Model comparison
Llama 3-70B vs Mercury
Mercury is the stronger model overall, scoring 37.6 to 28.8 on the Noometry Index.
Last verified . 9 shared benchmarks.
MetaSummary
- They share 9 benchmarks with published results for both. Llama 3-70B scores higher in 1 category and Mercury in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Mercury leads 41.6 to 33.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 35.1% for Llama 3-70B and 21.6% for Mercury.
- Llama 3-70B has downloadable open weights; the other is API-only.
Side by side
| Llama 3-70B | Mercury | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 28.8 | 37.6 |
| Released | 2024-04-18 | — |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 31 | 9 |
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Category by category
Coding Mercury leads
Llama 3-70B: 35.8 (#218), Mercury: 38.7 (#170)
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| LMArena Coding | 1206 | 1322 |
| BigCodeBench Instruct | 43.6% | — |
| BigCodeBench Complete | 54.5% | — |
| HumanEval+ | 72% | — |
| MBPP+ | 69% | — |
Agentic & Tool Use Not comparable
Llama 3-70B: 21.1 (#139), Mercury: —
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| Cybench | 5% | — |
Reasoning Too close to call
Llama 3-70B: 18.0 (#288), Mercury: 17.5 (#293)
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| Kagi LLM Benchmark | 35.1% | 21.6% |
| LMArena Hard Prompts | 1195 | 1285 |
| DTBench | 54.2% | — |
| Epoch Capabilities Index | 122.93 | — |
| ForecastBench | 57.1 | — |
| WinoGrande | 83.5% | — |
Math Not comparable
Llama 3-70B: 12.8 (#305), Mercury: —
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 4.3% | — |
| LMArena Math | 1218 | — |
| MATH Level 5 | 22.6% | — |
Knowledge Not comparable
Llama 3-70B: 20.8 (#277), Mercury: —
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| GPQA Diamond | 40.6% | — |
| LMArena Expert | 1149 | — |
| MMLU | 79.3% | — |
Multilingual Mercury leads
Llama 3-70B: 33.6 (#251), Mercury: 41.6 (#206)
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| LMArena Non-English | 1142 | 1260 |
| LMArena Chinese | 1114 | — |
| LMArena French | 1232 | — |
| LMArena German | 1169 | — |
| LMArena Japanese | 1017 | — |
| LMArena Korean | 1017 | — |
| LMArena Russian | 1159 | — |
| LMArena Spanish | 1241 | — |
Instruction Following Mercury leads
Llama 3-70B: 62.5 (#238), Mercury: 65.2 (#224)
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1194 | 1239 |
Long Context Mercury leads
Llama 3-70B: 35.6 (#240), Mercury: 38.4 (#198)
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| LMArena Longer Query | 1174 | 1266 |
Writing & Preference Mercury leads
Llama 3-70B: 42.8 (#231), Mercury: 46.2 (#221)
| Benchmark | Llama 3-70B | Mercury |
|---|---|---|
| LMArena Text | 1221 | 1282 |
| LMArena Creative Writing | 1210 | 1191 |
| LMArena Multi-Turn | 1223 | 1282 |
Frequently asked questions
Is Llama 3-70B better than Mercury?
Mercury is the stronger model overall, scoring 37.6 to 28.8 on the Noometry Index.
Is Llama 3-70B or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 35.8 in the Noometry coding category.
How many benchmarks do Llama 3-70B and Mercury share?
9 benchmarks have published results for both models. Llama 3-70B has 31 scored results on Noometry and Mercury has 9.