Model comparison
Llama 2-70B vs Mercury 2.5
Mercury 2.5 is the stronger model overall, scoring 33.5 to 24.4 on the Noometry Index.
Last verified . 0 shared benchmarks.
MetaSummary
- The widest gap is in math, where Mercury 2.5 leads 23.3 to 8.1.
- Llama 2-70B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-70B | Mercury 2.5 | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 24.4 | 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 | 35 | 4 |
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Category by category
Coding Mercury 2.5 leads
Llama 2-70B: 31.4 (#286), Mercury 2.5: 39.5 (#156)
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| SciCode | — | 38.5% |
| LMArena Coding | 1079 | — |
| ALE-Bench | — | 301.65 |
Reasoning Mercury 2.5 leads
Llama 2-70B: 14.4 (#325), Mercury 2.5: 22.4 (#193)
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| CritPt | — | 0% |
| LMArena Hard Prompts | 1073 | — |
| 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 Mercury 2.5 leads
Llama 2-70B: 8.1 (#326), Mercury 2.5: 23.3 (#272)
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0% | — |
| ProofBench | — | 3% |
| LMArena Math | 1091 | — |
| MATH Level 5 | 3.3% | — |
| GSM8K | 69.6% | — |
Knowledge Not comparable
Llama 2-70B: 7.4 (#310), Mercury 2.5: —
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| 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 Not comparable
Llama 2-70B: 27.7 (#274), Mercury 2.5: —
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| LMArena Non-English | 1045 | — |
| LMArena Chinese | 995 | — |
| LMArena French | 1090 | — |
| LMArena German | 1041 | — |
| LMArena Japanese | 927 | — |
| LMArena Korean | 964 | — |
| LMArena Russian | 1083 | — |
| LMArena Spanish | 1143 | — |
Instruction Following Not comparable
Llama 2-70B: 54.9 (#278), Mercury 2.5: —
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| LMArena Instruction Following | 1071 | — |
Long Context Not comparable
Llama 2-70B: 32.3 (#270), Mercury 2.5: —
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| LMArena Longer Query | 1062 | — |
Writing & Preference Not comparable
Llama 2-70B: 32.3 (#279), Mercury 2.5: —
| Benchmark | Llama 2-70B | Mercury 2.5 |
|---|---|---|
| LMArena Text | 1115 | — |
| LMArena Creative Writing | 1075 | — |
| LMArena Multi-Turn | 1088 | — |
Frequently asked questions
Is Llama 2-70B better than Mercury 2.5?
Mercury 2.5 is the stronger model overall, scoring 33.5 to 24.4 on the Noometry Index.
Is Llama 2-70B or Mercury 2.5 better for coding?
Mercury 2.5 scores higher on coding benchmarks: 39.5 versus 31.4 in the Noometry coding category.
How many benchmarks do Llama 2-70B and Mercury 2.5 share?
0 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Mercury 2.5 has 4.