# Gemini 3 Flash Preview vs Llama 3.2 1B

> Gemini 3 Flash Preview is the stronger model overall, scoring 52.3 to 19.9 on the Noometry Index. Llama 3.2 1B costs 16× less per token, which makes it the better buy when Gemini 3 Flash Preview's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-flash-preview-vs-llama-3-2-1b
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. Gemini 3 Flash Preview scores higher in 9 categories and Llama 3.2 1B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 3 Flash Preview leads 58.8 to 7.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Gemini 3 Flash Preview and 0.6% for Llama 3.2 1B.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.50 / $3 for Gemini 3 Flash Preview.
- Gemini 3 Flash Preview accepts more context: 1.05M tokens versus 60K.
- Llama 3.2 1B has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 52.3 | 19.9 |
| Rank | 33 | 349 |
| Context | 1.05M | 60K |
| Input $/M | $0.50 | $0.027 |
| Output $/M | $3 | $0.20 |
| Weights | Proprietary | Open |

## Coding

- Gemini 3 Flash Preview: 51.5 (#35)
- Llama 3.2 1B: 20.6 (#333)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| LMArena Coding | 1460 | 1071 |
| SWE-bench Verified | 75.4% | — |
| SWE-bench Verified (bash only) | 75.8% | — |
| LMArena WebDev | 1439 | — |
| SWE-bench Multilingual | 72.7% | — |
| GSO | 9.8% | — |
| WeirdML | 61.6% | — |
| BigCodeBench Instruct | — | 8.2% |
| BigCodeBench Complete | — | 11.3% |
| ALE-Bench | 1,367 | — |

## Agentic & Tool Use

- Gemini 3 Flash Preview: 38.6 (#27)
- Llama 3.2 1B: 14.5 (#142)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| BALROG | 48.1% | 6.6% |
| Terminal-Bench | 64.3% | — |
| Berkeley Function Calling Leaderboard | — | 10.8% |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 27.3% | — |
| τ²-bench Retail | 76.8% | — |
| τ²-bench Telecom | 91.2% | — |
| DeepResearch Bench | 49.8% | — |
| GDP.pdf | 10% | — |
| LMArena Search | 1198 | — |
| Vending-Bench 2 | 3,635 | — |

## Reasoning

- Gemini 3 Flash Preview: 49.2 (#35)
- Llama 3.2 1B: 15.6 (#304)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| Chess Puzzles | 40% | 0% |
| LMArena Hard Prompts | 1465 | 1044 |
| Epoch Capabilities Index | 151.83 | 101.95 |
| ARC-AGI-2 | 33.6% | — |
| SimpleBench | 61.1% | — |
| NYT Connections (extended) | 83.1% | — |
| ARC-AGI-1 | 84.7% | — |
| Mystery Game Puzzles | 26% | — |
| DTBench | 89.1% | — |
| LMCA | 43.1% | — |
| ForecastBench | 58.5 | — |

## Math

- Gemini 3 Flash Preview: 51.4 (#42)
- Llama 3.2 1B: 9.7 (#308)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 0.6% |
| LMArena Math | 1472 | 1086 |
| FrontierMath (Tiers 1-3) | 51.2% | — |
| FrontierMath Tier 4 | 17.1% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| ProofBench | 15% | — |
| FrontierMath (Feb 2025 set) | 35.6% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Gemini 3 Flash Preview: 58.8 (#30)
- Llama 3.2 1B: 7.2 (#307)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| GPQA Diamond | 89.4% | 23.9% |
| LMArena Expert | 1461 | 1007 |
| SimpleQA Verified | 66.8% | — |
| Vectara Hallucination Rate | 13.5% | — |

## Multimodal

- Gemini 3 Flash Preview: 45.3 (#15)
- Llama 3.2 1B: —

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| LMArena Vision | 1285 | — |
| GeoBench | 88% | — |
| VPCT | 72.6% | — |
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1413 | — |

## Multilingual

- Gemini 3 Flash Preview: 55.9 (#26)
- Llama 3.2 1B: 23.9 (#287)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1458 | 973 |
| LMArena Chinese | 1510 | 958 |
| LMArena German | 1497 | 1014 |
| LMArena Russian | 1480 | 941 |
| LMArena French | 1478 | — |
| LMArena Japanese | 1488 | — |
| LMArena Korean | 1443 | — |
| LMArena Spanish | 1470 | — |

## Instruction Following

- Gemini 3 Flash Preview: 75.8 (#52)
- Llama 3.2 1B: 52.6 (#285)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1437 | 1031 |

## Long Context

- Gemini 3 Flash Preview: 44.4 (#63)
- Llama 3.2 1B: 31.9 (#269)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1452 | 1050 |

## Writing & Preference

- Gemini 3 Flash Preview: 65.6 (#44)
- Llama 3.2 1B: 21.4 (#305)

| Benchmark | Gemini 3 Flash Preview | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1466 | 1055 |
| LMArena Creative Writing | 1457 | 1033 |
| LMArena Multi-Turn | 1471 | 1030 |
| EQ-Bench Creative Writing | — | 200 |

## FAQ

### Is Gemini 3 Flash Preview better than Llama 3.2 1B?

Gemini 3 Flash Preview is the stronger model overall, scoring 52.3 to 19.9 on the Noometry Index. Llama 3.2 1B costs 16× less per token, which makes it the better buy when Gemini 3 Flash Preview's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3 Flash Preview or Llama 3.2 1B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Gemini 3 Flash Preview lists at $0.50 and $3.

### Is Gemini 3 Flash Preview or Llama 3.2 1B better for coding?

Gemini 3 Flash Preview scores higher on coding benchmarks: 51.5 versus 20.6 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3 Flash Preview does, with 1.05M tokens against 60K.

### How many benchmarks do Gemini 3 Flash Preview and Llama 3.2 1B share?

18 benchmarks have published results for both models. Gemini 3 Flash Preview has 59 scored results on Noometry and Llama 3.2 1B has 22.