Model comparison
Mercury vs Qwen3 14B
Mercury is the stronger model overall, scoring 37.6 to 35.5 on the Noometry Index.
Last verified . 1 shared benchmarks.
Alibaba (Qwen)Summary
- They share 1 benchmark with published results for both. Mercury scores higher in 2 categories and Qwen3 14B in 1 category; 2 gaps are clear of the uncertainty.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 21.6% for Mercury and 49.1% for Qwen3 14B.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| Mercury | Qwen3 14B | |
|---|---|---|
| Provider | Inception | Alibaba (Qwen) |
| Noometry Index | 37.6 | 35.5 |
| Released | — | 2025-04 |
| Weights | Proprietary | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $0.35 |
| Output $ / M tokens | — | $1.40 |
| Results tracked | 9 | 12 |
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Category by category
Coding Mercury leads
Mercury: 38.7 (#170), Qwen3 14B: 37.3 (#195)
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
| LMArena Coding | 1322 | — |
Agentic & Tool Use Not comparable
Mercury: —, Qwen3 14B: 29.6 (#83)
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Qwen3 14B leads
Mercury: 17.5 (#293), Qwen3 14B: 18.5 (#280)
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 21.6% | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1285 | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Not comparable
Mercury: —, Qwen3 14B: 38.6 (#133)
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
Knowledge Not comparable
Mercury: —, Qwen3 14B: 39.3 (#134)
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
Multilingual Not comparable
Mercury: 41.6 (#206), Qwen3 14B: —
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1260 | — |
Instruction Following Not comparable
Mercury: 65.2 (#224), Qwen3 14B: —
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1239 | — |
Long Context Too close to call
Mercury: 38.4 (#198), Qwen3 14B: 38.1 (#204)
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1266 | — |
Writing & Preference Not comparable
Mercury: 46.2 (#221), Qwen3 14B: —
| Benchmark | Mercury | Qwen3 14B |
|---|---|---|
| LMArena Text | 1282 | — |
| LMArena Creative Writing | 1191 | — |
| LMArena Multi-Turn | 1282 | — |
Frequently asked questions
Is Mercury better than Qwen3 14B?
Mercury is the stronger model overall, scoring 37.6 to 35.5 on the Noometry Index.
Is Mercury or Qwen3 14B better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 37.3 in the Noometry coding category.
How many benchmarks do Mercury and Qwen3 14B share?
1 benchmark has published results for both models. Mercury has 9 scored results on Noometry and Qwen3 14B has 12.