Meta Llama 3.1 8B Instruct Turbo
meta/llama-3-1-8b-instruct-turbo提供： Meta · ファミリー: llama · リリース 2024-07-23 · 知識カットオフ: 2024-07
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
機能一覧
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding43
- Tool calling40/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)2/20
- Provider availability1/10
Agents51
- Tool calling35/35
- Structured output0/25
- Reasoning0/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output50
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume20/20
Cost efficiency93
- Headline price (log-scaled)93/95
- Has prompt-cache pricing0/5
Long context45
- Context window (100K → 2M)35/90
- Has published price for full window10/10
Production-readiness65
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.12 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $0.23 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.06 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.19 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.26 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
料金詳細
推奨料金 (提供元): helicone · llama-3.1-8b-instruct-turbo
1 か所で利用可能
| プロバイダー | プロバイダーモデルID | 入力 / 1M | 出力 / 1M | コンテキスト | リリース日 |
|---|---|---|---|---|---|
| Helicone helicone | llama-3.1-8b-instruct-turbo | $0.020 | $0.030 | 128K | 2024-07-23 |
Frequently asked questions
How much does Meta Llama 3.1 8B Instruct Turbo cost?
Meta Llama 3.1 8B Instruct Turbo costs $0.020 per 1M input tokens and $0.030 per 1M output tokens, sourced from helicone. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Meta Llama 3.1 8B Instruct Turbo?
Meta Llama 3.1 8B Instruct Turbo has a context window of 128K tokens, with a max output of 128K tokens per reply. This is the total combined size of prompt + completion.
Does Meta Llama 3.1 8B Instruct Turbo support tool calling?
Yes. Meta Llama 3.1 8B Instruct Turbo supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Meta Llama 3.1 8B Instruct Turbo support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Meta Llama 3.1 8B Instruct Turbo in our data source. Verify with Meta's official documentation before relying on it in production.
Can Meta Llama 3.1 8B Instruct Turbo accept image input?
No. Meta Llama 3.1 8B Instruct Turbo only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Meta Llama 3.1 8B Instruct Turbo open-weight?
No. Meta Llama 3.1 8B Instruct Turbo is a proprietary model — only Meta (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Meta Llama 3.1 8B Instruct Turbo?
If Meta Llama 3.1 8B Instruct Turbo doesn't fit, consider Llama-3.3-70B-Instruct, Meta-Llama-3.1-8B-Instruct, Llama 4 Scout 17B 16E Instruct. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
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Capability lists this model is in
最終更新：
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.