Model comparison
Mercury 2 vs Qwen3 14B
Mercury 2 is the stronger model overall, scoring 38.8 to 35.0 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Mercury 2 scores higher in 2 categories and Qwen3 14B in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Mercury 2 leads 23.0 to 18.1.
- The biggest single-benchmark swing is SciCode: 38.7% for Mercury 2 and 31.6% for Qwen3 14B.
- Mercury 2 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- Qwen3 14B accepts more context: 131K tokens versus 128K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| Mercury 2 | Qwen3 14B | |
|---|---|---|
| Provider | Inception | Alibaba (Qwen) |
| Noometry Index | 38.8 | 35.0 |
| Released | 2026-02-20 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 128K | 131K |
| Max output | 50K | 8K |
| Input $ / M tokens | $0.25 | $0.35 |
| Output $ / M tokens | $0.75 | $1.40 |
| Results tracked | 17 | 12 |
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Category by category
Coding Qwen3 14B leads
Mercury 2: 33.2 (#250), Qwen3 14B: 36.7 (#191)
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| SciCode | 38.7% | 31.6% |
| LMArena WebDev | 1170 | — |
| WeirdML | 43.2% | — |
| LMArena Coding | 1391 | — |
| ALE-Bench | 785.58 | — |
Agentic & Tool Use Not comparable
Mercury 2: —, Qwen3 14B: 29.4 (#78)
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Mercury 2 leads
Mercury 2: 23.0 (#170), Qwen3 14B: 18.1 (#272)
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| CritPt | 0.8% | 0% |
| Kagi LLM Benchmark | — | 49.1% |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1362 | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Not comparable
Mercury 2: —, Qwen3 14B: 37.0 (#102)
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
Knowledge Qwen3 14B leads
Mercury 2: 35.6 (#170), Qwen3 14B: 39.2 (#124)
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| Vectara Hallucination Rate | 12.3% | 5.4% |
| GPQA Diamond | — | 63.8% |
| LMArena Expert | 1358 | — |
Multilingual Not comparable
Mercury 2: 46.8 (#153), Qwen3 14B: —
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1331 | — |
| LMArena Chinese | 1416 | — |
| LMArena Russian | 1303 | — |
Instruction Following Not comparable
Mercury 2: 70.4 (#161), Qwen3 14B: —
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1328 | — |
Long Context Mercury 2 leads
Mercury 2: 40.4 (#149), Qwen3 14B: 38.0 (#201)
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1329 | — |
Writing & Preference Not comparable
Mercury 2: 54.0 (#151), Qwen3 14B: —
| Benchmark | Mercury 2 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1355 | — |
| LMArena Creative Writing | 1289 | — |
| LMArena Multi-Turn | 1358 | — |
Frequently asked questions
Is Mercury 2 better than Qwen3 14B?
Mercury 2 is the stronger model overall, scoring 38.8 to 35.0 on the Noometry Index.
Which is cheaper, Mercury 2 or Qwen3 14B?
Mercury 2 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Is Mercury 2 or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 36.7 versus 33.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3 14B does, with 131K tokens against 128K.
How many benchmarks do Mercury 2 and Qwen3 14B share?
3 benchmarks have published results for both models. Mercury 2 has 17 scored results on Noometry and Qwen3 14B has 12.