Model comparison
Llama 3.2 1B vs Qwen2.5 7B Instruct
Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 20.1 on the Noometry Index. Llama 3.2 1B costs 4.3× less per token, which makes it the better buy when Qwen2.5 7B Instruct's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. Llama 3.2 1B scores higher in 1 category and Qwen2.5 7B Instruct in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen2.5 7B Instruct leads 48.8 to 21.3.
- The biggest single-benchmark swing is BigCodeBench Complete: 11.3% for Llama 3.2 1B and 46.1% for Qwen2.5 7B Instruct.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 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 60K.
Side by side
| Llama 3.2 1B | Qwen2.5 7B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 20.1 | 29.0 |
| Released | 2024-09-24 | 2024-09 |
| Weights | Open | Open |
| Context window | 60K | 131K |
| Max output | 54K | 8K |
| Input $ / M tokens | $0.027 | $0.17 |
| Output $ / M tokens | $0.20 | $0.70 |
| Results tracked | 22 | 15 |
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Category by category
Coding Qwen2.5 7B Instruct leads
Llama 3.2 1B: 21.1 (#338), Qwen2.5 7B Instruct: 36.5 (#208)
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| BigCodeBench Instruct | 8.2% | 37.6% |
| BigCodeBench Complete | 11.3% | 46.1% |
| LMArena Coding | 1070 | — |
Agentic & Tool Use Qwen2.5 7B Instruct leads
Llama 3.2 1B: 14.6 (#150), Qwen2.5 7B Instruct: 23.8 (#124)
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| BALROG | 6.6% | 7.8% |
| Berkeley Function Calling Leaderboard | 10.8% | — |
Reasoning Llama 3.2 1B leads
Llama 3.2 1B: 16.2 (#308), Qwen2.5 7B Instruct: 14.8 (#322)
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| Epoch Capabilities Index | 101.99 | 118.51 |
| LMArena Hard Prompts | 1044 | — |
| DTBench | — | 47.7% |
| LMCA | — | 6.4% |
Math Qwen2.5 7B Instruct leads
Llama 3.2 1B: 10.4 (#313), Qwen2.5 7B Instruct: 12.6 (#306)
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | 2.5% |
| Omni-MATH | — | 29.4% |
| LMArena Math | 1086 | — |
Knowledge Qwen2.5 7B Instruct leads
Llama 3.2 1B: 7.2 (#312), Qwen2.5 7B Instruct: 17.0 (#286)
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 23.9% | 35.5% |
| MMLU-Pro | — | 53.9% |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1007 | — |
| MMLU | — | 72.9% |
Multilingual Not comparable
Llama 3.2 1B: 23.8 (#292), Qwen2.5 7B Instruct: —
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 973 | — |
| LMArena Chinese | 959 | — |
| LMArena German | 1014 | — |
| LMArena Russian | 941 | — |
Instruction Following Qwen2.5 7B Instruct leads
Llama 3.2 1B: 52.4 (#290), Qwen2.5 7B Instruct: 63.2 (#231)
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1031 | — |
Long Context Not comparable
Llama 3.2 1B: 31.9 (#274), Qwen2.5 7B Instruct: —
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1050 | — |
Writing & Preference Qwen2.5 7B Instruct leads
Llama 3.2 1B: 21.3 (#310), Qwen2.5 7B Instruct: 48.8 (#195)
| Benchmark | Llama 3.2 1B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1055 | — |
| LMArena Creative Writing | 1033 | — |
| EQ-Bench Creative Writing | 200 | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1030 | — |
Frequently asked questions
Is Llama 3.2 1B better than Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 20.1 on the Noometry Index. Llama 3.2 1B costs 4.3× less per token, which makes it the better buy when Qwen2.5 7B Instruct's lead doesn't matter for your workload.
Which is cheaper, Llama 3.2 1B or Qwen2.5 7B Instruct?
Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Qwen2.5 7B Instruct lists at $0.17 and $0.70.
Is Llama 3.2 1B or Qwen2.5 7B Instruct better for coding?
Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 21.1 in the Noometry coding category.
Which has the bigger context window?
Qwen2.5 7B Instruct does, with 131K tokens against 60K.
How many benchmarks do Llama 3.2 1B and Qwen2.5 7B Instruct share?
7 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen2.5 7B Instruct has 15.