Meta, open weights
Llama 3-8B
Llama 3-8B by Meta ranks 344th of 354 ranked models on the Noometry Index as of October 2026, with a score of 25.5. Its strongest category is long context, where it ranks 251st.
Last verified
Specifications
- Noometry rank
- #344 of 354
- Index score
- 25.5
- Evidence
- Confirmed 34 results
- Provider
Meta
- Released
- April 18, 2024
- 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.
- Coding 31.0
- Reasoning 14.3
- Math 8.8
- Knowledge 7.8
- Multilingual 30.8
- Instruction Following 58.4
- Long Context 34.2
- Writing & Preference 37.5
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 31.0 | #289 | 3 |
| Reasoning | 14.3 | #326 | 3 |
| Math | 8.8 | #323 | 3 |
| Knowledge | 7.8 | #308 | 2 |
| Multilingual | 30.8 | #261 | 1 |
| Instruction Following | 58.4 | #260 | 1 |
| Long Context | 34.2 | #251 | 1 |
| Writing & Preference | 37.5 | #256 | 3 |
Strengths and weaknesses
Categories where Llama 3-8B places highest and lowest among the models ranked in each, with its score against that category's median.
Strongest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Writing & Preference | 37.5 | −16.3 | #256 of 312, top 83% |
| Long Context | 34.2 | −6.8 | #251 of 296, top 85% |
| Coding | 31.0 | −7.7 | #289 of 340, top 85% |
Closest competitors
The models ranked just above and below Llama 3-8B. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| Claude 3 Haiku | #340 | 25.9 | — | 41 | Compare |
| Gemma 2 9B | #341 | 25.9 | — | — | Compare |
| Dolly 2.0-12b | #342 | 25.5 | — | — | Compare |
| GPT-4o mini | #343 | 25.5 | $0.26 | 120 | Compare |
| Claude 2.1 | #345 | 25.2 | — | — | Compare |
| Claude 2 | #346 | 25.0 | — | — | Compare |
| DeepSeek LLM 67B | #347 | 24.9 | — | — | Compare |
| Llama 13b | #348 | 24.4 | — | — | Compare |
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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
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| BigCodeBench Instruct | 31.9% | #54 of 64, top 85% | BigCodeBench | 2024-04-18 | |
| LMArena Coding | 1152 | #257 of 294, top 88% | LMArena | 2026-10-08 | |
| BigCodeBench Complete | 28.8% | BigCodeBench | 2024-04-18 | ||
| BigCodeBench Complete | 36.9% | #58 of 66, top 88% | BigCodeBench | 2024-04-18 | |
| HumanEval+ | 56.7% | #32 of 45, top 72% | EvalPlus | ||
| HumanEval+ | 29.3% | EvalPlus | |||
| MBPP+ | 51.6% | EvalPlus | |||
| MBPP+ | 54.8% | #30 of 38, top 79% | EvalPlus |
Reasoning
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Chess Puzzles | 0% | #122 of 129, top 95% | Epoch AI | 2026-08-28 | |
| LMArena Hard Prompts | 1133 | #258 of 297, top 87% | LMArena | 2026-10-08 | |
| DTBench | 43.9% | #148 of 151, top 99% | Epoch AI | ||
| Adversarial NLI | 57.3% | #3 of 9, top 34% | Epoch AI | ||
| Epoch Capabilities Index | 116.45 | #183 of 213, top 86% | Epoch AI | 2024-04-18 | |
| ForecastBench | 58.6 | #46 of 72, top 64% | Epoch AI | ||
| ForecastBench | 52.9 | Epoch AI | |||
| WinoGrande | 75.7% | #22 of 43, top 52% | Epoch AI | ||
| WinoGrande | 65% | Epoch AI |
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | #162 of 173, top 94% | Epoch AI | 2026-08-30 | |
| LMArena Math | 1151 | #251 of 285, top 89% | LMArena | 2026-10-08 | |
| MATH Level 5 | 6.1% | #76 of 79, top 97% | Epoch AI | 2025-01-27 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| GPQA Diamond | 26.1% | #179 of 186, top 97% | Epoch AI | 2025-01-27 | |
| LMArena Expert | 1113 | #247 of 273, top 91% | LMArena | 2026-10-08 | |
| ARC (AI2) Challenge | 82.8% | #12 of 39, top 31% | Epoch AI | ||
| MMLU | 68.8% | #48 of 81, top 60% | Epoch AI | ||
| OpenBookQA | 82.6% | #6 of 19, top 32% | Epoch AI | ||
| TriviaQA | 67.7% | #20 of 25, top 80% | Epoch AI |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1098 | #261 of 297, top 88% | LMArena | 2026-10-08 | |
| LMArena Chinese | 1076 | #259 of 285, top 91% | LMArena | 2026-10-08 | |
| LMArena French | 1159 | #204 of 223, top 92% | LMArena | 2026-10-08 | |
| LMArena German | 1104 | #210 of 231, top 91% | LMArena | 2026-10-08 | |
| LMArena Japanese | 967 | #203 of 211, top 97% | LMArena | 2026-10-08 | |
| LMArena Korean | 1004 | #201 of 213, top 95% | LMArena | 2026-10-08 | |
| LMArena Russian | 1109 | #256 of 283, top 91% | LMArena | 2026-10-08 | |
| LMArena Spanish | 1173 | #199 of 226, top 89% | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Instruction Following | 1127 | #258 of 298, top 87% | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Longer Query | 1128 | #260 of 291, top 90% | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1166 | #254 of 297, top 86% | LMArena | 2026-10-08 | |
| LMArena Creative Writing | 1150 | #250 of 295, top 85% | LMArena | 2026-10-08 | |
| LMArena Multi-Turn | 1152 | #253 of 295, top 86% | LMArena | 2026-10-08 |
Compare Llama 3-8B
- Llama 3-8B vs Llama 2-13B
- Llama 3-8B vs GPT-4o mini
- Llama 3-8B vs Claude 2.1
- Llama 3-8B vs Dolly 2.0-12b
- Llama 3-8B vs Claude 2
- Llama 3-8B vs Gemma 2 9B
- Llama 3-8B vs DeepSeek LLM 67B
- Llama 3-8B vs GPT-6 Astra
- Llama 3-8B vs Claude Fable 5.1
- Llama 3-8B vs Gemini 3.8 Flash
- Llama 3-8B vs Kimi K3
- Llama 3-8B vs Grok 4.6
- Llama 3-8B vs Qwen3.8 Max
- Llama 3-8B vs GLM-5.3
Other Meta models
- Muse Spark 1.354.8
- Muse Spark50.6
- Muse Spark 1.250.3
- Muse Spark 1.149.9
- Muse Glimmer41.7
- Codellama 70b Instruct33.7
- Llama 4 Maverick30.9
- Codellama 34b Instruct30.8
Frequently asked questions
How good is Llama 3-8B?
Llama 3-8B by Meta ranks 344th of 354 ranked models on the Noometry Index as of October 2026, with a score of 25.5. Its strongest category is long context, where it ranks 251st.
Is Llama 3-8B open source?
Yes. Llama 3-8B's weights are downloadable; check the license for commercial terms.
What are Llama 3-8B's strengths and weaknesses?
Relative to other ranked models, Llama 3-8B places best in writing & preference, long context, coding and lowest in math, knowledge, reasoning.
What is Llama 3-8B best at?
Its best category is long context, where it ranks 251st on Noometry.