Model comparison
Llama 3.1-70B vs Qwen1.5 4b Chat
Llama 3.1-70B and Qwen1.5 4b Chat score almost the same on the Noometry Index (29.6 vs 28.8), so choose on price, context window or the category you care about most.
Last verified . 13 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. Llama 3.1-70B scores higher in 6 categories and Qwen1.5 4b Chat in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen1.5 4b Chat leads 30.4 to 13.5.
Side by side
| Llama 3.1-70B | Qwen1.5 4b Chat | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.6 | 28.8 |
| Released | 2024-07-23 | — |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.40 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 35 | 13 |
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Category by category
Coding Llama 3.1-70B leads
Llama 3.1-70B: 30.3 (#296), Qwen1.5 4b Chat: 29.1 (#308)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Coding | 1260 | 999 |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
Agentic & Tool Use Not comparable
Llama 3.1-70B: 25.1 (#112), Qwen1.5 4b Chat: —
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
Reasoning Llama 3.1-70B leads
Llama 3.1-70B: 21.6 (#220), Qwen1.5 4b Chat: 18.5 (#279)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Hard Prompts | 1241 | 976 |
| DTBench | 60% | — |
| LMCA | 14.8% | — |
| Epoch Capabilities Index | 125.92 | — |
Math Qwen1.5 4b Chat leads
Llama 3.1-70B: 13.5 (#304), Qwen1.5 4b Chat: 30.4 (#234)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Math | 1252 | 1026 |
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |
Knowledge Qwen1.5 4b Chat leads
Llama 3.1-70B: 24.2 (#269), Qwen1.5 4b Chat: 26.7 (#255)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Expert | 1209 | 980 |
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |
Multilingual Llama 3.1-70B leads
Llama 3.1-70B: 38.8 (#225), Qwen1.5 4b Chat: 24.1 (#290)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Non-English | 1219 | 979 |
| LMArena Chinese | 1215 | 1024 |
| LMArena German | 1222 | 902 |
| LMArena Russian | 1234 | 952 |
| LMArena French | 1261 | — |
| LMArena Japanese | 1132 | — |
| LMArena Korean | 1140 | — |
| LMArena Spanish | 1253 | — |
Instruction Following Llama 3.1-70B leads
Llama 3.1-70B: 65.3 (#223), Qwen1.5 4b Chat: 49.0 (#300)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Instruction Following | 1231 | 978 |
| IFEval | 82.1% | — |
Long Context Llama 3.1-70B leads
Llama 3.1-70B: 37.6 (#214), Qwen1.5 4b Chat: 30.1 (#290)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Longer Query | 1241 | 988 |
Writing & Preference Llama 3.1-70B leads
Llama 3.1-70B: 35.4 (#267), Qwen1.5 4b Chat: 23.8 (#309)
| Benchmark | Llama 3.1-70B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Text | 1261 | 997 |
| LMArena Creative Writing | 1232 | 969 |
| LMArena Multi-Turn | 1256 | 977 |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |
Frequently asked questions
Is Llama 3.1-70B better than Qwen1.5 4b Chat?
Llama 3.1-70B and Qwen1.5 4b Chat score almost the same on the Noometry Index (29.6 vs 28.8), so choose on price, context window or the category you care about most.
Is Llama 3.1-70B or Qwen1.5 4b Chat better for coding?
Llama 3.1-70B scores higher on coding benchmarks: 30.3 versus 29.1 in the Noometry coding category.
How many benchmarks do Llama 3.1-70B and Qwen1.5 4b Chat share?
13 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Qwen1.5 4b Chat has 13.