Model comparison
GPT-5.5 Pro vs Qwen3 14B
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 35.0 on the Noometry Index. Qwen3 14B costs 110× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. GPT-5.5 Pro scores higher in 3 categories and Qwen3 14B in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.5 Pro leads 73.6 to 18.1.
- The biggest single-benchmark swing is Chess Puzzles: 64% for GPT-5.5 Pro and 4% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $30 / $180 for GPT-5.5 Pro.
- GPT-5.5 Pro accepts more context: 1.05M tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.5 Pro | Qwen3 14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 64.3 | 35.0 |
| Released | 2026-04-23 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $30 | $0.35 |
| Output $ / M tokens | $180 | $1.40 |
| Results tracked | 14 | 12 |
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Category by category
Coding Not comparable
GPT-5.5 Pro: —, Qwen3 14B: 36.7 (#191)
| Benchmark | GPT-5.5 Pro | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
Agentic & Tool Use Not comparable
GPT-5.5 Pro: —, Qwen3 14B: 29.4 (#78)
| Benchmark | GPT-5.5 Pro | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning GPT-5.5 Pro leads
GPT-5.5 Pro: 73.6 (#7), Qwen3 14B: 18.1 (#272)
| Benchmark | GPT-5.5 Pro | Qwen3 14B |
|---|---|---|
| CritPt | 30.6% | 0% |
| Chess Puzzles | 64% | 4% |
| DTBench | 96% | 64% |
| LMCA | 53.9% | 18.2% |
| Epoch Capabilities Index | 162.45 | 138.23 |
| ARC-AGI-2 | 84.6% | — |
| SimpleBench | 76.9% | — |
| Kagi LLM Benchmark | — | 49.1% |
| ARC-AGI-1 | 96.5% | — |
Math GPT-5.5 Pro leads
GPT-5.5 Pro: 83.8 (#8), Qwen3 14B: 37.0 (#102)
| Benchmark | GPT-5.5 Pro | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 66.4% |
| FrontierMath (Tiers 1-3) | 87.7% | — |
| FrontierMath Tier 4 | 78% | — |
| FrontierMath (Feb 2025 set) | 52.4% | — |
| FrontierMath Tier 4 (v1) | 39.6% | — |
Knowledge GPT-5.5 Pro leads
GPT-5.5 Pro: 64.2 (#17), Qwen3 14B: 39.2 (#124)
| Benchmark | GPT-5.5 Pro | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 93.9% | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
Long Context Not comparable
GPT-5.5 Pro: —, Qwen3 14B: 38.0 (#201)
| Benchmark | GPT-5.5 Pro | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
Frequently asked questions
Is GPT-5.5 Pro better than Qwen3 14B?
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 35.0 on the Noometry Index. Qwen3 14B costs 110× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.5 Pro or Qwen3 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; GPT-5.5 Pro lists at $30 and $180.
Which has the bigger context window?
GPT-5.5 Pro does, with 1.05M tokens against 131K.
How many benchmarks do GPT-5.5 Pro and Qwen3 14B share?
7 benchmarks have published results for both models. GPT-5.5 Pro has 14 scored results on Noometry and Qwen3 14B has 12.