Model comparison
Llama 2-70B vs Mercury
Mercury is the stronger model overall, scoring 37.6 to 24.4 on the Noometry Index.
Last verified . 8 shared benchmarks.
MetaSummary
- They share 8 benchmarks with published results for both. Llama 2-70B scores higher in 0 categories and Mercury in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mercury leads 46.2 to 32.3.
- Llama 2-70B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-70B | Mercury | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 24.4 | 37.6 |
| Released | 2023-07-18 | — |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 35 | 9 |
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Category by category
Coding Mercury leads
Llama 2-70B: 31.4 (#286), Mercury: 38.7 (#170)
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| LMArena Coding | 1079 | 1322 |
Reasoning Mercury leads
Llama 2-70B: 14.4 (#325), Mercury: 17.5 (#293)
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1073 | 1285 |
| Kagi LLM Benchmark | — | 21.6% |
| DTBench | 41.6% | — |
| BIG-Bench Hard | 64.9% | — |
| CommonsenseQA 2.0 | 50% | — |
| Epoch Capabilities Index | 113.79 | — |
| ForecastBench | 51.4 | — |
| HellaSwag | 85.3% | — |
| LAMBADA | 78.9% | — |
| PIQA | 82.8% | — |
| WinoGrande | 80.2% | — |
Math Not comparable
Llama 2-70B: 8.1 (#326), Mercury: —
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0% | — |
| LMArena Math | 1091 | — |
| MATH Level 5 | 3.3% | — |
| GSM8K | 69.6% | — |
Knowledge Not comparable
Llama 2-70B: 7.4 (#310), Mercury: —
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| GPQA Diamond | 26.3% | — |
| LMArena Expert | 1039 | — |
| ARC (AI2) Challenge | 78.3% | — |
| BoolQ | 88.6% | — |
| MMLU | 69.9% | — |
| OpenBookQA | 60.2% | — |
| TriviaQA | 87.6% | — |
Multilingual Mercury leads
Llama 2-70B: 27.7 (#274), Mercury: 41.6 (#206)
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| LMArena Non-English | 1045 | 1260 |
| LMArena Chinese | 995 | — |
| LMArena French | 1090 | — |
| LMArena German | 1041 | — |
| LMArena Japanese | 927 | — |
| LMArena Korean | 964 | — |
| LMArena Russian | 1083 | — |
| LMArena Spanish | 1143 | — |
Instruction Following Mercury leads
Llama 2-70B: 54.9 (#278), Mercury: 65.2 (#224)
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1071 | 1239 |
Long Context Mercury leads
Llama 2-70B: 32.3 (#270), Mercury: 38.4 (#198)
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| LMArena Longer Query | 1062 | 1266 |
Writing & Preference Mercury leads
Llama 2-70B: 32.3 (#279), Mercury: 46.2 (#221)
| Benchmark | Llama 2-70B | Mercury |
|---|---|---|
| LMArena Text | 1115 | 1282 |
| LMArena Creative Writing | 1075 | 1191 |
| LMArena Multi-Turn | 1088 | 1282 |
Frequently asked questions
Is Llama 2-70B better than Mercury?
Mercury is the stronger model overall, scoring 37.6 to 24.4 on the Noometry Index.
Is Llama 2-70B or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 31.4 in the Noometry coding category.
How many benchmarks do Llama 2-70B and Mercury share?
8 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Mercury has 9.