Model comparison
Gemini 3.8 Flash vs Llama 3-8B
Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 25.5 on the Noometry Index.
Last verified . 22 shared benchmarks.
Google
MetaSummary
- They share 22 benchmarks with published results for both. Gemini 3.8 Flash scores higher in 8 categories and Llama 3-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 3.8 Flash leads 74.8 to 7.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.9% for Gemini 3.8 Flash and 1.9% for Llama 3-8B.
- Llama 3-8B has downloadable open weights; the other is API-only.
Side by side
| Gemini 3.8 Flash | Llama 3-8B | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 61.8 | 25.5 |
| Released | 2026-09-02 | 2024-04-18 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 66K | — |
| Input $ / M tokens | $0.75 | — |
| Output $ / M tokens | $3.75 | — |
| Results tracked | 50 | 34 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Gemini 3.8 Flash leads
Gemini 3.8 Flash: 59.2 (#15), Llama 3-8B: 31.0 (#289)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| LMArena Coding | 1510 | 1152 |
| DeepSWE | 73.8% | — |
| FrontierCode | 41.2% | — |
| CursorBench | 39.6% | — |
| LMArena WebDev | 1584 | — |
| FrontierSWE | 19.6% | — |
| SciCode | 56.6% | — |
| WeirdML | 84.8% | — |
| BigCodeBench Instruct | — | 31.9% |
| BigCodeBench Complete | — | 36.9% |
| ALE-Bench | 1,270 | — |
| HumanEval+ | — | 56.7% |
| MBPP+ | — | 54.8% |
Agentic & Tool Use Not comparable
Gemini 3.8 Flash: 41.8 (#21), Llama 3-8B: —
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| APEX-Agents | 64.3% | — |
| Remote Labor Index | 5.8% | — |
| GDP.pdf | 23.4% | — |
| Vending-Bench 2 | 5,094 | — |
Reasoning Gemini 3.8 Flash leads
Gemini 3.8 Flash: 76.9 (#5), Llama 3-8B: 14.3 (#326)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| Chess Puzzles | 61% | 0% |
| LMArena Hard Prompts | 1508 | 1133 |
| DTBench | 95.7% | 43.9% |
| Epoch Capabilities Index | 156.71 | 116.45 |
| ARC-AGI-2 | 89.2% | — |
| NYT Connections (extended) | 97.4% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 18.3% | — |
| Mystery Game Puzzles | 47% | — |
| LMCA | 52.9% | — |
| Surface Evolver Bench | 76.9% | — |
| Adversarial NLI | — | 57.3% |
| ForecastBench | — | 58.6 |
| WinoGrande | — | 75.7% |
Math Gemini 3.8 Flash leads
Gemini 3.8 Flash: 65.3 (#28), Llama 3-8B: 8.8 (#323)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.9% | 1.9% |
| LMArena Math | 1528 | 1151 |
| FrontierMath (Tiers 1-3) | 68.4% | — |
| FrontierMath Tier 4 | 22% | — |
| ProofBench | 48% | — |
| MATH Level 5 | — | 6.1% |
Knowledge Gemini 3.8 Flash leads
Gemini 3.8 Flash: 74.8 (#2), Llama 3-8B: 7.8 (#308)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| GPQA Diamond | 95.4% | 26.1% |
| LMArena Expert | 1524 | 1113 |
| Humanity's Last Exam | 44.5% | — |
| SimpleQA Verified | 69.7% | — |
| ARC (AI2) Challenge | — | 82.8% |
| MMLU | — | 68.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |
Multimodal Not comparable
Gemini 3.8 Flash: 40.7 (#45), Llama 3-8B: —
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| LMArena Vision | 1314 | — |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 31.7% | — |
Multilingual Gemini 3.8 Flash leads
Gemini 3.8 Flash: 58.0 (#5), Llama 3-8B: 30.8 (#261)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| LMArena Non-English | 1491 | 1098 |
| LMArena Chinese | 1554 | 1076 |
| LMArena French | 1498 | 1159 |
| LMArena German | 1493 | 1104 |
| LMArena Japanese | 1502 | 967 |
| LMArena Korean | 1459 | 1004 |
| LMArena Russian | 1515 | 1109 |
| LMArena Spanish | 1485 | 1173 |
Instruction Following Gemini 3.8 Flash leads
Gemini 3.8 Flash: 78.0 (#13), Llama 3-8B: 58.4 (#260)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | 1490 | 1127 |
Long Context Gemini 3.8 Flash leads
Gemini 3.8 Flash: 46.3 (#24), Llama 3-8B: 34.2 (#251)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | 1508 | 1128 |
Writing & Preference Gemini 3.8 Flash leads
Gemini 3.8 Flash: 72.2 (#15), Llama 3-8B: 37.5 (#256)
| Benchmark | Gemini 3.8 Flash | Llama 3-8B |
|---|---|---|
| LMArena Text | 1499 | 1166 |
| LMArena Creative Writing | 1492 | 1150 |
| LMArena Multi-Turn | 1501 | 1152 |
| EQ-Bench Creative Writing | 1748 | — |
Frequently asked questions
Is Gemini 3.8 Flash better than Llama 3-8B?
Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 25.5 on the Noometry Index.
Is Gemini 3.8 Flash or Llama 3-8B better for coding?
Gemini 3.8 Flash scores higher on coding benchmarks: 59.2 versus 31.0 in the Noometry coding category.
How many benchmarks do Gemini 3.8 Flash and Llama 3-8B share?
22 benchmarks have published results for both models. Gemini 3.8 Flash has 50 scored results on Noometry and Llama 3-8B has 34.