Llama 3.1 8B Instruct
Meta • LLM
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...
Specifications
Context Window
16K tokens
Input Price/1M
$0.10
Output Price/1M
$0.10
Parameters
—
Speed
223 tok/s
Latency (TTFT)
460ms
Max Output
16K tokens
Benchmarks
Llama 3.1 8B Instruct results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Agentic
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 1.0 | 100.0 | — |
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SciCode | 13.0 | 100.0 | — |
| LiveCodeBench | 12.0 | 100.0 | — |
| AA Coding Index | 4.9 | 100.0 | — |
Knowledge
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 48.0 | 100.0 | — |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 16.0 | 100.0 | — |
Math
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Math Index | 4.3 | 100.0 | — |
| AIME 2025 | 4.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| HF Average | 23.9 | 100.0 | HuggingFace Open LLM Leaderboard v2 |
| AA Intelligence Index | 11.8 | 100.0 | — |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| IFBench | 29.0 | 100.0 | — |
| GPQA Diamond | 26.0 | 100.0 | — |
| HLE | 5.0 | 100.0 | — |
Tool Use
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 16.0 | 100.0 | — |
Information
- Release date
- July 23, 2024
- Tool Calling
- ✅ Supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Llama 3.1 8B Instruct
What is Llama 3.1 8B Instruct?
Llama 3.1 8B Instruct is an AI model developed by Meta, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 16K tokens, it is suitable for processing short documents and direct prompts.
Pricing & Costs in 2026
Llama 3.1 8B Instruct is usage-based, priced at $0.1/1M input tokens and $0.1/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
Llama 3.1 8B Instruct was evaluated on 14 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Llama 3.1 8B Instruct is suitable for a wide range of AI applications: automation with tool calling (API integration, databases, external systems), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Llama 3.1 8B Instruct competes directly with similarly capable models. As an open source model, it competes with Qwen (Alibaba), Mistral, and DeepSeek, as well as proprietary models like GPT, Claude, and Gemini. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Llama 3.1 8B Instruct?
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...
How much does Llama 3.1 8B Instruct cost?
Llama 3.1 8B Instruct costs $0.1/1M input tokens and $0.1/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Llama 3.1 8B Instruct compare with other models?
In available benchmarks, Llama 3.1 8B Instruct scored: Terminal-Bench Hard: 1/100, SciCode: 13/100, LiveCodeBench: 12/100. See the full table above for a detailed comparison.
Is Llama 3.1 8B Instruct open source?
Yes, Llama 3.1 8B Instruct is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
What is Llama 3.1 8B Instruct best for?
Llama 3.1 8B Instruct excels at general-purpose language tasks. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →