Model comparison
Gemini 2.0 Flash (Feb 2025) vs Llama 3-8B
Gemini 2.0 Flash (Feb 2025) is the stronger model overall, scoring 35.1 to 25.5 on the Noometry Index.
Last verified . 25 shared benchmarks.
Google
MetaSummary
- They share 25 benchmarks with published results for both. Gemini 2.0 Flash (Feb 2025) scores higher in 7 categories and Llama 3-8B in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemini 2.0 Flash (Feb 2025) leads 37.9 to 8.8.
- The biggest single-benchmark swing is MATH Level 5: 82.2% for Gemini 2.0 Flash (Feb 2025) and 6.1% for Llama 3-8B.
- Llama 3-8B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.0 Flash (Feb 2025) | Llama 3-8B | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 35.1 | 25.5 |
| Released | 2024-12-06 | 2024-04-18 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 54 | 34 |
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Category by category
Coding Llama 3-8B leads
Gemini 2.0 Flash (Feb 2025): 28.4 (#315), Llama 3-8B: 31.0 (#289)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| BigCodeBench Instruct | 45.9% | 31.9% |
| LMArena Coding | 1350 | 1152 |
| BigCodeBench Complete | 59.9% | 36.9% |
| SWE-bench Verified (bash only) | 13.5% | — |
| Aider Polyglot | 38.2% | — |
| WeirdML | 25.8% | — |
| LiveBench Coding | 63.4% | — |
| CadEval | 30% | — |
| HumanEval+ | — | 56.7% |
| MBPP+ | — | 54.8% |
Agentic & Tool Use Not comparable
Gemini 2.0 Flash (Feb 2025): 28.1 (#92), Llama 3-8B: —
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| TheAgentCompany | 11.4% | — |
Reasoning Too close to call
Gemini 2.0 Flash (Feb 2025): 15.2 (#318), Llama 3-8B: 14.3 (#326)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| LMArena Hard Prompts | 1346 | 1133 |
| DTBench | 63.2% | 43.9% |
| Epoch Capabilities Index | 135.36 | 116.45 |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 31.1% | — |
| Kagi LLM Benchmark | 37.8% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 1.1% | — |
| LiveBench Reasoning | 78.2% | — |
| LiveBench Data Analysis | 69.4% | — |
| Adversarial NLI | — | 57.3% |
| ForecastBench | — | 58.6 |
| LiveBench | 66.9% | — |
| WinoGrande | — | 75.7% |
Math Gemini 2.0 Flash (Feb 2025) leads
Gemini 2.0 Flash (Feb 2025): 37.9 (#146), Llama 3-8B: 8.8 (#323)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 57.8% | 1.9% |
| LMArena Math | 1352 | 1151 |
| MATH Level 5 | 82.2% | 6.1% |
| Omni-MATH | 45.9% | — |
| LiveBench Math | 75.8% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |
Knowledge Gemini 2.0 Flash (Feb 2025) leads
Gemini 2.0 Flash (Feb 2025): 32.0 (#213), Llama 3-8B: 7.8 (#308)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| GPQA Diamond | 64.1% | 26.1% |
| LMArena Expert | 1339 | 1113 |
| MMLU | 79.7% | 68.8% |
| Humanity's Last Exam | 6.6% | — |
| MMLU-Pro | 73.7% | — |
| Confabulations | 12.4% | — |
| GPQA (HELM) | 55.6% | — |
| ARC (AI2) Challenge | — | 82.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |
Multimodal Not comparable
Gemini 2.0 Flash (Feb 2025): 36.5 (#79), Llama 3-8B: —
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| LMArena Vision | 1158 | — |
| GeoBench | 77% | — |
Multilingual Gemini 2.0 Flash (Feb 2025) leads
Gemini 2.0 Flash (Feb 2025): 47.4 (#149), Llama 3-8B: 30.8 (#261)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| LMArena Non-English | 1342 | 1098 |
| LMArena Chinese | 1373 | 1076 |
| LMArena French | 1391 | 1159 |
| LMArena German | 1353 | 1104 |
| LMArena Japanese | 1294 | 967 |
| LMArena Korean | 1313 | 1004 |
| LMArena Russian | 1351 | 1109 |
| LMArena Spanish | 1363 | 1173 |
Instruction Following Gemini 2.0 Flash (Feb 2025) leads
Gemini 2.0 Flash (Feb 2025): 74.4 (#97), Llama 3-8B: 58.4 (#260)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | 1336 | 1127 |
| LiveBench Instruction Following | 85.8% | — |
| IFEval | 84.1% | — |
Long Context Gemini 2.0 Flash (Feb 2025) leads
Gemini 2.0 Flash (Feb 2025): 38.1 (#203), Llama 3-8B: 34.2 (#251)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | 1344 | 1128 |
| Fiction.LiveBench | 61.1% | — |
Writing & Preference Gemini 2.0 Flash (Feb 2025) leads
Gemini 2.0 Flash (Feb 2025): 49.5 (#190), Llama 3-8B: 37.5 (#256)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Llama 3-8B |
|---|---|---|
| LMArena Text | 1354 | 1166 |
| LMArena Creative Writing | 1340 | 1150 |
| LMArena Multi-Turn | 1350 | 1152 |
| Short-Story Creative Writing | 73.8% | — |
| EQ-Bench Creative Writing | 1128 | — |
| WildBench | 80% | — |
| LiveBench Language | 51.3% | — |
Frequently asked questions
Is Gemini 2.0 Flash (Feb 2025) better than Llama 3-8B?
Gemini 2.0 Flash (Feb 2025) is the stronger model overall, scoring 35.1 to 25.5 on the Noometry Index.
Is Gemini 2.0 Flash (Feb 2025) or Llama 3-8B better for coding?
Llama 3-8B scores higher on coding benchmarks: 31.0 versus 28.4 in the Noometry coding category.
How many benchmarks do Gemini 2.0 Flash (Feb 2025) and Llama 3-8B share?
25 benchmarks have published results for both models. Gemini 2.0 Flash (Feb 2025) has 54 scored results on Noometry and Llama 3-8B has 34.