# Gemini 2.5 Flash vs Llama-3.3-70B-Instruct

> Gemini 2.5 Flash is the stronger model overall, scoring 39.0 to 30.3 on the Noometry Index. Llama-3.3-70B-Instruct costs 5.5× less per token, which makes it the better buy when Gemini 2.5 Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-2-5-flash-vs-llama-3-3-70b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 9 categories and Llama-3.3-70B-Instruct in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemini 2.5 Flash leads 38.1 to 14.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 73.1% for Gemini 2.5 Flash and 5.1% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.30 / $2.50 for Gemini 2.5 Flash.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 128K.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 39.0 | 30.3 |
| Rank | 162 | 283 |
| Context | 1.05M | 128K |
| Input $/M | $0.30 | $0.10 |
| Output $/M | $2.50 | $0.32 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.5 Flash: 35.5 (#210)
- Llama-3.3-70B-Instruct: 30.6 (#284)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| WeirdML | 41.9% | 14.4% |
| LMArena Coding | 1424 | 1268 |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| SciCode | — | 26% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |
| ALE-Bench | 661.88 | — |

## Agentic & Tool Use

- Gemini 2.5 Flash: 30.6 (#67)
- Llama-3.3-70B-Instruct: 25.6 (#100)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 56.2% | 31.9% |
| BALROG | 33.5% | 23% |
| Terminal-Bench | 17.1% | — |
| TheAgentCompany | 41.1% | — |
| Vending-Bench 2 | 548.84 | — |

## Reasoning

- Gemini 2.5 Flash: 18.2 (#271)
- Llama-3.3-70B-Instruct: 13.7 (#325)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| SimpleBench | 41.2% | 19.9% |
| CritPt | 1.1% | 0% |
| LMArena Hard Prompts | 1422 | 1257 |
| DTBench | 76.5% | 59.5% |
| LMCA | 27.5% | 17.5% |
| Epoch Capabilities Index | 143.04 | 127.32 |
| ForecastBench | 60.6 | 58.6 |
| ARC-AGI-2 | 2.5% | — |
| Kagi LLM Benchmark | 56.8% | — |
| ARC-AGI-1 | 33.3% | — |
| EnigmaEval | 2.7% | — |
| LiveBench Reasoning | — | 50.8% |
| LiveBench Data Analysis | — | 49.5% |
| LiveBench | — | 50.2% |

## Math

- Gemini 2.5 Flash: 38.1 (#87)
- Llama-3.3-70B-Instruct: 14.3 (#292)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.1% | 5.1% |
| LMArena Math | 1415 | 1268 |
| Omni-MATH | 38.5% | — |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Gemini 2.5 Flash: 36.1 (#162)
- Llama-3.3-70B-Instruct: 30.5 (#220)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| Confabulations | 16.8% | 22.8% |
| Vectara Hallucination Rate | 7.8% | 4.1% |
| LMArena Expert | 1426 | 1225 |
| GPQA Diamond | — | 47.4% |
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| GPQA (HELM) | 39% | — |
| MMLU | — | 86.3% |

## Multimodal

- Gemini 2.5 Flash: 41.2 (#31)
- Llama-3.3-70B-Instruct: —

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Vision | 1254 | — |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |

## Multilingual

- Gemini 2.5 Flash: 52.5 (#83)
- Llama-3.3-70B-Instruct: 40.1 (#215)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1410 | 1236 |
| LMArena Chinese | 1450 | 1217 |
| LMArena French | 1433 | 1280 |
| LMArena German | 1419 | 1251 |
| LMArena Japanese | 1403 | 1149 |
| LMArena Korean | 1385 | 1142 |
| LMArena Russian | 1415 | 1252 |
| LMArena Spanish | 1421 | 1269 |

## Instruction Following

- Gemini 2.5 Flash: 75.9 (#50)
- Llama-3.3-70B-Instruct: 71.3 (#152)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1405 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
| IFEval | 89.8% | — |

## Long Context

- Gemini 2.5 Flash: 47.5 (#16)
- Llama-3.3-70B-Instruct: 26.4 (#290)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| Fiction.LiveBench | 77.8% | 33.3% |
| LMArena Longer Query | 1419 | 1256 |

## Writing & Preference

- Gemini 2.5 Flash: 54.0 (#153)
- Llama-3.3-70B-Instruct: 47.8 (#203)

| Benchmark | Gemini 2.5 Flash | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1417 | 1274 |
| LMArena Creative Writing | 1400 | 1250 |
| LMArena Multi-Turn | 1408 | 1279 |
| Short-Story Creative Writing | 76.5% | — |
| EQ-Bench Creative Writing | 1137 | — |
| WildBench | 81.7% | — |
| LiveBench Language | — | 39.2% |

## FAQ

### Is Gemini 2.5 Flash better than Llama-3.3-70B-Instruct?

Gemini 2.5 Flash is the stronger model overall, scoring 39.0 to 30.3 on the Noometry Index. Llama-3.3-70B-Instruct costs 5.5× less per token, which makes it the better buy when Gemini 2.5 Flash's lead doesn't matter for your workload.

### Which is cheaper, Gemini 2.5 Flash or Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Gemini 2.5 Flash lists at $0.30 and $2.50.

### Is Gemini 2.5 Flash or Llama-3.3-70B-Instruct better for coding?

Gemini 2.5 Flash scores higher on coding benchmarks: 35.5 versus 30.6 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Flash does, with 1.05M tokens against 128K.

### How many benchmarks do Gemini 2.5 Flash and Llama-3.3-70B-Instruct share?

30 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Llama-3.3-70B-Instruct has 43.