Deepseek R1 Distill Qwen 1.5B

Deepseek R1 Distill Qwen 1.5B

DeepSeek - R1は、DeepSeek - V3（合計6710億のパラメータ、トークンごとに370億のパラメータがアクティブ）をベースに構築された初代推論モデルです。大規模強化学習（RL）を組み合わせることで、思考連鎖と推論能力を強化し、数学、コード、および多段階推論タスクで優れた性能を発揮します。

DeepSeek - R1は、DeepSeek - V3（合計6710億のパラメータ、トークンごとに370億のパラメータがアクティブ）をベースに構築された初代推論モデルです。大規模強化学習（RL）を組み合わせることで、思考連鎖と推論能力を強化し、数学、コード、および多段階推論タスクで優れた性能を発揮します。

Intelligence(Weak)

Speed(Fast)

Input Supported Modalities

No

Is Reasoning Model

128,000

Context Window

128,000

Maximum Output Tokens

-

Knowledge Cutoff

Pricing

- /M tokens

Input

- /M tokens

Output

￥1.3 /M tokens

Blended Price

Quick Simple Comparison

DeepSeek R1 Distill Llama 70B

￥0.1

DeepSeek R1 Distill Qwen 32B

￥0.12

DeepSeek V3 0324 (Mar' 25)

Basic Parameters

GPT-4.1 Technical Parameters

Parameter Count

1,780.0M

Context Length

128.00k tokens

Training Data Cutoff

Open Source Category

Open Weights (Permissive License)

Multimodal Support

Text Only

Throughput

0

Release Date

2025-01-20

Response Speed

383.73,148 tokens/s

Benchmark Scores

Below is the performance of claude-monet in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.

Intelligence Index

Large Language Model Intelligence Level

1917

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

680

Indicator of AI model performance on coding tasks

Math Index

Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks

-

Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks

MMLU Pro

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

26.9

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

GPQA

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

9.8

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

HLE

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

3.3

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

LiveCodeBench

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

7

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

SciCode

The model's capability in code generation for scientific computing or specific scientific domains

6.6

The model's capability in code generation for scientific computing or specific scientific domains

HumanEval

Score achieved by the AI model on the specific HumanEval benchmark test set

45.4

Score achieved by the AI model on the specific HumanEval benchmark test set

Math 500 Score

Score on the first 500 larger, more well-known mathematical benchmark tests

68.7

Score on the first 500 larger, more well-known mathematical benchmark tests

AIME Score

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

17.7

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

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