Model comparison
Llama 3.1-70B vs Qwen3-4B
Qwen3-4B is the stronger model overall, scoring 31.9 to 29.6 on the Noometry Index.
Last verified . 2 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Llama 3.1-70B scores higher in 1 category and Qwen3-4B in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-4B leads 29.7 to 13.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 3.6% for Llama 3.1-70B and 52.2% for Qwen3-4B.
Side by side
| Llama 3.1-70B | Qwen3-4B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.6 | 31.9 |
| Released | 2024-07-23 | 2025-04-29 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.40 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 35 | 6 |
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Category by category
Coding Not comparable
Llama 3.1-70B: 30.3 (#296), Qwen3-4B: —
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| LMArena Coding | 1260 | — |
| BigCodeBench Complete | 54.8% | — |
Agentic & Tool Use Qwen3-4B leads
Llama 3.1-70B: 25.1 (#112), Qwen3-4B: 27.6 (#100)
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 35.7% |
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
Reasoning Llama 3.1-70B leads
Llama 3.1-70B: 21.6 (#220), Qwen3-4B: 19.2 (#268)
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1241 | — |
| DTBench | 60% | — |
| LMCA | 14.8% | — |
| Epoch Capabilities Index | 125.92 | — |
Math Qwen3-4B leads
Llama 3.1-70B: 13.5 (#304), Qwen3-4B: 29.7 (#240)
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 3.6% | 52.2% |
| MathArena Final-Answer Competitions | — | 38.5% |
| Omni-MATH | 21% | — |
| LMArena Math | 1252 | — |
| MATH Level 5 | 36.7% | — |
Knowledge Qwen3-4B leads
Llama 3.1-70B: 24.2 (#269), Qwen3-4B: 33.0 (#208)
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| GPQA Diamond | 44.2% | 52.3% |
| MMLU-Pro | 65.3% | — |
| Vectara Hallucination Rate | — | 5.7% |
| GPQA (HELM) | 42.6% | — |
| LMArena Expert | 1209 | — |
| MMLU | 80.1% | — |
Multilingual Not comparable
Llama 3.1-70B: 38.8 (#225), Qwen3-4B: —
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| LMArena Non-English | 1219 | — |
| LMArena Chinese | 1215 | — |
| LMArena French | 1261 | — |
| LMArena German | 1222 | — |
| LMArena Japanese | 1132 | — |
| LMArena Korean | 1140 | — |
| LMArena Russian | 1234 | — |
| LMArena Spanish | 1253 | — |
Instruction Following Not comparable
Llama 3.1-70B: 65.3 (#223), Qwen3-4B: —
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| IFEval | 82.1% | — |
| LMArena Instruction Following | 1231 | — |
Long Context Not comparable
Llama 3.1-70B: 37.6 (#214), Qwen3-4B: —
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| LMArena Longer Query | 1241 | — |
Writing & Preference Not comparable
Llama 3.1-70B: 35.4 (#267), Qwen3-4B: —
| Benchmark | Llama 3.1-70B | Qwen3-4B |
|---|---|---|
| LMArena Text | 1261 | — |
| LMArena Creative Writing | 1232 | — |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |
| LMArena Multi-Turn | 1256 | — |
Frequently asked questions
Is Llama 3.1-70B better than Qwen3-4B?
Qwen3-4B is the stronger model overall, scoring 31.9 to 29.6 on the Noometry Index.
How many benchmarks do Llama 3.1-70B and Qwen3-4B share?
2 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Qwen3-4B has 6.