Model comparison
Llama 3.1-8B vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.0 to 22.8 on the Noometry Index. Llama 3.1-8B costs 11× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Last verified . 9 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 9 benchmarks with published results for both. Llama 3.1-8B scores higher in 0 categories and Qwen3 14B in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 14B leads 39.2 to 8.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.7% for Llama 3.1-8B and 66.4% for Qwen3 14B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- Qwen3 14B accepts more context: 131K tokens versus 128K.
Side by side
| Llama 3.1-8B | Qwen3 14B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 22.8 | 35.0 |
| Released | 2024-07-23 | 2025-04 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 8K |
| Input $ / M tokens | $0.05 | $0.35 |
| Output $ / M tokens | $0.08 | $1.40 |
| Results tracked | 43 | 12 |
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Category by category
Coding Qwen3 14B leads
Llama 3.1-8B: 19.9 (#335), Qwen3 14B: 36.7 (#191)
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| SciCode | 13.2% | 31.6% |
| WeirdML | 1.7% | — |
| BigCodeBench Instruct | 32.8% | — |
| LMArena Coding | 1195 | — |
| BigCodeBench Complete | 40.5% | — |
| HumanEval+ | 62.8% | — |
| MBPP+ | 55.6% | — |
Agentic & Tool Use Qwen3 14B leads
Llama 3.1-8B: 22.3 (#123), Qwen3 14B: 29.4 (#78)
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | 41% |
| BALROG | 15.1% | — |
Reasoning Qwen3 14B leads
Llama 3.1-8B: 14.5 (#316), Qwen3 14B: 18.1 (#272)
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| CritPt | 0% | 0% |
| Chess Puzzles | 0% | 4% |
| DTBench | 50.9% | 64% |
| LMCA | 5.4% | 18.2% |
| Epoch Capabilities Index | 116.48 | 138.23 |
| Kagi LLM Benchmark | — | 49.1% |
| LMArena Hard Prompts | 1175 | — |
| PIQA | 81.2% | — |
Math Qwen3 14B leads
Llama 3.1-8B: 9.5 (#311), Qwen3 14B: 37.0 (#102)
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.7% | 66.4% |
| Omni-MATH | 13.7% | — |
| LMArena Math | 1179 | — |
| MATH Level 5 | 22.9% | — |
| GSM8K | 82.4% | — |
Knowledge Qwen3 14B leads
Llama 3.1-8B: 8.0 (#302), Qwen3 14B: 39.2 (#124)
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 27% | 63.8% |
| MMLU-Pro | 40.6% | — |
| Vectara Hallucination Rate | — | 5.4% |
| GPQA (HELM) | 24.7% | — |
| LMArena Expert | 1144 | — |
| BoolQ | 82.8% | — |
| MMLU | 56.1% | — |
Multilingual Not comparable
Llama 3.1-8B: 34.2 (#244), Qwen3 14B: —
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1148 | — |
| LMArena Chinese | 1151 | — |
| LMArena French | 1176 | — |
| LMArena German | 1144 | — |
| LMArena Japanese | 1061 | — |
| LMArena Korean | 1053 | — |
| LMArena Russian | 1158 | — |
| LMArena Spanish | 1169 | — |
Instruction Following Not comparable
Llama 3.1-8B: 59.1 (#253), Qwen3 14B: —
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| IFEval | 74.3% | — |
| LMArena Instruction Following | 1159 | — |
Long Context Qwen3 14B leads
Llama 3.1-8B: 35.8 (#233), Qwen3 14B: 38.0 (#201)
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1182 | — |
Writing & Preference Not comparable
Llama 3.1-8B: 29.9 (#285), Qwen3 14B: —
| Benchmark | Llama 3.1-8B | Qwen3 14B |
|---|---|---|
| LMArena Text | 1187 | — |
| LMArena Creative Writing | 1154 | — |
| EQ-Bench Creative Writing | 713 | — |
| WildBench | 68.7% | — |
| LMArena Multi-Turn | 1172 | — |
Frequently asked questions
Is Llama 3.1-8B better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.0 to 22.8 on the Noometry Index. Llama 3.1-8B costs 11× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Which is cheaper, Llama 3.1-8B or Qwen3 14B?
Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Is Llama 3.1-8B or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 36.7 versus 19.9 in the Noometry coding category.
Which has the bigger context window?
Qwen3 14B does, with 131K tokens against 128K.
How many benchmarks do Llama 3.1-8B and Qwen3 14B share?
9 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Qwen3 14B has 12.