AI 模型情报

L3 8B Stheno V3.2

novita-ai/l3-8b-stheno-v3-2

出品方： novita-ai · 系列: llama · 发布 2024-11-29

$0.050
输入 / 1M token
$0.050
输出 / 1M token
8K
上下文长度
32K
最大输出

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

能力清单

✓ 工具调用✗ 推理? 结构化输出✗ 附件✓ 开放权重✓ 温度可调
支持模态: 输入 text · 输出 text

Model fit scores

0–100 · higher is better

These 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.

Coding41
  • Tool calling40/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)0/20
  • 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 efficiency86
  • Headline price (log-scaled)86/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
Production-readiness58
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K8/15
  • 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.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$0.28
< $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
$0.55
< $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
$0.13
< $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
$0.45
< $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
$0.63
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定价详情

推荐定价来自 novita-ai · Sao10K/L3-8B-Stheno-v3.2

$0.050
输入
$0.050
输出

在 1 家渠道可用

服务商服务商模型 ID输入 / 1M输出 / 1M上下文发布日期
NovitaAI
novita-ai
Sao10K/L3-8B-Stheno-v3.2$0.050$0.0508K2024-11-29

Frequently asked questions

How much does L3 8B Stheno V3.2 cost?

L3 8B Stheno V3.2 costs $0.050 per 1M input tokens and $0.050 per 1M output tokens, sourced from novita-ai. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of L3 8B Stheno V3.2?

L3 8B Stheno V3.2 has a context window of 8K tokens, with a max output of 32K tokens per reply. This is the total combined size of prompt + completion.

Does L3 8B Stheno V3.2 support tool calling?

Yes. L3 8B Stheno V3.2 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 L3 8B Stheno V3.2 support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for L3 8B Stheno V3.2 in our data source. Verify with novita-ai's official documentation before relying on it in production.

Can L3 8B Stheno V3.2 accept image input?

No. L3 8B Stheno V3.2 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is L3 8B Stheno V3.2 open-weight?

Yes. L3 8B Stheno V3.2'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 L3 8B Stheno V3.2?

If L3 8B Stheno V3.2 doesn't fit, consider Ling-2.6-1T, Ling-2.6-flash, PaddleOCR-VL. 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 come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

More novita-ai models

Capability lists this model is in

See also

最近更新：

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.