Compare / Qwen3-14B vs Llama 4 Scout
Qwen3-14B vs Llama 4 Scout
Which is cheaper, which is more capable, and which does better at each kind of work, from 25 results on 4 sources that measured both models.
Of the 25 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.
Results as of 13 October 2026 (catalogue release 2026-10-13-2e2420e3c5cc). See also Alibaba vs Meta, every model from both labs.
Qwen3-14B or Llama 4 Scout? The short answer
They score about the same, so pick Qwen3-14B: it costs 47% less per token.
- Qwen3-14B is cheaper: $0.15 against $0.28 per million tokens, 47% less.
- They score about the same on the Artificial Analysis Intelligence Index (8.2 and 8.1).
- Qwen3-14B is newer: released 28 Apr 2025, against 5 Apr 2025 for Llama 4 Scout.
- On third-party benchmarks, on the results both models have: Qwen3-14B does better for agents and tool use, reasoning and knowledge, writing and sticking to the facts.
Head to head
Every fact side by side
| Qwen3-14B | Llama 4 Scout | |
|---|---|---|
| Price per million tokens | $0.12 in · $0.24 out | $0.18 in · $0.59 out |
| Blended (3 in : 1 out) | $0.15 | $0.28 |
| Cheapest host, blended | $0.13 (NextBit, INT4) | $0.15 (DeepInfra, FP8) |
| Intelligence Index | 8.2 | 8.1 |
| Spring Prompt overall | – | – |
| Output speed, tokens a second | – | 46 |
| Context window | 131,072 tokens | 1,310,720 tokens |
| Released | 28 Apr 2025 (newer) | 5 Apr 2025 |
| Weights | Open | Open |
| Developer based in | China | the US |
Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.
Which is better for what
Each model's rank among the models on sale today, for each kind of work, from our own benchmarks and licensed sources. Further right is better; the better rank is in green.
Every shared result
Each model's best result on every measure both have, grouped by benchmark, with the setting that produced it. Under each measure, every model that benchmark has measured is a grey tick, best to the right, so you can see where the two sit in the field. The headline measures of each benchmark come first; the rest are under "Show all". Green marks the better value; where a source reports ranges that overlap, neither is marked.
| Measure | Qwen3-14B | Llama 4 Scout |
|---|---|---|
| Artificial Analysis reported by Artificial Analysis · 3 results | ||
| Artificial Analysis Intelligence Indexindex score, higher is better 194 · 197 of 243 measured | 8.2thinking reasoning | 8.1 |
| GPQA Diamond% of questions, higher is better 181 · 185 of 231 measured | 60.4%thinking reasoning | 58.7% |
| Humanity's Last Exam% of questions, higher is better 202 · 221 of 242 measured | 4.5%thinking reasoning | 3.8% |
| Berkeley Function Calling Leaderboard (BFCL) V4 reported by Berkeley Function Calling Leaderboard (BFCL) V4 · 3 results | ||
| Overall accuracy · BFCL% correct, higher is better 34 · 53 of 81 measured | 41.0%bfcl fc | 28.1%bfcl fc |
| Irrelevance detection · BFCL% correct, higher is better 20 · 75 of 81 measured | 87.2%bfcl prompt | 44.9%bfcl fc |
| Memory · BFCL% correct, higher is better 33 · 55 of 81 measured | 19.6%bfcl fc | 8.2%bfcl fc |
| UGI Leaderboard reported by UGI Leaderboard · 3 results | ||
| Writing score · UGIscore out of 100, higher is better 128 · 169 of 230 measured | 34.8no reasoning | 26.7 |
| Requested-length error · UGI% off the requested word count, lower is better 111 · 99 of 230 measured | 20.0%no reasoning | 19.0% |
| Style adherence · UGIscore from 0 to 1, higher is better 49 · 66 of 230 measured | 0.37no reasoning | 0.36 |
| Vectara Hallucination Leaderboard reported by Vectara Hallucination Leaderboard · 2 results | ||
| Hallucination rate · Vectara% of summaries, lower is better 17 · 38 of 104 measured | 5.4% | 7.7% |
| Answer rate · Vectara% of documents, higher is better 17 · 65 of 104 measured | 99.9% | 99.0% |
Show all 25 results (14 more)
| Measure | Qwen3-14B | Llama 4 Scout |
|---|---|---|
| Artificial Analysis reported by Artificial Analysis · 9 results | ||
| Terminal-Bench 2.1% of tasks, higher is better 112 · 118 of 130 measured | 4.9%thinking reasoning | 3.7% |
| Terminal-Bench 4.0% of tasks, higher is better 66 · 66 of 112 measured | 0.0%thinking reasoning | 0.0% |
| τ-bench banking% of tasks, higher is better 100 · 117 of 121 measured | 5.6%thinking reasoning | 3.3% |
| Artificial Analysis Coding Indexindex score, higher is better 115 · 124 of 131 measured | 13.8thinking reasoning | 8.2 |
| IFBench% of instructions, higher is better 132 · 138 of 195 measured | 40.5%thinking reasoning | 39.5% |
| Long-context reasoning (AA-LCR)% of questions, higher is better 222 · 190 of 233 measured | 0.0%no reasoning | 27.7% |
| SciCode% of problems, higher is better 100 · 110 of 113 measured | 30.7%thinking reasoning | 21.3% |
| Terminal-Bench Hard% of tasks, higher is better 153 · 175 of 190 measured | 5.3%no reasoning | 1.5% |
| τ²-bench telecom% of tasks, higher is better 123 · 176 of 193 measured | 34.5%thinking reasoning | 15.5% |
| Berkeley Function Calling Leaderboard (BFCL) V4 reported by Berkeley Function Calling Leaderboard (BFCL) V4 · 5 results | ||
| Multi-turn tasks · BFCL% correct, higher is better 31 · 53 of 81 measured | 34.8%bfcl fc | 9.0%bfcl fc |
| Relevance detection · BFCL% correct, higher is better 26 · 1 of 81 measured | 87.5%bfcl fc | 100.0%bfcl fc |
| Single-turn calls (curated) · BFCL% correct, higher is better 7 · 8 of 81 measured | 89.5%bfcl prompt | 89.4%bfcl fc |
| Single-turn calls (user-contributed) · BFCL% correct, higher is better 10 · 34 of 81 measured | 80.0%bfcl fc | 74.7%bfcl fc |
| Web search · BFCL% correct, higher is better 37 · 34 of 81 measured | 10.5%bfcl prompt | 14.5%bfcl fc |
Compare them with other models
Quick answers
Is Qwen3-14B better than Llama 4 Scout?
They score about the same, so pick Qwen3-14B: it costs 47% less per token.
Which is cheaper, Qwen3-14B or Llama 4 Scout?
Qwen3-14B is cheaper: $0.15 against $0.28 per million tokens, 47% less.
Which is better for agents and tool use, Qwen3-14B or Llama 4 Scout?
Qwen3-14B ranks 122 of 164 models on sale for multi-step tasks with tools: support desks, coding agents, function calls, against 150 for Llama 4 Scout.
Which is better for reasoning and knowledge, Qwen3-14B or Llama 4 Scout?
Qwen3-14B ranks 162 of 198 models on sale for hard questions across science, maths and general knowledge, against 167 for Llama 4 Scout.
Which is better for writing, Qwen3-14B or Llama 4 Scout?
Qwen3-14B ranks 130 of 188 models on sale for what people prefer in blind comparisons, and judged writing quality, against 164 for Llama 4 Scout.
Which is better for sticking to the facts, Qwen3-14B or Llama 4 Scout?
Qwen3-14B ranks 15 of 152 models on sale for summarising without inventing things, and factual answers, against 47 for Llama 4 Scout.
Which has the bigger context window, Qwen3-14B or Llama 4 Scout?
Llama 4 Scout: 1,310,720 tokens, against 131,072 for Qwen3-14B.
Run Qwen3-14B and Llama 4 Scout on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.