Llama 3.1 Euryale 70B v2.2
meta/l3-1-euryale-70bمن Meta · العائلة: llama · أُصدِر 2024-08-28 · تاريخ المعرفة: 2023-12-31
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
القدرات
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.
Coding64
- Tool calling40/40
- Structured output20/20
- Reasoning0/10
- Context window (100K → 1M)2/20
- Provider availability2/10
Agents72
- Tool calling35/35
- Structured output25/25
- Reasoning0/15
- Output token limit10/15
- Provider availability2/10
JSON / structured output97
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume17/20
Cost efficiency57
- Headline price (log-scaled)57/95
- Has prompt-cache pricing0/5
Long context46
- Context window (100K → 2M)36/90
- Has published price for full window10/10
Production-readiness70
- Number of independent providers10/40
- 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 | $4.68 < $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 | $9.35 < $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 | $2.13 < $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 | $7.65 < $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 | $10.71 $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
تفاصيل التسعير
السعر المُوصى به من openrouter · sao10k/l3.1-euryale-70b
متاح لدى 2 مزود
| المزود | معرف نموذج المزود | إدخال / 1M | إخراج / 1M | السياق | تاريخ الإصدار |
|---|---|---|---|---|---|
| OpenRouter openrouter | sao10k/l3.1-euryale-70b | $0.850 | $0.850 | 131K | 2024-08-28 |
| Kilo Gateway kilo | sao10k/l3.1-euryale-70b | $0.850 | $0.850 | 131K | 2024-08-28 |
Frequently asked questions
How much does Llama 3.1 Euryale 70B v2.2 cost?
Llama 3.1 Euryale 70B v2.2 costs $0.850 per 1M input tokens and $0.850 per 1M output tokens, sourced from openrouter. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Llama 3.1 Euryale 70B v2.2?
Llama 3.1 Euryale 70B v2.2 has a context window of 131K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.
Does Llama 3.1 Euryale 70B v2.2 support tool calling?
Yes. Llama 3.1 Euryale 70B v2.2 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 Llama 3.1 Euryale 70B v2.2 support structured output / JSON mode?
Yes. Llama 3.1 Euryale 70B v2.2 supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can Llama 3.1 Euryale 70B v2.2 accept image input?
No. Llama 3.1 Euryale 70B v2.2 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Llama 3.1 Euryale 70B v2.2 open-weight?
Yes. Llama 3.1 Euryale 70B v2.2's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Llama 3.1 Euryale 70B v2.2?
If Llama 3.1 Euryale 70B v2.2 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
آخر تحديث:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.