B: 21.1 (#338), Qwen1.5-14B: 33.1 (#263)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1070 | 1138 |
| BigCodeBench Instruct | 8.2% | — |
| BigCodeBench Complete | 11.3% | — |
Agentic & Tool Use Not comparable
Llama 3.2 1B: 14.6 (#150), Qwen1.5-14B: —
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | — |
| BALROG | 6.6% | — |
Reasoning Qwen1.5-14B leads
Llama 3.2 1B: 16.2 (#308), Qwen1.5-14B: 21.4 (#223)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1044 | 1113 |
| Chess Puzzles | 0% | — |
| Epoch Capabilities Index | 101.99 | — |
Math Qwen1.5-14B leads
Llama 3.2 1B: 10.4 (#313), Qwen1.5-14B: 32.4 (#215)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1086 | 1125 |
| OTIS Mock AIME 2024-2025 | 0.6% | — |
Knowledge Qwen1.5-14B leads
Llama 3.2 1B: 7.2 (#312), Qwen1.5-14B: 29.8 (#232)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1007 | 1094 |
| GPQA Diamond | 23.9% | — |
| MMLU | — | 68.6% |
Multilingual Qwen1.5-14B leads
Llama 3.2 1B: 23.8 (#292), Qwen1.5-14B: 30.7 (#262)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 973 | 1095 |
| LMArena Chinese | 959 | 1147 |
| LMArena German | 1014 | 1043 |
| LMArena Russian | 941 | 1046 |
| LMArena French | — | 1116 |
| LMArena Japanese | — | 1019 |
| LMArena Spanish | — | 1085 |
Instruction Following Qwen1.5-14B leads
Llama 3.2 1B: 52.4 (#290), Qwen1.5-14B: 56.8 (#271)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1031 | 1102 |
Long Context Qwen1.5-14B leads
Llama 3.2 1B: 31.9 (#274), Qwen1.5-14B: 33.7 (#257)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1050 | 1113 |
Writing & Preference Qwen1.5-14B leads
Llama 3.2 1B: 21.3 (#310), Qwen1.5-14B: 33.6 (#276)
| Benchmark | Llama 3.2 1B | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1055 | 1128 |
| LMArena Creative Writing | 1033 | 1091 |
| LMArena Multi-Turn | 1030 | 1110 |
| EQ-Bench Creative Writing | 200 | — |
Frequently asked questions
Is Llama 3.2 1B better than Qwen1.5-14B?
Qwen1.5-14B is the stronger model overall, scoring 32.7 to 20.1 on the Noometry Index.
Is Llama 3.2 1B or Qwen1.5-14B better for coding?
Qwen1.5-14B scores higher on coding benchmarks: 33.1 versus 21.1 in the Noometry coding category.
How many benchmarks do Llama 3.2 1B and Qwen1.5-14B share?
13 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen1.5-14B has 17.