Compare / Qwen3 14B vs GPT-5 Mini
Qwen3 14B vs GPT-5 Mini
Which is cheaper, which is more capable, and which does better at each kind of work, from 22 results on 3 sources that measured both models.
Qwen3 14B or GPT-5 Mini? The short answer
- Qwen3 14B is cheaper: $0.15 against $0.69 per million tokens, 4.6 times less.
- GPT-5 Mini scores higher on the Artificial Analysis Intelligence Index: 20.6 against 8.2.
- On our business benchmarks, Qwen3 14B ranks higher for sticking to the facts.
- On our business benchmarks, GPT-5 Mini ranks higher for agents and tool use, reasoning and knowledge and writing.
At a glance
| Qwen3 14B | GPT-5 Mini | |
|---|---|---|
| Price per million tokens | $0.12 in · $0.24 out | $0.25 in · $2.00 out |
| Blended (3 in : 1 out) | $0.15 | $0.69 |
| Cheapest host, blended | $0.13 (NextBit, INT4) | $0.34 (OpenAI) |
| Intelligence Index | 8.2 | 20.6 |
| Spring Prompt overall | – | – |
| Output speed, tokens a second | – | – |
| Context window | 131,072 tokens | 400,000 tokens |
| Weights | Open | Closed |
| 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 models available today, for each kind of work, from our own benchmarks and licensed sources. The better rank is in green.
| Use case | Qwen3 14B | GPT-5 Mini |
|---|---|---|
| Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls | 120 of 161 | 106 of 161 |
| Reasoning and knowledgeHard questions across science, maths and general knowledge | 159 of 195 | 91 of 195 |
| WritingWhat people prefer in blind comparisons, and judged writing quality | 128 of 187 | 117 of 187 |
| Sticking to the factsSummarising without inventing things, and factual answers | 17 of 153 | 131 of 153 |
Every shared result
| Benchmark | Metric | Qwen3 14B | GPT-5 Mini |
|---|---|---|---|
| Artificial Analysisreported | Artificial Analysis Coding Indexindex score | 13.8 | 15.6 |
| Artificial Analysisreported | Artificial Analysis Intelligence Indexindex score | 8.20 | 20.6 |
| Artificial Analysisreported | GPQA Diamond% of questions | 60.4% | 82.8% |
| Artificial Analysisreported | Humanity's Last Exam% of questions | 4.5% | 21.5% |
| Artificial Analysisreported | IFBench% of instructions | 40.5% | 75.4% |
| Artificial Analysisreported | Long-context reasoning (AA-LCR)% of questions | 0.0% | 72.3% |
| Artificial Analysisreported | SciCode% of problems | 30.7% | 39.0% |
| Artificial Analysisreported | Terminal-Bench 2.1% of tasks | 4.9% | 3.7% |
| Artificial Analysisreported | Terminal-Bench 4.0% of tasks | 0.0% | 0.0% |
| Artificial Analysisreported | Terminal-Bench Hard% of tasks | 5.3% | 33.3% |
| Artificial Analysisreported | Τ-bench banking% of tasks | 5.6% | 15.5% |
| Artificial Analysisreported | Τ²-bench telecom% of tasks | 34.5% | 71.1% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Irrelevance detection% correct | 87.2% | 91.0% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Memory% correct | 19.6% | 44.3% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Multi-turn tasks% correct | 34.8% | 27.5% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Overall accuracy% correct | 41.0% | 55.5% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Relevance detection% correct | 87.5% | 93.8% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Single-turn calls (curated)% correct | 89.5% | 69.8% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Single-turn calls (user-contributed)% correct | 80.0% | 62.5% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Web search% correct | 10.5% | 82.0% |
| Vectara Hallucination Leaderboardreported | Answer rate% of documents | 99.9% | 99.9% |
| Vectara Hallucination Leaderboardreported | Hallucination rate% of summaries | 5.4% | 12.9% |
Bold green marks the better value on that metric. Where a source reports ranges that overlap, the difference may not be meaningful; see the benchmark page for ranges.
Quick answers
Is Qwen3 14B better than GPT-5 Mini?
It depends on the task. Among models available today, on our benchmarks and licensed sources, Qwen3 14B ranks higher for sticking to the facts; GPT-5 Mini ranks higher for agents and tool use, reasoning and knowledge and writing.
Which is cheaper, Qwen3 14B or GPT-5 Mini?
Qwen3 14B costs $0.15 per million tokens (three input to one output), against $0.69 for GPT-5 Mini.
Run Qwen3 14B and GPT-5 Mini on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.