Model comparison
Llama 2-7B vs Mercury
Mercury is the stronger model overall, scoring 37.3 to 28.6 on the Noometry Index.
Last verified . 8 shared benchmarks.
MetaSummary
- They share 8 benchmarks with published results for both. Llama 2-7B 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 28.1.
- Llama 2-7B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-7B | Mercury | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 28.6 | 37.3 |
| Released | 2023-07-18 | — |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 29 | 9 |
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Category by category
Coding Mercury leads
Llama 2-7B: 28.7 (#302), Mercury: 38.1 (#164)
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Coding | 1002 | 1323 |
Reasoning Mercury leads
Llama 2-7B: 15.1 (#309), Mercury: 16.8 (#288)
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1009 | 1284 |
| Kagi LLM Benchmark | — | 21.6% |
| Chess Puzzles | 0% | — |
| BIG-Bench Hard | 39.2% | — |
| Epoch Capabilities Index | 98.54 | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Not comparable
Llama 2-7B: 28.2 (#231), Mercury: —
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Math | 1042 | — |
| GSM8K | 16.7% | — |
Knowledge Not comparable
Llama 2-7B: 27.7 (#243), Mercury: —
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Expert | 1036 | — |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| MMLU | 45.8% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, Mercury: —
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| ScienceQA | 43.1% | — |
Multilingual Mercury leads
Llama 2-7B: 23.9 (#288), Mercury: 41.7 (#201)
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Non-English | 973 | 1259 |
| LMArena Chinese | 973 | — |
| LMArena French | 969 | — |
| LMArena German | 978 | — |
| LMArena Russian | 995 | — |
| LMArena Spanish | 1007 | — |
Instruction Following Mercury leads
Llama 2-7B: 51.0 (#293), Mercury: 65.3 (#220)
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1006 | 1238 |
Long Context Mercury leads
Llama 2-7B: 30.4 (#282), Mercury: 38.3 (#193)
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Longer Query | 999 | 1264 |
Writing & Preference Mercury leads
Llama 2-7B: 28.1 (#293), Mercury: 46.2 (#216)
| Benchmark | Llama 2-7B | Mercury |
|---|---|---|
| LMArena Text | 1053 | 1282 |
| LMArena Creative Writing | 1033 | 1186 |
| LMArena Multi-Turn | 1029 | 1283 |
Frequently asked questions
Is Llama 2-7B better than Mercury?
Mercury is the stronger model overall, scoring 37.3 to 28.6 on the Noometry Index.
Is Llama 2-7B or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.1 versus 28.7 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Mercury share?
8 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Mercury has 9.