Model comparison
Llama 3.2 1B vs Mercury
Mercury is the stronger model overall, scoring 37.6 to 20.1 on the Noometry Index.
Last verified . 8 shared benchmarks.
MetaSummary
- They share 8 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Mercury in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mercury leads 46.2 to 21.3.
- Llama 3.2 1B has downloadable open weights; the other is API-only.
Side by side
| Llama 3.2 1B | Mercury | |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 20.1 | 37.6 |
| Released | 2024-09-24 | — |
| Weights | Open | Proprietary |
| Context window | 60K | — |
| Max output | 54K | — |
| Input $ / M tokens | $0.027 | — |
| Output $ / M tokens | $0.20 | — |
| Results tracked | 22 | 9 |
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Category by category
Coding Mercury leads
Llama 3.2 1B: 21.1 (#338), Mercury: 38.7 (#170)
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| LMArena Coding | 1070 | 1322 |
| BigCodeBench Instruct | 8.2% | — |
| BigCodeBench Complete | 11.3% | — |
Agentic & Tool Use Not comparable
Llama 3.2 1B: 14.6 (#150), Mercury: —
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | — |
| BALROG | 6.6% | — |
Reasoning Mercury leads
Llama 3.2 1B: 16.2 (#308), Mercury: 17.5 (#293)
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1044 | 1285 |
| Kagi LLM Benchmark | — | 21.6% |
| Chess Puzzles | 0% | — |
| Epoch Capabilities Index | 101.99 | — |
Math Not comparable
Llama 3.2 1B: 10.4 (#313), Mercury: —
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | — |
| LMArena Math | 1086 | — |
Knowledge Not comparable
Llama 3.2 1B: 7.2 (#312), Mercury: —
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| GPQA Diamond | 23.9% | — |
| LMArena Expert | 1007 | — |
Multilingual Mercury leads
Llama 3.2 1B: 23.8 (#292), Mercury: 41.6 (#206)
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| LMArena Non-English | 973 | 1260 |
| LMArena Chinese | 959 | — |
| LMArena German | 1014 | — |
| LMArena Russian | 941 | — |
Instruction Following Mercury leads
Llama 3.2 1B: 52.4 (#290), Mercury: 65.2 (#224)
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1031 | 1239 |
Long Context Mercury leads
Llama 3.2 1B: 31.9 (#274), Mercury: 38.4 (#198)
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| LMArena Longer Query | 1050 | 1266 |
Writing & Preference Mercury leads
Llama 3.2 1B: 21.3 (#310), Mercury: 46.2 (#221)
| Benchmark | Llama 3.2 1B | Mercury |
|---|---|---|
| LMArena Text | 1055 | 1282 |
| LMArena Creative Writing | 1033 | 1191 |
| LMArena Multi-Turn | 1030 | 1282 |
| EQ-Bench Creative Writing | 200 | — |
Frequently asked questions
Is Llama 3.2 1B better than Mercury?
Mercury is the stronger model overall, scoring 37.6 to 20.1 on the Noometry Index.
Is Llama 3.2 1B or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 21.1 in the Noometry coding category.
How many benchmarks do Llama 3.2 1B and Mercury share?
8 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Mercury has 9.