Model comparison
Llama 3-70B vs Qwen3-1.7B
Llama 3-70B is the stronger model overall, scoring 28.5 to 26.2 on the Noometry Index.
Last verified . 2 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Llama 3-70B scores higher in 1 category and Qwen3-1.7B in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Qwen3-1.7B leads 24.5 to 20.9.
Side by side
| Llama 3-70B | Qwen3-1.7B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 28.5 | 26.2 |
| Released | 2024-04-18 | 2025-04-29 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 31 | 4 |
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Category by category
Coding Not comparable
Llama 3-70B: 35.3 (#215), Qwen3-1.7B: —
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| BigCodeBench Instruct | 43.6% | — |
| LMArena Coding | 1206 | — |
| BigCodeBench Complete | 54.5% | — |
| HumanEval+ | 72% | — |
| MBPP+ | 69% | — |
Agentic & Tool Use Qwen3-1.7B leads
Llama 3-70B: 20.9 (#132), Qwen3-1.7B: 24.5 (#108)
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
| Cybench | 5% | — |
Reasoning Qwen3-1.7B leads
Llama 3-70B: 17.4 (#284), Qwen3-1.7B: 18.5 (#263)
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| Kagi LLM Benchmark | 35.1% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1195 | — |
| DTBench | 54.2% | — |
| Epoch Capabilities Index | 122.91 | — |
| ForecastBench | 57.1 | — |
| WinoGrande | 83.5% | — |
Math Qwen3-1.7B leads
Llama 3-70B: 12.0 (#299), Qwen3-1.7B: 15.4 (#288)
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 4.3% | 8.1% |
| LMArena Math | 1218 | — |
| MATH Level 5 | 22.6% | — |
Knowledge Llama 3-70B leads
Llama 3-70B: 20.8 (#272), Qwen3-1.7B: 19.6 (#273)
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 40.6% | 38% |
| LMArena Expert | 1149 | — |
| MMLU | 79.3% | — |
Multilingual Not comparable
Llama 3-70B: 33.8 (#246), Qwen3-1.7B: —
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1142 | — |
| LMArena Chinese | 1114 | — |
| LMArena French | 1231 | — |
| LMArena German | 1169 | — |
| LMArena Japanese | 1017 | — |
| LMArena Korean | 1017 | — |
| LMArena Russian | 1159 | — |
| LMArena Spanish | 1241 | — |
Instruction Following Not comparable
Llama 3-70B: 62.8 (#233), Qwen3-1.7B: —
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1194 | — |
Long Context Not comparable
Llama 3-70B: 35.6 (#235), Qwen3-1.7B: —
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1174 | — |
Writing & Preference Not comparable
Llama 3-70B: 43.0 (#225), Qwen3-1.7B: —
| Benchmark | Llama 3-70B | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1221 | — |
| LMArena Creative Writing | 1210 | — |
| LMArena Multi-Turn | 1223 | — |
Frequently asked questions
Is Llama 3-70B better than Qwen3-1.7B?
Llama 3-70B is the stronger model overall, scoring 28.5 to 26.2 on the Noometry Index.
How many benchmarks do Llama 3-70B and Qwen3-1.7B share?
2 benchmarks have published results for both models. Llama 3-70B has 31 scored results on Noometry and Qwen3-1.7B has 4.