Llama 3.1 8B Instruct
meta/llama-3.1-8b-instruct- Meta
- Family · Llama 3
- Open weights
- Text → Text
- Tools · JSON
Not on OSMEXO yet
Spec & list price
Context128K
Max output118K
Input / 1M$0.05
Output / 1M$0.081.6× input
Usage
Tokens / day4.5B▼ 17% 7d
Usage rank#117
Requests / day2.8M
Tool calls / req0.00
Per request · 30 days
Avg input6200.0× median
Avg output990.1× median
Cache hit21%0.3× median
Tool-call failures15%7.7× median
Consumption
Peak 10.8B 29 SepLow 3.0B 1 NovRank today #117
News & trends
1 mentions this week ▼ 80%Llama 3 family · videos, posts, articles · 30 days
News · latest from Meta
- Meta Networking at the 2026 OCP Global Summit: Open Innovation for Scale-Up, Scale-Out, and Scale-Across AI NetworksMeta Engineering · 26 Oct
- Scale Agentic Coding Workflows with Meta’s Muse Spark Open on NVIDIA GB300 NVL72NVIDIA · 15 Oct
- Meta Muse Spark Open is live on Together AITogether AI · 15 Oct
- Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta15 Oct
Benchmarks
Benchmark data: Artificial AnalysisOutput speed#60/334106 tok/s1.6× faster than median
Fastest provider413 tok/sbest of 5 providers
First token#420.44 s2.4× quicker than median
Family progress
Intelligence Index
- Family releases7.7
Technical details
- Tokenizer
- Llama3
- Knowledge cutoff
- 2023-12-31
- License
- llama3.1
- Parameters
- 8B
- Moderation
- none
- Downloads · likes
- 4.5M · 8.8K
Request parameters 17
- tools
- tool_choice
- response_format
- structured_outputs
- temperature
- top_p
- top_k
- min_p
- max_tokens
- stop
+7 more
- seed
- frequency_penalty
- logit_bias
- logprobs
- presence_penalty
- repetition_penalty
- top_logprobs
When to use
Best for
- Cheap high-volume chat and classification
- Self-hosted deployments (open weights)
- Fine-tuning a small open model
- Simple tool calling and structured output
Think twice for
- Image input (text only)
- Hardest reasoning and coding tasks
- Very long documents (limited context)
Research papers
- Adaptive Multi-Token Prediction: How far should we go?20 Oct
- Reinforcement Learning In Partially Verifiable Environments for Colon Cancer Treatment Planning12 Oct
- Principled Under Pressure: Post-Training Decides Whether LLMs Act on Their Own Moral Judgment6 Oct
- Silent Dissent: LLM Agents That Yield to the Majority Still Represent Their Original Premise2 Oct
- Uncertainty-Normalized Margins for Direct Preference Optimization29 Sep
- Illusory Truth or Mere Exposure? Model-Dependent Repetition Effects in LLM-Based Social Media Simulations28 Sep
- From Noise to Signal: Improving Security Log Anomaly Detection Using LLMs with Endpoint-Specific Logs20 Aug
- Simulating Tenant Responses to Energy Policy Interventions with Transaction-Cost-Aware LLM Agent27 Jul
Same family
Llama 3- G
- 5.5
- 4.8
- 7.3
- 6.6
- 6.9
- 5.4
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