Model comparison
Qwen3 14B vs Qwen3 235B-A22B
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 35.5 on the Noometry Index. Qwen3 14B costs 2.0× less per token, which makes it the better buy when Qwen3 235B-A22B's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. Qwen3 14B scores higher in 1 category and Qwen3 235B-A22B in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 235B-A22B leads 50.4 to 38.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 49.1% for Qwen3 14B and 69.4% for Qwen3 235B-A22B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $0.70 / $2.80 for Qwen3 235B-A22B.
Side by side
| Qwen3 14B | Qwen3 235B-A22B | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 35.5 | 43.5 |
| Released | 2025-04 | 2025-04 |
| Weights | Open | Open |
| Context window | 131K | 131K |
| Max output | 8K | 16K |
| Input $ / M tokens | $0.35 | $0.70 |
| Output $ / M tokens | $1.40 | $2.80 |
| Results tracked | 12 | 49 |
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Category by category
Coding Qwen3 235B-A22B leads
Qwen3 14B: 37.3 (#195), Qwen3 235B-A22B: 44.3 (#75)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| SciCode | 31.6% | 42.4% |
| Aider Polyglot | — | 59.6% |
| WeirdML | — | 41% |
| LMArena Coding | — | 1445 |
Agentic & Tool Use Qwen3 235B-A22B leads
Qwen3 14B: 29.6 (#83), Qwen3 235B-A22B: 33.9 (#51)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 41% | 52.1% |
| Vending-Bench 2 | — | -11.34 |
Reasoning Qwen3 14B leads
Qwen3 14B: 18.5 (#280), Qwen3 235B-A22B: 15.7 (#311)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| Kagi LLM Benchmark | 49.1% | 69.4% |
| CritPt | 0% | 0% |
| Chess Puzzles | 4% | 12% |
| DTBench | 64% | 80.3% |
| LMCA | 18.2% | 29.3% |
| Epoch Capabilities Index | 138.23 | 143.85 |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31% |
| ARC-AGI-1 | — | 11% |
| LMArena Hard Prompts | — | 1433 |
| Mystery Game Puzzles | — | 9% |
| ForecastBench | — | 59.7 |
Math Qwen3 235B-A22B leads
Qwen3 14B: 38.6 (#133), Qwen3 235B-A22B: 50.4 (#57)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.4% | 86.7% |
| Omni-MATH | — | 71.8% |
| LMArena Math | — | 1432 |
| MATH Level 5 | — | 68.9% |
| FrontierMath (Feb 2025 set) | — | 8.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3 235B-A22B leads
Qwen3 14B: 39.3 (#134), Qwen3 235B-A22B: 49.6 (#73)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| GPQA Diamond | 63.8% | 80.1% |
| Vectara Hallucination Rate | 5.4% | 9.3% |
| SimpleQA Verified | — | 40.4% |
| MMLU-Pro | — | 84.4% |
| Confabulations | — | 15.6% |
| GPQA (HELM) | — | 72.7% |
| LMArena Expert | — | 1463 |
Multilingual Not comparable
Qwen3 14B: —, Qwen3 235B-A22B: 52.3 (#89)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | — | 1409 |
| LMArena Chinese | — | 1481 |
| LMArena French | — | 1445 |
| LMArena German | — | 1433 |
| LMArena Japanese | — | 1399 |
| LMArena Korean | — | 1391 |
| LMArena Russian | — | 1411 |
| LMArena Spanish | — | 1430 |
Instruction Following Not comparable
Qwen3 14B: —, Qwen3 235B-A22B: 72.6 (#136)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| IFEval | — | 83.5% |
| LMArena Instruction Following | — | 1408 |
Long Context Qwen3 235B-A22B leads
Qwen3 14B: 38.1 (#204), Qwen3 235B-A22B: 46.1 (#26)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| Fiction.LiveBench | 62.5% | 75% |
| LMArena Longer Query | — | 1426 |
Writing & Preference Not comparable
Qwen3 14B: —, Qwen3 235B-A22B: 59.6 (#108)
| Benchmark | Qwen3 14B | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | — | 1419 |
| LMArena Creative Writing | — | 1384 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1366 |
| WildBench | — | 86.6% |
| LMArena Multi-Turn | — | 1432 |
Frequently asked questions
Is Qwen3 14B better than Qwen3 235B-A22B?
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 35.5 on the Noometry Index. Qwen3 14B costs 2.0× less per token, which makes it the better buy when Qwen3 235B-A22B's lead doesn't matter for your workload.
Which is cheaper, Qwen3 14B or Qwen3 235B-A22B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Qwen3 235B-A22B lists at $0.70 and $2.80.
Is Qwen3 14B or Qwen3 235B-A22B better for coding?
Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 131K tokens.
How many benchmarks do Qwen3 14B and Qwen3 235B-A22B share?
12 benchmarks have published results for both models. Qwen3 14B has 12 scored results on Noometry and Qwen3 235B-A22B has 49.