Context Window
—
Input Price/1M
$2.75
Output Price/1M
$6.50
Parameters
—
Speed
37 tok/s
Latency (TTFT)
580ms
Llama 3.1 Instruct 405B results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 7.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 31.0 | 100.0 | Artificial Analysis official API |
| SciCode | 30.0 | 100.0 | — |
| AA Coding Index | 14.5 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 73.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 24.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 70.3 | 100.0 | Artificial Analysis official API |
| AA Math Index | 3.0 | 100.0 | Artificial Analysis official API |
| AIME 2025 | 3.0 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 17.4 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 73.2 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 52.0 | 100.0 | Artificial Analysis official API |
| IFBench | 39.0 | 100.0 | — |
| HLE | 4.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 19.0 | 100.0 | — |
Llama 3.1 Instruct 405B is an AI model developed by Meta, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via Meta's cloud API.
Llama 3.1 Instruct 405B is usage-based, priced at $2.75/1M input tokens and $6.5/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The mid-range pricing balances quality and cost for most professional applications.
Llama 3.1 Instruct 405B was evaluated on 15 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.
Llama 3.1 Instruct 405B specializes in text, offering advanced capabilities for creating and processing text content.
In the 2026 AI model ecosystem, Llama 3.1 Instruct 405B 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.
Llama 3.1 Instruct 405B is an AI model developed by Meta. It is a text model.
Llama 3.1 Instruct 405B costs $2.75/1M input tokens and $6.5/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, Llama 3.1 Instruct 405B scored: Terminal-Bench Hard: 7/100, LiveCodeBench: 31/100, SciCode: 30/100. See the full table above for a detailed comparison.
No, Llama 3.1 Instruct 405B is a proprietary model from Meta. It is available via cloud API. For open source alternatives, check our open source model ranking.
Llama 3.1 Instruct 405B excels at general-purpose language tasks.
Last updated: June 01, 2026 • View methodology →