Meta, open weights

# Llama 2-7B

> Llama 2-7B by Meta, released July 2023. Ranked #317 of 354 with a Noometry Index of 29.1. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/llama-2-7b
- Last updated: 2026-10-10
- Title: Llama 2-7B Benchmarks, Price & Rank (October 2026)

Llama 2-7B by Meta ranks 317th of 354 ranked models on the Noometry Index as of October 2026, with a score of 29.1. Its strongest category is math, where it ranks 233rd.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #317 of 354
- **Index score:** 29.1
- **Evidence:** Confirmed 29 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 2-7B category scores

1.  Coding 29.2
2.  Reasoning 15.7
3.  Math 30.7
4.  Knowledge 28.2
5.  Multilingual 23.8
6.  Instruction Following 50.8
7.  Long Context 30.4
8.  Writing & Preference 28.0
9.  0204060

Llama 2-7B category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 29.2 | #307 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 15.7 | #312 | 2 |
| [Math](https://noometry.com/best/math) | 30.7 | #233 | 1 |
| [Knowledge](https://noometry.com/best/knowledge) | 28.2 | #248 | 1 |
| [Multilingual](https://noometry.com/best/multilingual) | 23.8 | #293 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 50.8 | #298 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 30.4 | #287 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 28.0 | #298 | 3 |

## Strengths and weaknesses

Categories where Llama 2-7B places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Llama 2-7B: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Math](https://noometry.com/best/math) | 30.7 | −5.9 | #233 of 327, top 72% |
| [Knowledge](https://noometry.com/best/knowledge) | 28.2 | −9.1 | #248 of 314, top 79% |
| [Reasoning](https://noometry.com/best/reasoning) | 15.7 | −7.9 | #312 of 350, top 90% |

### Weakest categories

Llama 2-7B: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Multilingual](https://noometry.com/best/multilingual) | 23.8 | −23.7 | #293 of 297, top 99% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 50.8 | −20.5 | #298 of 305, top 98% |
| [Long Context](https://noometry.com/best/long-context) | 30.4 | −10.5 | #287 of 296, top 97% |

## Closest competitors

The models ranked just above and below Llama 2-7B. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Llama 2-7B
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Gemma 1.1 2b IT](https://noometry.com/models/gemma-1-1-2b-it) | #313 | 29.3 | — | — | [Compare](https://noometry.com/compare/gemma-1-1-2b-it-vs-llama-2-7b) |
| [Phi 3 Small 8k Instruct](https://noometry.com/models/phi-3-small-8k-instruct) | #314 | 29.3 | — | — | [Compare](https://noometry.com/compare/llama-2-7b-vs-phi-3-small-8k-instruct) |
| [Claude 3.5 Haiku](https://noometry.com/models/claude-3-5-haiku) | #315 | 29.2 | — | — | [Compare](https://noometry.com/compare/claude-3-5-haiku-vs-llama-2-7b) |
| [GPT-4](https://noometry.com/models/gpt-4) | #316 | 29.1 | $37.50 | — | [Compare](https://noometry.com/compare/gpt-4-vs-llama-2-7b) |
| [Granite 4.0 Micro](https://noometry.com/models/granite-4-0-micro) | #318 | 29.0 | $0.0408 | — | [Compare](https://noometry.com/compare/granite-4-0-micro-vs-llama-2-7b) |
| [Claude 3 Sonnet](https://noometry.com/models/claude-3-sonnet) | #319 | 29.0 | — | — | [Compare](https://noometry.com/compare/claude-3-sonnet-vs-llama-2-7b) |
| [Qwen2.5 7B Instruct](https://noometry.com/models/qwen2-5-7b-instruct) | #320 | 29.0 | $0.31 | — | [Compare](https://noometry.com/compare/llama-2-7b-vs-qwen2-5-7b-instruct) |
| [Llama 3.2 3B](https://noometry.com/models/llama-3-2-3b) | #321 | 28.9 | $0.12 | — | [Compare](https://noometry.com/compare/llama-2-7b-vs-llama-3-2-3b) |

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 2-7B Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1002 | #290 of 294, top 99% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Reasoning

Llama 2-7B Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 0% | #119 of 129, top 93% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1009 | #289 of 297, top 98% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [BIG-Bench Hard](https://noometry.com/benchmarks/bbh) | 39.2% | #22 of 27, top 82% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 99.06 | #204 of 213, top 96% |  | [Epoch AI](https://epoch.ai/eci) | 2023-07-18 |
| [HellaSwag](https://noometry.com/benchmarks/hellaswag) | 77.2% | #20 of 29, top 69% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LAMBADA](https://noometry.com/benchmarks/lambada) | 73.3% | #7 of 9, top 78% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [PIQA](https://noometry.com/benchmarks/piqa) | 78.8% | #24 of 27, top 89% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WinoGrande](https://noometry.com/benchmarks/winogrande) | 69.2% | #32 of 43, top 75% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

Llama 2-7B Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1042 | #279 of 285, top 98% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [GSM8K](https://noometry.com/benchmarks/gsm8k) | 16.7% | #36 of 38, top 95% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Knowledge

Llama 2-7B Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1036 | #266 of 273, top 98% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ARC (AI2) Challenge](https://noometry.com/benchmarks/arc-challenge) | 45.9% | #31 of 39, top 80% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [BoolQ](https://noometry.com/benchmarks/boolq) | 77.9% | #18 of 23, top 79% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [MMLU](https://noometry.com/benchmarks/mmlu) | 45.8% | #71 of 81, top 88% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [OpenBookQA](https://noometry.com/benchmarks/openbookqa) | 58.6% | #12 of 19, top 64% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [TriviaQA](https://noometry.com/benchmarks/triviaqa) | 73.7% | #17 of 25, top 68% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Multimodal

Llama 2-7B Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ScienceQA](https://noometry.com/benchmarks/scienceqa) | 43.1% | #6 of 6, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Multilingual

Llama 2-7B Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 973 | #293 of 297, top 99% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 973 | #282 of 285, top 99% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 970 | #223 of 223, top 100% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 978 | #229 of 231, top 100% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 995 | #276 of 283, top 98% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1007 | #226 of 226, top 100% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Llama 2-7B Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1006 | #292 of 298, top 98% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Llama 2-7B Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 999 | #287 of 291, top 99% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Llama 2-7B Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1053 | #288 of 297, top 97% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1033 | #283 of 295, top 96% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1029 | #282 of 295, top 96% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## Compare Llama 2-7B

-   [Llama 2-7B vs Llama 13b](https://noometry.com/compare/llama-13b-vs-llama-2-7b)
-   [Llama 2-7B vs GPT-4](https://noometry.com/compare/gpt-4-vs-llama-2-7b)
-   [Llama 2-7B vs Granite 4.0 Micro](https://noometry.com/compare/granite-4-0-micro-vs-llama-2-7b)
-   [Llama 2-7B vs Claude 3.5 Haiku](https://noometry.com/compare/claude-3-5-haiku-vs-llama-2-7b)
-   [Llama 2-7B vs Claude 3 Sonnet](https://noometry.com/compare/claude-3-sonnet-vs-llama-2-7b)
-   [Llama 2-7B vs Phi 3 Small 8k Instruct](https://noometry.com/compare/llama-2-7b-vs-phi-3-small-8k-instruct)
-   [Llama 2-7B vs Qwen2.5 7B Instruct](https://noometry.com/compare/llama-2-7b-vs-qwen2-5-7b-instruct)
-   [Llama 2-7B vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-llama-2-7b)
-   [Llama 2-7B vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-llama-2-7b)
-   [Llama 2-7B vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-llama-2-7b)
-   [Llama 2-7B vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-llama-2-7b)
-   [Llama 2-7B vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-llama-2-7b)
-   [Llama 2-7B vs Qwen3.8 Max](https://noometry.com/compare/llama-2-7b-vs-qwen3-8-max)
-   [Llama 2-7B vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-llama-2-7b)

## 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 2-7B?

Llama 2-7B by Meta ranks 317th of 354 ranked models on the Noometry Index as of October 2026, with a score of 29.1. Its strongest category is math, where it ranks 233rd.

### Is Llama 2-7B open source?

Yes. Llama 2-7B's weights are downloadable; check the license for commercial terms.

### What are Llama 2-7B's strengths and weaknesses?

Relative to other ranked models, Llama 2-7B places best in math, knowledge, reasoning and lowest in multilingual, instruction following, long context.

### What is Llama 2-7B best at?

Its best category is math, where it ranks 233rd on Noometry.

### Cite this page

Noometry. (2026). Llama 2-7B benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/llama-2-7b

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/llama-2-7b.md).