Meta: Llama 4 Scout
CONFIRMEDLlama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
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Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
| Benchmark | Wert | Beleg |
|---|---|---|
| MultilingualScore | 91.1 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| BenchmarkScore | 68.9 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| SteerabilityScore | 92.1 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| BenchmarkScore | 87.6 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| Tool UseScore | 77.3 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| Benchmark | Wert | Beleg |
|---|---|---|
| CodeScore | 88.4 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| BenchmarkScore | 86.0 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| ReasoningScore | 50.5 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| MathScore | 77.0 | Quelle ↗Model Card · abgerufen 2026-10-11 |
| joelniklaus/LEXam-hardlexam_hard | 26.78 | Quelle ↗Community · 2026-07-12Testdetailslighteval, LEXam paper prompts, one response per question, no tools; DeepSeek-R1-0528 judge; mean of the German and English means over the 518 questions, 0-100 |
| LEXam-Benchmark/LEXamopen_question | 41.27 | Quelle ↗Community · 2026-06-02 |
| thamilvendhan/signalbenchsrc | 0.4167 | Quelle ↗Community · 2026-07-08TestdetailsSRC overall; deterministic action-based grader, no LLM judge; seed 0, n=75 |
| thamilvendhan/signalbenchaccess_deny | 0.0833 | Quelle ↗Community · 2026-07-08Testdetailsfamily=access_deny; n=12 |
| thamilvendhan/signalbenchtime | 0.75 | Quelle ↗Community · 2026-07-08Testdetailsfamily=time; n=12 |
| openai/gsm8kgsm8k | 94.8445792267 | Quelle ↗Community · 2025-03-19 |
| Idavidrein/gpqadiamond | 51.5151515152 | Quelle ↗Community · 2026-04-16TestdetailsGPQA Diamond |
| TIGER-Lab/MMLU-Prommlu_pro | 65.92 | Quelle ↗Community · 2026-06-30 |
| thamilvendhan/signalbenchinjection | 0.5833 | Quelle ↗Community · 2026-07-08Testdetailsfamily=injection; n=12 |
| thamilvendhan/signalbenchbot_policy | 0.0833 | Quelle ↗Community · 2026-07-08Testdetailsfamily=bot_policy; n=12 |
| thamilvendhan/signalbenchmemory_label | 0.5833 | Quelle ↗Community · 2026-07-08Testdetailsfamily=memory_label; n=12 |
| LEXam-Benchmark/LEXammcq_4_choices | 28.19 | Quelle ↗Community · 2026-06-02 |
Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
| Benchmark | Wert | Beleg |
|---|---|---|
| thamilvendhan/signalbenchsrc | 0.6333 | Quelle ↗Community · 2026-07-08TestdetailsSRC overall; deterministic action-based grader, no LLM judge; seed 0, n=75 |
| thamilvendhan/signalbenchaccess_deny | 0.5 | Quelle ↗Community · 2026-07-08Testdetailsfamily=access_deny; n=12 |
| thamilvendhan/signalbenchbot_policy | 0.4167 | Quelle ↗Community · 2026-07-08Testdetailsfamily=bot_policy; n=12 |
| thamilvendhan/signalbenchtime | 0.8333 | Quelle ↗Community · 2026-07-08Testdetailsfamily=time; n=12 |
| openai/gsm8kgsm8k | 84.5 | Quelle ↗Community · 2026-03-23 |
| Benchmark | Wert | Beleg |
|---|---|---|
| thamilvendhan/signalbenchinjection | 0.75 | Quelle ↗Community · 2026-07-08Testdetailsfamily=injection; n=12 |
| Idavidrein/gpqadiamond | 30.4 | Quelle ↗Community · 2026-01-27 |
| LEXam-Benchmark/LEXammcq_4_choices | 24.04 | Quelle ↗Community · 2026-06-02 |
| LEXam-Benchmark/LEXamopen_question | 10 | Quelle ↗Community · 2026-06-02 |
| thamilvendhan/signalbenchmemory_label | 0.6667 | Quelle ↗Community · 2026-07-08Testdetailsfamily=memory_label; n=12 |
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...
| Benchmark | Wert | Beleg |
|---|---|---|
| TIGER-Lab/MMLU-Prommlu_pro | 62.84 | Quelle ↗Community · 2026-06-30 |
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