# Gemini 3.8 Flash vs Llama 4 Scout

> Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 27.7 on the Noometry Index. Llama 4 Scout costs 10.0× less per token, which makes it the better buy when Gemini 3.8 Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-8-flash-vs-llama-4-scout
- Last updated: 2026-10-10
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. Gemini 3.8 Flash scores higher in 10 categories and Llama 4 Scout in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.8 Flash leads 76.9 to 9.1.
- The biggest single-benchmark swing is ARC-AGI-1: 98.5% for Gemini 3.8 Flash and 0.5% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.8 Flash.
- Gemini 3.8 Flash accepts more context: 1.05M tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 61.8 | 27.7 |
| Rank | 11 | 330 |
| Context | 1.05M | 128K |
| Input $/M | $0.75 | $0.10 |
| Output $/M | $3.75 | $0.30 |
| Weights | Proprietary | Open |

## Coding

- Gemini 3.8 Flash: 59.2 (#15)
- Llama 4 Scout: 20.2 (#339)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| SciCode | 56.6% | 17% |
| LMArena Coding | 1510 | 1286 |
| DeepSWE | 73.8% | — |
| FrontierCode | 41.2% | — |
| SWE-bench Verified (bash only) | — | 9.1% |
| CursorBench | 39.6% | — |
| LMArena WebDev | 1584 | — |
| FrontierSWE | 19.6% | — |
| WeirdML | 84.8% | — |
| BigCodeBench Complete | — | 43.1% |
| ALE-Bench | 1,270 | — |

## Agentic & Tool Use

- Gemini 3.8 Flash: 41.8 (#21)
- Llama 4 Scout: 24.6 (#119)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| APEX-Agents | 64.3% | — |
| Berkeley Function Calling Leaderboard | — | 28.1% |
| Remote Labor Index | 5.8% | — |
| GDP.pdf | 23.4% | — |
| Vending-Bench 2 | 5,094 | — |

## Reasoning

- Gemini 3.8 Flash: 76.9 (#5)
- Llama 4 Scout: 9.1 (#345)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| ARC-AGI-2 | 89.2% | 0% |
| ARC-AGI-1 | 98.5% | 0.5% |
| CritPt | 18.3% | 0% |
| LMArena Hard Prompts | 1508 | 1266 |
| DTBench | 95.7% | 57.9% |
| LMCA | 52.9% | 12% |
| Epoch Capabilities Index | 156.71 | 129.64 |
| Kagi LLM Benchmark | — | 36.9% |
| NYT Connections (extended) | 97.4% | — |
| Chess Puzzles | 61% | — |
| Mystery Game Puzzles | 47% | — |
| Surface Evolver Bench | 76.9% | — |
| ForecastBench | — | 57.5 |

## Math

- Gemini 3.8 Flash: 65.3 (#28)
- Llama 4 Scout: 19.6 (#286)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.9% | 7.8% |
| LMArena Math | 1528 | 1287 |
| FrontierMath (Tiers 1-3) | 68.4% | — |
| FrontierMath Tier 4 | 22% | — |
| ProofBench | 48% | — |
| Omni-MATH | — | 37.3% |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |

## Knowledge

- Gemini 3.8 Flash: 74.8 (#2)
- Llama 4 Scout: 31.9 (#217)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | 95.4% | 51.8% |
| LMArena Expert | 1524 | 1235 |
| Humanity's Last Exam | 44.5% | — |
| SimpleQA Verified | 69.7% | — |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |

## Multimodal

- Gemini 3.8 Flash: 40.7 (#45)
- Llama 4 Scout: 32.2 (#102)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Vision | 1314 | 1118 |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 31.7% | — |
| SpatialViz-Bench | — | 34.2% |

## Multilingual

- Gemini 3.8 Flash: 58.0 (#5)
- Llama 4 Scout: 41.0 (#212)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1491 | 1252 |
| LMArena Chinese | 1554 | 1255 |
| LMArena French | 1498 | 1282 |
| LMArena German | 1493 | 1272 |
| LMArena Japanese | 1502 | 1206 |
| LMArena Korean | 1459 | 1207 |
| LMArena Russian | 1515 | 1263 |
| LMArena Spanish | 1485 | 1278 |

## Instruction Following

- Gemini 3.8 Flash: 78.0 (#13)
- Llama 4 Scout: 65.8 (#217)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1490 | 1248 |
| IFEval | — | 81.8% |

## Long Context

- Gemini 3.8 Flash: 46.3 (#24)
- Llama 4 Scout: 27.5 (#294)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1508 | 1265 |
| Fiction.LiveBench | — | 36% |

## Writing & Preference

- Gemini 3.8 Flash: 72.2 (#15)
- Llama 4 Scout: 37.0 (#261)

| Benchmark | Gemini 3.8 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1499 | 1279 |
| LMArena Creative Writing | 1492 | 1249 |
| EQ-Bench Creative Writing | 1748 | 783 |
| LMArena Multi-Turn | 1501 | 1280 |
| WildBench | — | 78% |

## FAQ

### Is Gemini 3.8 Flash better than Llama 4 Scout?

Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 27.7 on the Noometry Index. Llama 4 Scout costs 10.0× less per token, which makes it the better buy when Gemini 3.8 Flash's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.8 Flash or Llama 4 Scout?

Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Gemini 3.8 Flash lists at $0.75 and $3.75.

### Is Gemini 3.8 Flash or Llama 4 Scout better for coding?

Gemini 3.8 Flash scores higher on coding benchmarks: 59.2 versus 20.2 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.8 Flash does, with 1.05M tokens against 128K.

### How many benchmarks do Gemini 3.8 Flash and Llama 4 Scout share?

28 benchmarks have published results for both models. Gemini 3.8 Flash has 50 scored results on Noometry and Llama 4 Scout has 43.