Model comparison
Gemini 2.5 Pro vs Llama 2-70B
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 24.4 on the Noometry Index.
Last verified . 23 shared benchmarks.
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MetaSummary
- They share 23 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 8 categories and Llama 2-70B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 2.5 Pro leads 56.0 to 7.4.
- The biggest single-benchmark swing is MATH Level 5: 95.9% for Gemini 2.5 Pro and 3.3% for Llama 2-70B.
- Llama 2-70B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Pro | Llama 2-70B | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 45.0 | 24.4 |
| Released | 2025-03-25 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 66K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 78 | 35 |
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Category by category
Coding Gemini 2.5 Pro leads
Gemini 2.5 Pro: 42.4 (#101), Llama 2-70B: 31.4 (#286)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| LMArena Coding | 1452 | 1079 |
| SWE-bench Verified | 57.6% | — |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| LMArena WebDev | 1227 | — |
| SciCode | 42.8% | — |
| GSO | 3.9% | — |
| WeirdML | 54% | — |
| LiveBench Coding | 85.9% | — |
| CadEval | 64% | — |
| ALE-Bench | 785.52 | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Pro: 29.2 (#88), Llama 2-70B: —
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| Terminal-Bench | 32.6% | — |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |
| Vending-Bench 2 | 573.64 | — |
Reasoning Gemini 2.5 Pro leads
Gemini 2.5 Pro: 28.8 (#99), Llama 2-70B: 14.4 (#325)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| LMArena Hard Prompts | 1455 | 1073 |
| DTBench | 82.4% | 41.6% |
| Epoch Capabilities Index | 145.32 | 113.79 |
| ForecastBench | 61.3 | 51.4 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| ARC-AGI-1 | 41% | — |
| CritPt | 2% | — |
| Chess Puzzles | 20% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| BIG-Bench Hard | — | 64.9% |
| CommonsenseQA 2.0 | — | 50% |
| HellaSwag | — | 85.3% |
| LAMBADA | — | 78.9% |
| LiveBench | 82.3% | — |
| PIQA | — | 82.8% |
| WinoGrande | — | 80.2% |
Math Gemini 2.5 Pro leads
Gemini 2.5 Pro: 32.5 (#213), Llama 2-70B: 8.1 (#326)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 84.7% | 0% |
| LMArena Math | 1450 | 1091 |
| MATH Level 5 | 95.9% | 3.3% |
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| Omni-MATH | 41.6% | — |
| LiveBench Math | 90.2% | — |
| FrontierMath (Feb 2025 set) | 14.1% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
| GSM8K | — | 69.6% |
Knowledge Gemini 2.5 Pro leads
Gemini 2.5 Pro: 56.0 (#46), Llama 2-70B: 7.4 (#310)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| GPQA Diamond | 85.3% | 26.3% |
| LMArena Expert | 1452 | 1039 |
| Humanity's Last Exam | 21.6% | — |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| GPQA (HELM) | 74.9% | — |
| ARC (AI2) Challenge | — | 78.3% |
| BoolQ | — | 88.6% |
| MMLU | — | 69.9% |
| OpenBookQA | — | 60.2% |
| TriviaQA | — | 87.6% |
Multimodal Not comparable
Gemini 2.5 Pro: 45.2 (#18), Llama 2-70B: —
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| LMArena Vision | 1263 | — |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |
Multilingual Gemini 2.5 Pro leads
Gemini 2.5 Pro: 55.3 (#31), Llama 2-70B: 27.7 (#274)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| LMArena Non-English | 1451 | 1045 |
| LMArena Chinese | 1507 | 995 |
| LMArena French | 1472 | 1090 |
| LMArena German | 1487 | 1041 |
| LMArena Japanese | 1461 | 927 |
| LMArena Korean | 1434 | 964 |
| LMArena Russian | 1461 | 1083 |
| LMArena Spanish | 1473 | 1143 |
Instruction Following Gemini 2.5 Pro leads
Gemini 2.5 Pro: 75.0 (#75), Llama 2-70B: 54.9 (#278)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| LMArena Instruction Following | 1437 | 1071 |
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
Long Context Gemini 2.5 Pro leads
Gemini 2.5 Pro: 59.8 (#5), Llama 2-70B: 32.3 (#270)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| LMArena Longer Query | 1449 | 1062 |
| Fiction.LiveBench | 91.7% | — |
Writing & Preference Gemini 2.5 Pro leads
Gemini 2.5 Pro: 63.7 (#62), Llama 2-70B: 32.3 (#279)
| Benchmark | Gemini 2.5 Pro | Llama 2-70B |
|---|---|---|
| LMArena Text | 1458 | 1115 |
| LMArena Creative Writing | 1454 | 1075 |
| LMArena Multi-Turn | 1453 | 1088 |
| Short-Story Creative Writing | 83.8% | — |
| EQ-Bench Creative Writing | 1421 | — |
| WildBench | 85.7% | — |
| LiveBench Language | 67.8% | — |
Frequently asked questions
Is Gemini 2.5 Pro better than Llama 2-70B?
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 24.4 on the Noometry Index.
Is Gemini 2.5 Pro or Llama 2-70B better for coding?
Gemini 2.5 Pro scores higher on coding benchmarks: 42.4 versus 31.4 in the Noometry coding category.
How many benchmarks do Gemini 2.5 Pro and Llama 2-70B share?
23 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and Llama 2-70B has 35.