Model comparison
Llama 3-8B vs Mercury
Mercury is the stronger model overall, scoring 37.6 to 25.5 on the Noometry Index.
Last verified . 8 shared benchmarks.
MetaSummary
- They share 8 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and Mercury in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Mercury leads 41.6 to 30.8.
- Llama 3-8B has downloadable open weights; the other is API-only.
Side by side
| Llama 3-8B | Mercury | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 25.5 | 37.6 |
| Released | 2024-04-18 | — |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 34 | 9 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Mercury leads
Llama 3-8B: 31.0 (#289), Mercury: 38.7 (#170)
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Coding | 1152 | 1322 |
| BigCodeBench Instruct | 31.9% | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Reasoning Mercury leads
Llama 3-8B: 14.3 (#326), Mercury: 17.5 (#293)
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1133 | 1285 |
| Kagi LLM Benchmark | — | 21.6% |
| Chess Puzzles | 0% | — |
| DTBench | 43.9% | — |
| Adversarial NLI | 57.3% | — |
| Epoch Capabilities Index | 116.45 | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |
Math Not comparable
Llama 3-8B: 8.8 (#323), Mercury: —
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |
Knowledge Not comparable
Llama 3-8B: 7.8 (#308), Mercury: —
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| GPQA Diamond | 26.1% | — |
| LMArena Expert | 1113 | — |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |
Multilingual Mercury leads
Llama 3-8B: 30.8 (#261), Mercury: 41.6 (#206)
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Non-English | 1098 | 1260 |
| LMArena Chinese | 1076 | — |
| LMArena French | 1159 | — |
| LMArena German | 1104 | — |
| LMArena Japanese | 967 | — |
| LMArena Korean | 1004 | — |
| LMArena Russian | 1109 | — |
| LMArena Spanish | 1173 | — |
Instruction Following Mercury leads
Llama 3-8B: 58.4 (#260), Mercury: 65.2 (#224)
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1127 | 1239 |
Long Context Mercury leads
Llama 3-8B: 34.2 (#251), Mercury: 38.4 (#198)
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Longer Query | 1128 | 1266 |
Writing & Preference Mercury leads
Llama 3-8B: 37.5 (#256), Mercury: 46.2 (#221)
| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Text | 1166 | 1282 |
| LMArena Creative Writing | 1150 | 1191 |
| LMArena Multi-Turn | 1152 | 1282 |
Frequently asked questions
Is Llama 3-8B better than Mercury?
Mercury is the stronger model overall, scoring 37.6 to 25.5 on the Noometry Index.
Is Llama 3-8B or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 31.0 in the Noometry coding category.
How many benchmarks do Llama 3-8B and Mercury share?
8 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Mercury has 9.