Model comparison
Qwen3 14B vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 35.5 on the Noometry Index. Qwen3 14B costs 2.2× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Last verified . 8 shared benchmarks.
Alibaba (Qwen)Summary
- They share 8 benchmarks with published results for both. Qwen3 14B scores higher in 0 categories and Qwen3.6 27B in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 39.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 66.4% for Qwen3 14B and 91.1% for Qwen3.6 27B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.
- Qwen3.6 27B accepts more context: 262K tokens versus 131K.
Side by side
| Qwen3 14B | Qwen3.6 27B | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 35.5 | 42.2 |
| Released | 2025-04 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 8K | 66K |
| Input $ / M tokens | $0.35 | $0.60 |
| Output $ / M tokens | $1.40 | $3.60 |
| Results tracked | 12 | 11 |
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Category by category
Coding Qwen3.6 27B leads
Qwen3 14B: 37.3 (#195), Qwen3.6 27B: 39.1 (#163)
| Benchmark | Qwen3 14B | Qwen3.6 27B |
|---|---|---|
| SciCode | 31.6% | 37.3% |
Agentic & Tool Use Not comparable
Qwen3 14B: 29.6 (#83), Qwen3.6 27B: —
| Benchmark | Qwen3 14B | Qwen3.6 27B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 41% | — |
Reasoning Qwen3.6 27B leads
Qwen3 14B: 18.5 (#280), Qwen3.6 27B: 25.0 (#153)
| Benchmark | Qwen3 14B | Qwen3.6 27B |
|---|---|---|
| CritPt | 0% | 0.9% |
| Chess Puzzles | 4% | 22% |
| DTBench | 64% | 78.1% |
| LMCA | 18.2% | 34.5% |
| Epoch Capabilities Index | 138.23 | 146.5 |
| Kagi LLM Benchmark | 49.1% | — |
| Mystery Game Puzzles | — | 7% |
Math Qwen3.6 27B leads
Qwen3 14B: 38.6 (#133), Qwen3.6 27B: 48.5 (#62)
| Benchmark | Qwen3 14B | Qwen3.6 27B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.4% | 91.1% |
| FrontierMath (Tiers 1-3) | — | 35.1% |
Knowledge Qwen3.6 27B leads
Qwen3 14B: 39.3 (#134), Qwen3.6 27B: 52.4 (#63)
| Benchmark | Qwen3 14B | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | 63.8% | 85.9% |
| Vectara Hallucination Rate | 5.4% | — |
Long Context Not comparable
Qwen3 14B: 38.1 (#204), Qwen3.6 27B: —
| Benchmark | Qwen3 14B | Qwen3.6 27B |
|---|---|---|
| Fiction.LiveBench | 62.5% | — |
Writing & Preference Not comparable
Qwen3 14B: —, Qwen3.6 27B: 50.3 (#181)
| Benchmark | Qwen3 14B | Qwen3.6 27B |
|---|---|---|
| EQ-Bench 4 | — | 1026 |
Frequently asked questions
Is Qwen3 14B better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 35.5 on the Noometry Index. Qwen3 14B costs 2.2× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Which is cheaper, Qwen3 14B or Qwen3.6 27B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.
Is Qwen3 14B or Qwen3.6 27B better for coding?
Qwen3.6 27B scores higher on coding benchmarks: 39.1 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 27B does, with 262K tokens against 131K.
How many benchmarks do Qwen3 14B and Qwen3.6 27B share?
8 benchmarks have published results for both models. Qwen3 14B has 12 scored results on Noometry and Qwen3.6 27B has 11.