Meta, open weights

# Llama 2-70B

> Llama 2-70B by Meta, released July 2023. Ranked #349 of 354 with a Noometry Index of 24.4. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/llama-2-70b
- Last updated: 2026-10-10
- Title: Llama 2-70B Benchmarks, Price & Rank (October 2026)

Llama 2-70B by Meta ranks 349th of 354 ranked models on the Noometry Index as of October 2026, with a score of 24.4. Its strongest category is long context, where it ranks 270th.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #349 of 354
- **Index score:** 24.4
- **Evidence:** Confirmed 35 results
- **Provider:** [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta)
- **Released:** July 18, 2023
- **Weights:** Open weights
- **Reasoning:** Unknown
- **Context window:** —
- **Max output:** —
- **Input price:** Not listed
- **Output price:** Not listed
- **Blended price:** Not listed
- **Output speed:** Not measured
- **Value:** Not ranked
- **Knowledge cutoff:** Unknown

## Category scores

Each category score combines every public result we have in that category.

Llama 2-70B category scores

1.  Coding 31.4
2.  Reasoning 14.4
3.  Math 8.1
4.  Knowledge 7.4
5.  Multilingual 27.7
6.  Instruction Following 54.9
7.  Long Context 32.3
8.  Writing & Preference 32.3
9.  0204060

Llama 2-70B category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 31.4 | #286 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 14.4 | #325 | 2 |
| [Math](https://noometry.com/best/math) | 8.1 | #326 | 3 |
| [Knowledge](https://noometry.com/best/knowledge) | 7.4 | #310 | 2 |
| [Multilingual](https://noometry.com/best/multilingual) | 27.7 | #274 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 54.9 | #278 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 32.3 | #270 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 32.3 | #279 | 3 |

## Strengths and weaknesses

Categories where Llama 2-70B places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Llama 2-70B: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 31.4 | −7.3 | #286 of 340, top 85% |
| [Writing & Preference](https://noometry.com/best/writing) | 32.3 | −21.5 | #279 of 312, top 90% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 54.9 | −16.4 | #278 of 305, top 92% |

### Weakest categories

Llama 2-70B: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Math](https://noometry.com/best/math) | 8.1 | −28.5 | #326 of 327, top 100% |
| [Knowledge](https://noometry.com/best/knowledge) | 7.4 | −29.9 | #310 of 314, top 99% |
| [Reasoning](https://noometry.com/best/reasoning) | 14.4 | −9.2 | #325 of 350, top 93% |

## Closest competitors

The models ranked just above and below Llama 2-70B. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Llama 2-70B
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Claude 2.1](https://noometry.com/models/claude-2-1) | #345 | 25.2 | — | — | [Compare](https://noometry.com/compare/claude-2-1-vs-llama-2-70b) |
| [Claude 2](https://noometry.com/models/claude-2) | #346 | 25.0 | — | — | [Compare](https://noometry.com/compare/claude-2-vs-llama-2-70b) |
| [DeepSeek LLM 67B](https://noometry.com/models/deepseek-llm-67b) | #347 | 24.9 | — | — | [Compare](https://noometry.com/compare/deepseek-llm-67b-vs-llama-2-70b) |
| [Llama 13b](https://noometry.com/models/llama-13b) | #348 | 24.4 | — | — | [Compare](https://noometry.com/compare/llama-13b-vs-llama-2-70b) |
| [GPT-3.5-turbo](https://noometry.com/models/gpt-3-5-turbo) | #350 | 23.2 | $0.75 | — | [Compare](https://noometry.com/compare/gpt-3-5-turbo-vs-llama-2-70b) |
| [Mistral 7B](https://noometry.com/models/mistral-7b) | #351 | 23.0 | $0.25 | — | [Compare](https://noometry.com/compare/llama-2-70b-vs-mistral-7b) |
| [Llama 3.1-8B](https://noometry.com/models/llama-3-1-8b) | #352 | 23.0 | $0.0575 | — | [Compare](https://noometry.com/compare/llama-2-70b-vs-llama-3-1-8b) |
| [Gemma 3 1B](https://noometry.com/models/gemma-3-1b) | #353 | 21.1 | — | — | [Compare](https://noometry.com/compare/gemma-3-1b-vs-llama-2-70b) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

Llama 2-70B Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1079 | #278 of 294, top 95% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Reasoning

Llama 2-70B Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1073 | #274 of 297, top 93% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 41.6% | #151 of 151, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [BIG-Bench Hard](https://noometry.com/benchmarks/bbh) | 58.5% |  |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [BIG-Bench Hard](https://noometry.com/benchmarks/bbh) | 64.9% | #11 of 27, top 41% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CommonsenseQA 2.0](https://noometry.com/benchmarks/csqa2) | 50% | #2 of 2 |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 113.79 | #185 of 213, top 87% |  | [Epoch AI](https://epoch.ai/eci) | 2023-07-18 |
| [ForecastBench](https://noometry.com/benchmarks/forecastbench) | 51.4 | #71 of 72, top 99% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [HellaSwag](https://noometry.com/benchmarks/hellaswag) | 85.3% | #8 of 29, top 28% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LAMBADA](https://noometry.com/benchmarks/lambada) | 78.9% | #2 of 9, top 23% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [PIQA](https://noometry.com/benchmarks/piqa) | 82.8% | #13 of 27, top 49% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WinoGrande](https://noometry.com/benchmarks/winogrande) | 80.2% | #15 of 43, top 35% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

Llama 2-70B Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 0% | #173 of 173, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-02-25 |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1091 | #267 of 285, top 94% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [MATH Level 5](https://noometry.com/benchmarks/math-level-5) | 3.3% | #79 of 79, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-01-27 |
| [GSM8K](https://noometry.com/benchmarks/gsm8k) | 69.6% | #15 of 38, top 40% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GSM8K](https://noometry.com/benchmarks/gsm8k) | 58.7% |  |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Knowledge

Llama 2-70B Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 26.3% | #178 of 186, top 96% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-01-27 |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1039 | #265 of 273, top 98% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ARC (AI2) Challenge](https://noometry.com/benchmarks/arc-challenge) | 78.3% | #15 of 39, top 39% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [BoolQ](https://noometry.com/benchmarks/boolq) | 88.6% | #3 of 23, top 14% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [MMLU](https://noometry.com/benchmarks/mmlu) | 69.9% | #46 of 81, top 57% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [MMLU](https://noometry.com/benchmarks/mmlu) | 59.9% |  |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [OpenBookQA](https://noometry.com/benchmarks/openbookqa) | 60.2% | #11 of 19, top 58% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [TriviaQA](https://noometry.com/benchmarks/triviaqa) | 87.6% | Best of 25 |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Multilingual

Llama 2-70B Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1045 | #274 of 297, top 93% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 995 | #279 of 285, top 98% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1090 | #215 of 223, top 97% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1041 | #223 of 231, top 97% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 927 | #208 of 211, top 99% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 964 | #205 of 213, top 97% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1083 | #261 of 283, top 93% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1143 | #207 of 226, top 92% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Llama 2-70B Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1071 | #274 of 298, top 92% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Llama 2-70B Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1062 | #275 of 291, top 95% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Llama 2-70B Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1115 | #269 of 297, top 91% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1075 | #273 of 295, top 93% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1088 | #268 of 295, top 91% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## Compare Llama 2-70B

-   [Llama 2-70B vs Llama 13b](https://noometry.com/compare/llama-13b-vs-llama-2-70b)
-   [Llama 2-70B vs GPT-3.5-turbo](https://noometry.com/compare/gpt-3-5-turbo-vs-llama-2-70b)
-   [Llama 2-70B vs DeepSeek LLM 67B](https://noometry.com/compare/deepseek-llm-67b-vs-llama-2-70b)
-   [Llama 2-70B vs Mistral 7B](https://noometry.com/compare/llama-2-70b-vs-mistral-7b)
-   [Llama 2-70B vs Claude 2](https://noometry.com/compare/claude-2-vs-llama-2-70b)
-   [Llama 2-70B vs Llama 3.1-8B](https://noometry.com/compare/llama-2-70b-vs-llama-3-1-8b)
-   [Llama 2-70B vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-llama-2-70b)
-   [Llama 2-70B vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-llama-2-70b)
-   [Llama 2-70B vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-llama-2-70b)
-   [Llama 2-70B vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-llama-2-70b)
-   [Llama 2-70B vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-llama-2-70b)
-   [Llama 2-70B vs Qwen3.8 Max](https://noometry.com/compare/llama-2-70b-vs-qwen3-8-max)
-   [Llama 2-70B vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-llama-2-70b)
-   [Llama 2-70B vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-llama-2-70b)

## Other Meta models

-   [Muse Spark 1.3](https://noometry.com/models/muse-spark-1-3)54.8
-   [Muse Spark](https://noometry.com/models/muse-spark)50.6
-   [Muse Spark 1.2](https://noometry.com/models/muse-spark-1-2)50.3
-   [Muse Spark 1.1](https://noometry.com/models/muse-spark-1-1)49.9
-   [Muse Glimmer](https://noometry.com/models/muse-glimmer)41.7
-   [Codellama 70b Instruct](https://noometry.com/models/codellama-70b-instruct)33.7
-   [Llama 4 Maverick](https://noometry.com/models/llama-4-maverick)30.9
-   [Codellama 34b Instruct](https://noometry.com/models/codellama-34b-instruct)30.8

## Frequently asked questions

### How good is Llama 2-70B?

Llama 2-70B by Meta ranks 349th of 354 ranked models on the Noometry Index as of October 2026, with a score of 24.4. Its strongest category is long context, where it ranks 270th.

### Is Llama 2-70B open source?

Yes. Llama 2-70B's weights are downloadable; check the license for commercial terms.

### What are Llama 2-70B's strengths and weaknesses?

Relative to other ranked models, Llama 2-70B places best in coding, writing & preference, instruction following and lowest in math, knowledge, reasoning.

### What is Llama 2-70B best at?

Its best category is long context, where it ranks 270th on Noometry.

### Cite this page

Noometry. (2026). Llama 2-70B benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/llama-2-70b

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/llama-2-70b.md).