Model comparison
Llama 4 Scout vs Mercury
Mercury is the stronger model overall, scoring 37.6 to 27.7 on the Noometry Index.
Last verified . 9 shared benchmarks.
MetaSummary
- They share 9 benchmarks with published results for both. Llama 4 Scout scores higher in 1 category and Mercury in 5 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in coding, where Mercury leads 38.7 to 20.2.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 36.9% for Llama 4 Scout and 21.6% for Mercury.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Llama 4 Scout | Mercury | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 27.7 | 37.6 |
| Released | 2025-04-05 | — |
| Weights | Open | Proprietary |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.10 | — |
| Output $ / M tokens | $0.30 | — |
| Results tracked | 43 | 9 |
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Category by category
Coding Mercury leads
Llama 4 Scout: 20.2 (#339), Mercury: 38.7 (#170)
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| LMArena Coding | 1286 | 1322 |
| SWE-bench Verified (bash only) | 9.1% | — |
| SciCode | 17% | — |
| BigCodeBench Complete | 43.1% | — |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.6 (#119), Mercury: —
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning Mercury leads
Llama 4 Scout: 9.1 (#345), Mercury: 17.5 (#293)
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| Kagi LLM Benchmark | 36.9% | 21.6% |
| LMArena Hard Prompts | 1266 | 1285 |
| ARC-AGI-2 | 0% | — |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| DTBench | 57.9% | — |
| LMCA | 12% | — |
| Epoch Capabilities Index | 129.64 | — |
| ForecastBench | 57.5 | — |
Math Not comparable
Llama 4 Scout: 19.6 (#286), Mercury: —
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 7.8% | — |
| Omni-MATH | 37.3% | — |
| LMArena Math | 1287 | — |
| MATH Level 5 | 62.3% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
Knowledge Not comparable
Llama 4 Scout: 31.9 (#217), Mercury: —
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| GPQA Diamond | 51.8% | — |
| MMLU-Pro | 74.2% | — |
| Vectara Hallucination Rate | 7.7% | — |
| GPQA (HELM) | 50.7% | — |
| LMArena Expert | 1235 | — |
Multimodal Not comparable
Llama 4 Scout: 32.2 (#102), Mercury: —
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual Too close to call
Llama 4 Scout: 41.0 (#212), Mercury: 41.6 (#206)
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| LMArena Non-English | 1252 | 1260 |
| LMArena Chinese | 1255 | — |
| LMArena French | 1282 | — |
| LMArena German | 1272 | — |
| LMArena Japanese | 1206 | — |
| LMArena Korean | 1207 | — |
| LMArena Russian | 1263 | — |
| LMArena Spanish | 1278 | — |
Instruction Following Too close to call
Llama 4 Scout: 65.8 (#217), Mercury: 65.2 (#224)
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| LMArena Instruction Following | 1248 | 1239 |
| IFEval | 81.8% | — |
Long Context Mercury leads
Llama 4 Scout: 27.5 (#294), Mercury: 38.4 (#198)
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| LMArena Longer Query | 1265 | 1266 |
| Fiction.LiveBench | 36% | — |
Writing & Preference Mercury leads
Llama 4 Scout: 37.0 (#261), Mercury: 46.2 (#221)
| Benchmark | Llama 4 Scout | Mercury |
|---|---|---|
| LMArena Text | 1279 | 1282 |
| LMArena Creative Writing | 1249 | 1191 |
| LMArena Multi-Turn | 1280 | 1282 |
| EQ-Bench Creative Writing | 783 | — |
| WildBench | 78% | — |
Frequently asked questions
Is Llama 4 Scout better than Mercury?
Mercury is the stronger model overall, scoring 37.6 to 27.7 on the Noometry Index.
Is Llama 4 Scout or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 20.2 in the Noometry coding category.
How many benchmarks do Llama 4 Scout and Mercury share?
9 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and Mercury has 9.