Model comparison
Llama 2-70B vs Qwen3-4B
Qwen3-4B is the stronger model overall, scoring 31.9 to 24.4 on the Noometry Index.
Last verified . 2 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Llama 2-70B scores higher in 0 categories and Qwen3-4B in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-4B leads 33.0 to 7.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0% for Llama 2-70B and 52.2% for Qwen3-4B.
Side by side
| Llama 2-70B | Qwen3-4B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 24.4 | 31.9 |
| Released | 2023-07-18 | 2025-04-29 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 35 | 6 |
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Category by category
Coding Not comparable
Llama 2-70B: 31.4 (#286), Qwen3-4B: —
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| LMArena Coding | 1079 | — |
Agentic & Tool Use Not comparable
Llama 2-70B: —, Qwen3-4B: 27.6 (#100)
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 35.7% |
Reasoning Qwen3-4B leads
Llama 2-70B: 14.4 (#325), Qwen3-4B: 19.2 (#268)
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1073 | — |
| DTBench | 41.6% | — |
| BIG-Bench Hard | 64.9% | — |
| CommonsenseQA 2.0 | 50% | — |
| Epoch Capabilities Index | 113.79 | — |
| ForecastBench | 51.4 | — |
| HellaSwag | 85.3% | — |
| LAMBADA | 78.9% | — |
| PIQA | 82.8% | — |
| WinoGrande | 80.2% | — |
Math Qwen3-4B leads
Llama 2-70B: 8.1 (#326), Qwen3-4B: 29.7 (#240)
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0% | 52.2% |
| MathArena Final-Answer Competitions | — | 38.5% |
| LMArena Math | 1091 | — |
| MATH Level 5 | 3.3% | — |
| GSM8K | 69.6% | — |
Knowledge Qwen3-4B leads
Llama 2-70B: 7.4 (#310), Qwen3-4B: 33.0 (#208)
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| GPQA Diamond | 26.3% | 52.3% |
| Vectara Hallucination Rate | — | 5.7% |
| LMArena Expert | 1039 | — |
| ARC (AI2) Challenge | 78.3% | — |
| BoolQ | 88.6% | — |
| MMLU | 69.9% | — |
| OpenBookQA | 60.2% | — |
| TriviaQA | 87.6% | — |
Multilingual Not comparable
Llama 2-70B: 27.7 (#274), Qwen3-4B: —
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| LMArena Non-English | 1045 | — |
| LMArena Chinese | 995 | — |
| LMArena French | 1090 | — |
| LMArena German | 1041 | — |
| LMArena Japanese | 927 | — |
| LMArena Korean | 964 | — |
| LMArena Russian | 1083 | — |
| LMArena Spanish | 1143 | — |
Instruction Following Not comparable
Llama 2-70B: 54.9 (#278), Qwen3-4B: —
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| LMArena Instruction Following | 1071 | — |
Long Context Not comparable
Llama 2-70B: 32.3 (#270), Qwen3-4B: —
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| LMArena Longer Query | 1062 | — |
Writing & Preference Not comparable
Llama 2-70B: 32.3 (#279), Qwen3-4B: —
| Benchmark | Llama 2-70B | Qwen3-4B |
|---|---|---|
| LMArena Text | 1115 | — |
| LMArena Creative Writing | 1075 | — |
| LMArena Multi-Turn | 1088 | — |
Frequently asked questions
Is Llama 2-70B better than Qwen3-4B?
Qwen3-4B is the stronger model overall, scoring 31.9 to 24.4 on the Noometry Index.
How many benchmarks do Llama 2-70B and Qwen3-4B share?
2 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Qwen3-4B has 6.