Snowflake:モデルの知能、性能、料金

Snowflake
Snowflake

Snowflakeのモデルを、品質、料金、出力速度、遅延、コンテキストウィンドウなどの主要指標で分析します。 この分析は、ユースケースに最適なSnowflake提供モデルを選ぶための参考情報です。

最高の知能

#1
Llama 4 Maverick
Llama 4 Maverick
14

Intelligence Index

モデル合計:1件

最速

#1
Llama 4 Maverick
Llama 4 Maverick
131 t/s

出力速度

モデル合計:1件

最安料金

#1
Llama 4 Maverick
Llama 4 Maverick
$0.50

ブレンド料金(100万トークンあたり)

モデル合計:1件

現在、SnowflakeはLlama 4 Maverickを提供しています。

ハイライト

Artificial Analysis Intelligence Index · Higher is better
Output tokens per second · Higher is better
USD per 1M tokens (blended) · Lower is better

知能評価

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

Agentic real-world work tasks, (Elo-500)/2000

Agentic tool use

Agentic coding & terminal use

Coding

Reasoning & knowledge

Scientific reasoning

Physics reasoning

Long context reasoning

Agentic knowledge work, Elo

Agentic SaaS workflows

No data available

Legal agentic work, criterion pass rate

No data available

Agentic business operations

No data available

Instruction following

Long-horizon agentic tasks

No data available

Kubernetes incident root-cause analysis

No data available

Visual reasoning

Reasoning models are indicated by a lightbulb icon

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon

While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.

コンテキストウィンドウ

Context Window

Context window: tokens limit · Higher is better
Reasoning models are indicated by a lightbulb icon

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

料金

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon

While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.

性能の概要

Output Speed vs. Price

Output speed: output tokens per second · USD per 1M tokens (blended)
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

速度

出力速度(1秒あたりのトークン数)で測定

Output Speed

Output tokens per second · Higher is better
Reasoning models are indicated by a lightbulb icon

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

遅延

最初のトークンまでの時間(秒)で測定

Latency: Time To First Token

Seconds to first token received · Lower is better
Reasoning models are indicated by a lightbulb icon

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

エンドツーエンド応答時間

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time vs. Price

End-to-end response time: end-to-end seconds to output 500 tokens · USD per 1M tokens (blended)
Most attractive quadrant

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

詳細分析
OpenAIのロゴ
gpt-oss-120b (low)
131k
オープン
15
$0.03
--
--
--
--
Metaのロゴ
Llama 4 Maverick
131k
オープン
14
$0.06
131
1.13
4.95
--

主要な定義

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

よくある質問

Snowflakeに関するよくある質問

Snowflakeが提供し、当社が追跡しているモデルは1モデルです:Llama 4 Maverick

Snowflakeで利用できるモデルのうち、知能が最も高いのはIntelligence Indexスコア14のLlama 4 Maverickです。

Snowflakeで出力速度が最も速いモデルは、毎秒131.0トークンのLlama 4 Maverickです。

Snowflakeで最初の回答トークンまでの時間が最短のモデルは、1.13秒のLlama 4 Maverickです。遅延が短いほど、最初の応答が速くなります。

Snowflakeでブレンド料金が最も安いモデルは、100万トークンあたり$0.50のLlama 4 Maverickです(キャッシュヒット/入力/出力を7:2:1とした場合)。

はい。Snowflakeの全1モデルが、構造化出力のJSONモードに対応しています。

はい。Snowflakeの全1モデルがオープンウェイトです。

はい。インフラストラクチャの変更、負荷分散、アップデートにより、プロバイダーの性能は時間とともに変化する場合があります。すべてのプロバイダーを継続的にベンチマークし、「推移」グラフに過去の性能傾向を表示しています。

Snowflakeのモデルを選ぶ際は、知能(品質を重視するタスク)、出力速度(高スループットが必要なタスク)、遅延(最初の応答の速さが必要な対話型アプリケーション)、料金(費用を重視するワークロード)、コンテキストウィンドウの規模、JSONモード、関数呼び出しへの対応などを検討してください。