Model comparison
Mercury vs Qwen2-72B
Mercury is the stronger model overall, scoring 37.6 to 30.0 on the Noometry Index.
Last verified . 8 shared benchmarks.
Alibaba (Qwen)Summary
- They share 8 benchmarks with published results for both. Mercury scores higher in 5 categories and Qwen2-72B in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where Mercury leads 38.7 to 29.1.
- Qwen2-72B has downloadable open weights; the other is API-only.
Side by side
| Mercury | Qwen2-72B | |
|---|---|---|
| Provider | Inception | Alibaba (Qwen) |
| Noometry Index | 37.6 | 30.0 |
| Released | — | 2024-06-07 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 9 | 26 |
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Category by category
Coding Mercury leads
Mercury: 38.7 (#170), Qwen2-72B: 29.1 (#310)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| LMArena Coding | 1322 | 1196 |
| WeirdML | — | 11.3% |
| BigCodeBench Instruct | — | 38.5% |
| BigCodeBench Complete | — | 54% |
Agentic & Tool Use Not comparable
Mercury: —, Qwen2-72B: 17.0 (#146)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| TheAgentCompany | — | 1.1% |
| METR Time Horizons | — | 29.9% |
Reasoning Qwen2-72B leads
Mercury: 17.5 (#293), Qwen2-72B: 23.2 (#181)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| LMArena Hard Prompts | 1285 | 1191 |
| Kagi LLM Benchmark | 21.6% | — |
| Epoch Capabilities Index | — | 125.28 |
Math Not comparable
Mercury: —, Qwen2-72B: 30.2 (#236)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| LMArena Math | — | 1235 |
| MATH Level 5 | — | 39.1% |
Knowledge Not comparable
Mercury: —, Qwen2-72B: 21.2 (#275)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| GPQA Diamond | — | 40.8% |
| LMArena Expert | — | 1171 |
| MMLU | — | 82.4% |
Multilingual Mercury leads
Mercury: 41.6 (#206), Qwen2-72B: 35.9 (#244)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| LMArena Non-English | 1260 | 1176 |
| LMArena Chinese | — | 1240 |
| LMArena French | — | 1170 |
| LMArena German | — | 1151 |
| LMArena Japanese | — | 1111 |
| LMArena Korean | — | 1083 |
| LMArena Russian | — | 1169 |
| LMArena Spanish | — | 1169 |
Instruction Following Mercury leads
Mercury: 65.2 (#224), Qwen2-72B: 61.7 (#241)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| LMArena Instruction Following | 1239 | 1181 |
Long Context Mercury leads
Mercury: 38.4 (#198), Qwen2-72B: 36.1 (#235)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| LMArena Longer Query | 1266 | 1192 |
Writing & Preference Mercury leads
Mercury: 46.2 (#221), Qwen2-72B: 40.8 (#241)
| Benchmark | Mercury | Qwen2-72B |
|---|---|---|
| LMArena Text | 1282 | 1203 |
| LMArena Creative Writing | 1191 | 1181 |
| LMArena Multi-Turn | 1282 | 1196 |
Frequently asked questions
Is Mercury better than Qwen2-72B?
Mercury is the stronger model overall, scoring 37.6 to 30.0 on the Noometry Index.
Is Mercury or Qwen2-72B better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 29.1 in the Noometry coding category.
How many benchmarks do Mercury and Qwen2-72B share?
8 benchmarks have published results for both models. Mercury has 9 scored results on Noometry and Qwen2-72B has 26.