# Gemini 3.6 Flash vs Llama 3.1-8B

> Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 23.0 on the Noometry Index. Llama 3.1-8B costs 26× less per token, which makes it the better buy when Gemini 3.6 Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-6-flash-vs-llama-3-1-8b
- Last updated: 2026-10-12
- Shared benchmarks: 27

## Summary

- They share 27 benchmarks with published results for both. Gemini 3.6 Flash scores higher in 9 categories and Llama 3.1-8B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 3.6 Flash leads 67.8 to 8.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.2% for Gemini 3.6 Flash and 1.7% for Llama 3.1-8B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.6 Flash.
- Gemini 3.6 Flash accepts more context: 1.05M tokens versus 128K.
- Llama 3.1-8B has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 54.1 | 23.0 |
| Rank | 33 | 352 |
| Context | 1.05M | 128K |
| Input $/M | $0.75 | $0.05 |
| Output $/M | $3.75 | $0.08 |
| Weights | Proprietary | Open |

## Coding

- Gemini 3.6 Flash: 50.0 (#48)
- Llama 3.1-8B: 20.2 (#340)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| SciCode | 52.7% | 13.2% |
| WeirdML | 56.1% | 1.7% |
| LMArena Coding | 1491 | 1195 |
| DeepSWE | 46.7% | — |
| FrontierCode | 34.4% | — |
| LMArena WebDev | 1538 | — |
| BigCodeBench Instruct | — | 32.8% |
| BigCodeBench Complete | — | 40.5% |
| ALE-Bench | 715.52 | — |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |

## Agentic & Tool Use

- Gemini 3.6 Flash: 32.3 (#65)
- Llama 3.1-8B: 22.5 (#131)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| APEX-Agents | 46.9% | — |
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |
| GDP.pdf | 14% | — |

## Reasoning

- Gemini 3.6 Flash: 58.8 (#22)
- Llama 3.1-8B: 14.9 (#321)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| CritPt | 10.6% | 0% |
| Chess Puzzles | 43% | 0% |
| LMArena Hard Prompts | 1485 | 1175 |
| DTBench | 95.5% | 50.9% |
| LMCA | 44.9% | 5.4% |
| Epoch Capabilities Index | 154.25 | 116.57 |
| ARC-AGI-2 | 60.4% | — |
| NYT Connections (extended) | 89% | — |
| ARC-AGI-1 | 91.2% | — |
| Mystery Game Puzzles | 30% | — |
| PIQA | — | 81.2% |

## Math

- Gemini 3.6 Flash: 57.3 (#40)
- Llama 3.1-8B: 10.2 (#317)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.2% | 1.7% |
| LMArena Math | 1505 | 1179 |
| FrontierMath (Tiers 1-3) | 58.9% | — |
| FrontierMath Tier 4 | 22% | — |
| MathArena Final-Answer Competitions | 70.8% | — |
| ProofBench | 36% | — |
| Omni-MATH | — | 13.7% |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |

## Knowledge

- Gemini 3.6 Flash: 67.8 (#8)
- Llama 3.1-8B: 8.0 (#307)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| GPQA Diamond | 94.1% | 27% |
| LMArena Expert | 1488 | 1144 |
| SimpleQA Verified | 66.2% | — |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |

## Multimodal

- Gemini 3.6 Flash: 38.5 (#64)
- Llama 3.1-8B: —

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| LMArena Vision | 1298 | — |
| Blueprint-Bench 2 | 31.2% | — |
| Furniture Assembly | 23.3% | — |
| LMArena Document | 1456 | — |

## Multilingual

- Gemini 3.6 Flash: 56.5 (#19)
- Llama 3.1-8B: 34.0 (#249)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | 1469 | 1148 |
| LMArena Chinese | 1531 | 1151 |
| LMArena French | 1504 | 1177 |
| LMArena German | 1478 | 1144 |
| LMArena Japanese | 1476 | 1061 |
| LMArena Korean | 1431 | 1053 |
| LMArena Russian | 1487 | 1158 |
| LMArena Spanish | 1475 | 1169 |

## Instruction Following

- Gemini 3.6 Flash: 77.0 (#33)
- Llama 3.1-8B: 58.9 (#258)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| LMArena Instruction Following | 1466 | 1159 |
| IFEval | — | 74.3% |

## Long Context

- Gemini 3.6 Flash: 45.1 (#50)
- Llama 3.1-8B: 35.8 (#238)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | 1474 | 1182 |

## Writing & Preference

- Gemini 3.6 Flash: 68.2 (#27)
- Llama 3.1-8B: 29.7 (#290)

| Benchmark | Gemini 3.6 Flash | Llama 3.1-8B |
|---|---|---|
| LMArena Text | 1479 | 1187 |
| LMArena Creative Writing | 1465 | 1154 |
| EQ-Bench Creative Writing | 1604 | 713 |
| LMArena Multi-Turn | 1481 | 1172 |
| WildBench | — | 68.7% |

## FAQ

### Is Gemini 3.6 Flash better than Llama 3.1-8B?

Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 23.0 on the Noometry Index. Llama 3.1-8B costs 26× less per token, which makes it the better buy when Gemini 3.6 Flash's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.6 Flash or Llama 3.1-8B?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Gemini 3.6 Flash lists at $0.75 and $3.75.

### Is Gemini 3.6 Flash or Llama 3.1-8B better for coding?

Gemini 3.6 Flash scores higher on coding benchmarks: 50.0 versus 20.2 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.6 Flash does, with 1.05M tokens against 128K.

### How many benchmarks do Gemini 3.6 Flash and Llama 3.1-8B share?

27 benchmarks have published results for both models. Gemini 3.6 Flash has 46 scored results on Noometry and Llama 3.1-8B has 43.