AIモデルインテリジェンス

Phi-4 15B

microsoft/phi-4-multimodal-instruct

提供: Microsoft · ファミリー: phi · リリース 2025-01-01 · 知識カットオフ: 2023-10

$0.240
入力 / 100万トークン
$0.470
出力 / 100万トークン
32K
コンテキスト長
32K
最大出力

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

機能一覧

ツール呼び出し推論? 構造化出力添付オープンウェイト? 温度制御
モダリティ: 入力 text, image · 出力 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.

Coding3
  • Tool calling0/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)0/20
  • Provider availability3/10
Agents18
  • Tool calling0/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability3/10
JSON / structured output19
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control0/10
  • Price-friendly for high-volume19/20
Cost efficiency66
  • Headline price (log-scaled)66/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
Vision71
  • Accepts image input50/50
  • Context window (10K → 1M)8/30
  • Has published price10/10
  • Provider availability3/10
Production-readiness69
  • Number of independent providers15/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers4/10
  • 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
$1.44
< $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
$2.87
< $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
$0.72
< $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
$2.39
< $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
$3.16
< $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): evroc · microsoft/Phi-4-multimodal-instruct

$0.240
入力
$0.470
出力

最安プロバイダー: nvidia · Unknown 入力 + Unknown 出力

3 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
evroc
evroc
microsoft/Phi-4-multimodal-instruct$0.240$0.47032K2025-01-01
Nvidia
nvidia
microsoft/phi-4-multimodal-instructUnknownUnknown128K2025-07-26
GitHub Models
github-models
microsoft/phi-4-multimodal-instructUnknownUnknown128K2024-12-11

プロバイダー間でデータに差異

  • context_window varies: 128000, 32000
  • release_date varies (span 227d): 2024-12-11, 2025-01-01, 2025-07-26
  • modalities varies across offerings

プロバイダーごとに本モデルの値が異なります。上部の「主要数値」は代表的プロバイダーを使用しています。詳細は表をご確認ください。

Frequently asked questions

How much does Phi-4 15B cost?

Phi-4 15B costs $0.240 per 1M input tokens and $0.470 per 1M output tokens, sourced from evroc. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Phi-4 15B?

Phi-4 15B has a context window of 32K tokens, with a max output of 32K tokens per reply. This is the total combined size of prompt + completion.

Does Phi-4 15B support tool calling?

No. Phi-4 15B does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does Phi-4 15B support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for Phi-4 15B in our data source. Verify with Microsoft's official documentation before relying on it in production.

Can Phi-4 15B accept image input?

Yes. Phi-4 15B accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check Microsoft's docs for the exact rule.

Is Phi-4 15B open-weight?

Yes. Phi-4 15B'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 Phi-4 15B?

If Phi-4 15B doesn't fit, consider Phi-4-mini-instruct, Phi-4, WizardLM-2 8x22B. 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.

More Microsoft models

Capability lists this model is in

最終更新:

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.