DeepSeek: R1 Distill Qwen 14B

by DeepSeek

DeepSeek R1 Distill Qwen 14B is a distilled large language model based on [Qwen 2.5 14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models. Other benchmark results include: - AIME 2024 pass@1: 69.7 - MATH-500 pass@1: 93.9 - CodeForces Rating: 1481 The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.

Avg Score

0.0%

0 answers

Avg Latency

0ms

0 runs

Pricing

$0.15

input

$0.15

output

per 1M tokens

Context

33K

tokens

Alternatives

Models with similar or better quality but different tradeoffs

No alternatives found

Run benchmarks on this model to discover alternatives

Other Models from DeepSeek

Compare performance with other models from the same creator

Model	Score	Latency	Cost/1M
DeepSeek: R1	96.2%	109.7s	$1.60
DeepSeek: DeepSeek V3.1 Terminus	91.9%	41.8s	$0.50
DeepSeek: DeepSeek V3.2 Exp	89.6%	96.8s	$0.27
DeepSeek: DeepSeek V3	88.5%	21.2s	$0.75
DeepSeek: DeepSeek V3.1	85.8%	60.0s	$0.45
DeepSeek: R1 0528	85.0%	36.9s	Free
DeepSeek: DeepSeek V3.1 Terminus	83.1%	21.4s	$0.50
DeepSeek: R1 0528	81.5%	120.7s	$1.07
DeepSeek: DeepSeek V3.2 Speciale	80.7%	152.3s	$0.34
DeepSeek: DeepSeek V3.2	79.9%	37.8s	$0.32
DeepSeek: DeepSeek V3 0324	78.7%	15.3s	$0.53
DeepSeek: R1 Distill Llama 70B	49.2%	33.8s	$0.07
DeepSeek: R1 Distill Qwen 32B	40.8%	53.5s	$0.29
DeepSeek: DeepSeek R1 0528 Qwen3 8B	—	—	$0.07
DeepSeek: DeepSeek Prover V2	—	—	$1.34

Benchmark Performance

How this model performs across different benchmarks

No benchmark data available

Run benchmarks with this model to see performance breakdown

Score Over Time

Performance trends across all benchmark runs

No score trend data

Score history will appear here after multiple runs

Benchmark Activity

Number of benchmark runs over time

No activity data

Activity will appear here after benchmark runs

Quickstart

Get started with this model using OpenRouter

View on OpenRouter

import { OpenRouter } from "@openrouter/sdk";

const openrouter = new OpenRouter({
  apiKey: "<OPENROUTER_API_KEY>"
});

const completion = await openrouter.chat.completions.create({
  model: "deepseek/deepseek-r1-distill-qwen-14b",
  messages: [
    {
      role: "user",
      content: "Hello!"
    }
  ]
});

console.log(completion.choices[0].message.content);

Get your API key at openrouter.ai/keys