Model comparison
Llama 2-13B vs Mercury
Mercury is the stronger model overall, scoring 37.3 to 29.1 on the Noometry Index.
Last verified . 8 shared benchmarks.
MetaSummary
- They share 8 benchmarks with published results for both. Llama 2-13B 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 30.0.
- Llama 2-13B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-13B | Mercury | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 29.1 | 37.3 |
| Released | 2023-07-18 | — |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 32 | 9 |
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Category by category
Coding Mercury leads
Llama 2-13B: 30.4 (#287), Mercury: 38.1 (#164)
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Coding | 1062 | 1323 |
Reasoning Mercury leads
Llama 2-13B: 12.3 (#333), Mercury: 16.8 (#288)
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1051 | 1284 |
| Kagi LLM Benchmark | — | 21.6% |
| Chess Puzzles | 0% | — |
| DTBench | 42.2% | — |
| BIG-Bench Hard | 58.2% | — |
| Epoch Capabilities Index | 105.8 | — |
| HellaSwag | 80.7% | — |
| LAMBADA | 76.5% | — |
| PIQA | 80.8% | — |
| WinoGrande | 72.8% | — |
Math Not comparable
Llama 2-13B: 28.7 (#226), Mercury: —
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Math | 1065 | — |
| GSM8K | 36.9% | — |
Knowledge Not comparable
Llama 2-13B: 27.5 (#244), Mercury: —
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Expert | 1030 | — |
| ARC (AI2) Challenge | 60.3% | — |
| BoolQ | 82.4% | — |
| MMLU | 55.6% | — |
| OpenBookQA | 57% | — |
| TriviaQA | 79.6% | — |
Multimodal Not comparable
Llama 2-13B: —, Mercury: —
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| ScienceQA | 55.8% | — |
Multilingual Mercury leads
Llama 2-13B: 26.7 (#274), Mercury: 41.7 (#201)
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Non-English | 1024 | 1259 |
| LMArena Chinese | 1001 | — |
| LMArena French | 1043 | — |
| LMArena German | 1009 | — |
| LMArena Japanese | 894 | — |
| LMArena Korean | 953 | — |
| LMArena Russian | 1055 | — |
| LMArena Spanish | 1086 | — |
Instruction Following Mercury leads
Llama 2-13B: 53.5 (#282), Mercury: 65.3 (#220)
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1046 | 1238 |
Long Context Mercury leads
Llama 2-13B: 32.3 (#264), Mercury: 38.3 (#193)
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Longer Query | 1064 | 1264 |
Writing & Preference Mercury leads
Llama 2-13B: 30.0 (#284), Mercury: 46.2 (#216)
| Benchmark | Llama 2-13B | Mercury |
|---|---|---|
| LMArena Text | 1085 | 1282 |
| LMArena Creative Writing | 1047 | 1186 |
| LMArena Multi-Turn | 1050 | 1283 |
Frequently asked questions
Is Llama 2-13B better than Mercury?
Mercury is the stronger model overall, scoring 37.3 to 29.1 on the Noometry Index.
Is Llama 2-13B or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.1 versus 30.4 in the Noometry coding category.
How many benchmarks do Llama 2-13B and Mercury share?
8 benchmarks have published results for both models. Llama 2-13B has 32 scored results on Noometry and Mercury has 9.