Model comparison
Llama 3.2 1B vs Qwen1.5-72B
Qwen1.5-72B is the stronger model overall, scoring 30.8 to 20.1 on the Noometry Index.
Last verified . 16 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 16 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Qwen1.5-72B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen1.5-72B leads 33.2 to 10.4.
- The biggest single-benchmark swing is BigCodeBench Complete: 11.3% for Llama 3.2 1B and 40.3% for Qwen1.5-72B.
Side by side
| Llama 3.2 1B | Qwen1.5-72B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 20.1 | 30.8 |
| 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 | 22 |
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Category by category
Coding Qwen1.5-72B leads
Llama 3.2 1B: 21.1 (#338), Qwen1.5-72B: 31.9 (#277)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| BigCodeBench Instruct | 8.2% | 33.2% |
| LMArena Coding | 1070 | 1165 |
| BigCodeBench Complete | 11.3% | 40.3% |
| HumanEval+ | — | 59.1% |
| MBPP+ | — | 61.6% |
Agentic & Tool Use Not comparable
Llama 3.2 1B: 14.6 (#150), Qwen1.5-72B: —
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | — |
| BALROG | 6.6% | — |
Reasoning Qwen1.5-72B leads
Llama 3.2 1B: 16.2 (#308), Qwen1.5-72B: 22.2 (#203)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| LMArena Hard Prompts | 1044 | 1148 |
| Chess Puzzles | 0% | — |
| Epoch Capabilities Index | 101.99 | — |
Math Qwen1.5-72B leads
Llama 3.2 1B: 10.4 (#313), Qwen1.5-72B: 33.2 (#205)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| LMArena Math | 1086 | 1164 |
| OTIS Mock AIME 2024-2025 | 0.6% | — |
Knowledge Qwen1.5-72B leads
Llama 3.2 1B: 7.2 (#312), Qwen1.5-72B: 11.5 (#300)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| GPQA Diamond | 23.9% | 28.8% |
| LMArena Expert | 1007 | 1136 |
Multilingual Qwen1.5-72B leads
Llama 3.2 1B: 23.8 (#292), Qwen1.5-72B: 33.2 (#253)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| LMArena Non-English | 973 | 1135 |
| LMArena Chinese | 959 | 1186 |
| LMArena German | 1014 | 1084 |
| LMArena Russian | 941 | 1104 |
| LMArena French | — | 1159 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1050 |
| LMArena Spanish | — | 1110 |
Instruction Following Qwen1.5-72B leads
Llama 3.2 1B: 52.4 (#290), Qwen1.5-72B: 59.3 (#256)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| LMArena Instruction Following | 1031 | 1141 |
Long Context Qwen1.5-72B leads
Llama 3.2 1B: 31.9 (#274), Qwen1.5-72B: 35.1 (#243)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| LMArena Longer Query | 1050 | 1157 |
Writing & Preference Qwen1.5-72B leads
Llama 3.2 1B: 21.3 (#310), Qwen1.5-72B: 37.3 (#258)
| Benchmark | Llama 3.2 1B | Qwen1.5-72B |
|---|---|---|
| LMArena Text | 1055 | 1166 |
| LMArena Creative Writing | 1033 | 1137 |
| LMArena Multi-Turn | 1030 | 1160 |
| EQ-Bench Creative Writing | 200 | — |
Frequently asked questions
Is Llama 3.2 1B better than Qwen1.5-72B?
Qwen1.5-72B is the stronger model overall, scoring 30.8 to 20.1 on the Noometry Index.
Is Llama 3.2 1B or Qwen1.5-72B better for coding?
Qwen1.5-72B scores higher on coding benchmarks: 31.9 versus 21.1 in the Noometry coding category.
How many benchmarks do Llama 3.2 1B and Qwen1.5-72B share?
16 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen1.5-72B has 22.