Model comparison
Llama 2-7B vs Mercury 2.5
Mercury 2.5 is the stronger model overall, scoring 33.5 to 29.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
MetaSummary
- The widest gap is in coding, where Mercury 2.5 leads 39.5 to 29.2.
- Llama 2-7B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-7B | Mercury 2.5 | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 29.1 | 33.5 |
| Released | 2023-07-18 | 2026-09-08 |
| Weights | Open | Proprietary |
| Context window | — | 260K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.04 |
| Output $ / M tokens | — | $0.15 |
| Results tracked | 29 | 4 |
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Category by category
Coding Mercury 2.5 leads
Llama 2-7B: 29.2 (#307), Mercury 2.5: 39.5 (#156)
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| SciCode | — | 38.5% |
| LMArena Coding | 1002 | — |
| ALE-Bench | — | 301.65 |
Reasoning Mercury 2.5 leads
Llama 2-7B: 15.7 (#312), Mercury 2.5: 22.4 (#193)
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| CritPt | — | 0% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1009 | — |
| BIG-Bench Hard | 39.2% | — |
| Epoch Capabilities Index | 99.06 | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Llama 2-7B leads
Llama 2-7B: 30.7 (#233), Mercury 2.5: 23.3 (#272)
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| ProofBench | — | 3% |
| LMArena Math | 1042 | — |
| GSM8K | 16.7% | — |
Knowledge Not comparable
Llama 2-7B: 28.2 (#248), Mercury 2.5: —
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| 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 2.5: —
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| ScienceQA | 43.1% | — |
Multilingual Not comparable
Llama 2-7B: 23.8 (#293), Mercury 2.5: —
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| LMArena Non-English | 973 | — |
| LMArena Chinese | 973 | — |
| LMArena French | 970 | — |
| LMArena German | 978 | — |
| LMArena Russian | 995 | — |
| LMArena Spanish | 1007 | — |
Instruction Following Not comparable
Llama 2-7B: 50.8 (#298), Mercury 2.5: —
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| LMArena Instruction Following | 1006 | — |
Long Context Not comparable
Llama 2-7B: 30.4 (#287), Mercury 2.5: —
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| LMArena Longer Query | 999 | — |
Writing & Preference Not comparable
Llama 2-7B: 28.0 (#298), Mercury 2.5: —
| Benchmark | Llama 2-7B | Mercury 2.5 |
|---|---|---|
| LMArena Text | 1053 | — |
| LMArena Creative Writing | 1033 | — |
| LMArena Multi-Turn | 1029 | — |
Frequently asked questions
Is Llama 2-7B better than Mercury 2.5?
Mercury 2.5 is the stronger model overall, scoring 33.5 to 29.1 on the Noometry Index.
Is Llama 2-7B or Mercury 2.5 better for coding?
Mercury 2.5 scores higher on coding benchmarks: 39.5 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Mercury 2.5 share?
0 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Mercury 2.5 has 4.