Model comparison
Llama 3-8B vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.0 to 25.3 on the Noometry Index. Llama 3-8B costs 4.4× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Last verified . 5 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 5 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and Qwen3 14B in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 14B leads 39.2 to 7.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.9% for Llama 3-8B and 66.4% for Qwen3 14B.
- Llama 3-8B is cheaper at $0.14 / $0.14 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- Qwen3 14B accepts more context: 131K tokens versus 8K.
Side by side
| Llama 3-8B | Qwen3 14B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 25.3 | 35.0 |
| Released | 2024-04-18 | 2025-04 |
| Weights | Open | Open |
| Context window | 8K | 131K |
| Max output | 8K | 8K |
| Input $ / M tokens | $0.14 | $0.35 |
| Output $ / M tokens | $0.14 | $1.40 |
| Results tracked | 34 | 12 |
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Category by category
Coding Qwen3 14B leads
Llama 3-8B: 30.5 (#285), Qwen3 14B: 36.7 (#191)
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
| BigCodeBench Instruct | 31.9% | — |
| LMArena Coding | 1152 | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Agentic & Tool Use Not comparable
Llama 3-8B: —, Qwen3 14B: 29.4 (#78)
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Qwen3 14B leads
Llama 3-8B: 13.8 (#321), Qwen3 14B: 18.1 (#272)
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| Chess Puzzles | 0% | 4% |
| DTBench | 43.9% | 64% |
| Epoch Capabilities Index | 116.33 | 138.23 |
| Kagi LLM Benchmark | — | 49.1% |
| CritPt | — | 0% |
| LMArena Hard Prompts | 1133 | — |
| LMCA | — | 18.2% |
| Adversarial NLI | 57.3% | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |
Math Qwen3 14B leads
Llama 3-8B: 8.3 (#317), Qwen3 14B: 37.0 (#102)
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | 66.4% |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |
Knowledge Qwen3 14B leads
Llama 3-8B: 7.8 (#303), Qwen3 14B: 39.2 (#124)
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 26.1% | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1113 | — |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |
Multilingual Not comparable
Llama 3-8B: 31.0 (#256), Qwen3 14B: —
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1098 | — |
| LMArena Chinese | 1076 | — |
| LMArena French | 1158 | — |
| LMArena German | 1104 | — |
| LMArena Japanese | 967 | — |
| LMArena Korean | 1003 | — |
| LMArena Russian | 1109 | — |
| LMArena Spanish | 1172 | — |
Instruction Following Not comparable
Llama 3-8B: 58.7 (#255), Qwen3 14B: —
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1127 | — |
Long Context Qwen3 14B leads
Llama 3-8B: 34.2 (#246), Qwen3 14B: 38.0 (#201)
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1128 | — |
Writing & Preference Not comparable
Llama 3-8B: 37.7 (#251), Qwen3 14B: —
| Benchmark | Llama 3-8B | Qwen3 14B |
|---|---|---|
| LMArena Text | 1166 | — |
| LMArena Creative Writing | 1150 | — |
| LMArena Multi-Turn | 1152 | — |
Frequently asked questions
Is Llama 3-8B better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.0 to 25.3 on the Noometry Index. Llama 3-8B costs 4.4× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Which is cheaper, Llama 3-8B or Qwen3 14B?
Llama 3-8B is cheaper. It lists at $0.14 per million input tokens and $0.14 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Is Llama 3-8B or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 36.7 versus 30.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3 14B does, with 131K tokens against 8K.
How many benchmarks do Llama 3-8B and Qwen3 14B share?
5 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Qwen3 14B has 12.