# Gemini 1.5 Pro (May 2024) vs Llama-3.3-70B-Instruct

> Gemini 1.5 Pro (May 2024) is the stronger model overall, scoring 32.1 to 30.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-1-5-pro-vs-llama-3-3-70b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. Gemini 1.5 Pro (May 2024) scores higher in 5 categories and Llama-3.3-70B-Instruct in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemini 1.5 Pro (May 2024) leads 39.8 to 26.4.
- The biggest single-benchmark swing is MATH Level 5: 70.4% for Gemini 1.5 Pro (May 2024) and 41.6% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 32.1 | 30.6 |
| Rank | 261 | 291 |
| Context | — | 128K |
| Input $/M | — | $0.10 |
| Output $/M | — | $0.32 |
| Weights | Proprietary | Open |

## Coding

- Gemini 1.5 Pro (May 2024): 34.2 (#241)
- Llama-3.3-70B-Instruct: 31.0 (#290)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| WeirdML | 22.2% | 14.4% |
| BigCodeBench Instruct | 43.8% | 46.9% |
| LMArena Coding | 1294 | 1268 |
| BigCodeBench Complete | 57.5% | 57.5% |
| SciCode | — | 26% |
| LiveBench Coding | — | 36.6% |
| CadEval | 34% | — |
| HumanEval+ | 79.3% | — |
| MBPP+ | 74.6% | — |

## Agentic & Tool Use

- Gemini 1.5 Pro (May 2024): 17.9 (#145)
- Llama-3.3-70B-Instruct: 25.8 (#105)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| BALROG | 21% | 23% |
| Berkeley Function Calling Leaderboard | — | 31.9% |
| TheAgentCompany | 3.4% | — |
| Cybench | 7.5% | — |

## Reasoning

- Gemini 1.5 Pro (May 2024): 12.3 (#338)
- Llama-3.3-70B-Instruct: 14.1 (#327)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| SimpleBench | 27.1% | 19.9% |
| LMArena Hard Prompts | 1296 | 1257 |
| DTBench | 59% | 59.5% |
| Epoch Capabilities Index | 131.73 | 127.33 |
| ForecastBench | 58.4 | 58.6 |
| ARC-AGI-2 | 0.8% | — |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 50.8% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| BIG-Bench Hard | 89.2% | — |
| LiveBench | — | 50.2% |

## Math

- Gemini 1.5 Pro (May 2024): 25.8 (#266)
- Llama-3.3-70B-Instruct: 15.3 (#298)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 23.1% | 5.1% |
| LMArena Math | 1315 | 1267 |
| MATH Level 5 | 70.4% | 41.6% |
| Omni-MATH | 36.4% | — |
| LiveBench Math | — | 42.2% |

## Knowledge

- Gemini 1.5 Pro (May 2024): 29.4 (#239)
- Llama-3.3-70B-Instruct: 30.6 (#226)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| GPQA Diamond | 57.2% | 47.4% |
| Confabulations | 13.5% | 22.8% |
| LMArena Expert | 1279 | 1225 |
| MMLU | 86.9% | 86.3% |
| Humanity's Last Exam | 4.6% | — |
| MMLU-Pro | 73.7% | — |
| Vectara Hallucination Rate | — | 4.1% |
| GPQA (HELM) | 53.4% | — |

## Multimodal

- Gemini 1.5 Pro (May 2024): 36.8 (#77)
- Llama-3.3-70B-Instruct: —

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Vision | 1161 | — |
| Video-MME | 75% | — |

## Multilingual

- Gemini 1.5 Pro (May 2024): 45.3 (#174)
- Llama-3.3-70B-Instruct: 39.9 (#220)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1312 | 1236 |
| LMArena Chinese | 1331 | 1217 |
| LMArena French | 1302 | 1281 |
| LMArena German | 1286 | 1251 |
| LMArena Japanese | 1292 | 1150 |
| LMArena Korean | 1298 | 1143 |
| LMArena Russian | 1320 | 1252 |
| LMArena Spanish | 1311 | 1270 |

## Instruction Following

- Gemini 1.5 Pro (May 2024): 68.6 (#185)
- Llama-3.3-70B-Instruct: 71.1 (#157)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1297 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
| IFEval | 83.7% | — |

## Long Context

- Gemini 1.5 Pro (May 2024): 39.8 (#169)
- Llama-3.3-70B-Instruct: 26.4 (#295)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1308 | 1256 |
| Fiction.LiveBench | — | 33.3% |

## Writing & Preference

- Gemini 1.5 Pro (May 2024): 52.4 (#172)
- Llama-3.3-70B-Instruct: 47.6 (#207)

| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1319 | 1274 |
| LMArena Creative Writing | 1333 | 1250 |
| LMArena Multi-Turn | 1296 | 1280 |
| WildBench | 81.3% | — |
| LiveBench Language | — | 39.2% |

## FAQ

### Is Gemini 1.5 Pro (May 2024) better than Llama-3.3-70B-Instruct?

Gemini 1.5 Pro (May 2024) is the stronger model overall, scoring 32.1 to 30.6 on the Noometry Index.

### Is Gemini 1.5 Pro (May 2024) or Llama-3.3-70B-Instruct better for coding?

Gemini 1.5 Pro (May 2024) scores higher on coding benchmarks: 34.2 versus 31.0 in the Noometry coding category.

### How many benchmarks do Gemini 1.5 Pro (May 2024) and Llama-3.3-70B-Instruct share?

30 benchmarks have published results for both models. Gemini 1.5 Pro (May 2024) has 45 scored results on Noometry and Llama-3.3-70B-Instruct has 43.