DeepSeekReleased on Jan 20, 2025

DeepSeek R1 Distill Qwen 14B: API Pricing, Context Window & Benchmarks

DeepSeek R1 Distill Qwen 14B is a language model from DeepSeek, released in January 2025.

DeepSeek-R1 is the first-generation reasoning model built atop DeepSeek-V3 (671B total parameters, 37B activated per token). It incorporates large-scale reinforcement learning (RL) to enhance its chain-of-thought and reasoning

DeepSeek R1 Distill Qwen 14B benchmarks

Rankings

Quality Tracker

DeepSeek R1 Distill Qwen 14B Performance Across Datasets

Scores sourced from the model's scorecard, paper, or official blog posts

LLM Stats Logollm-stats.com - Sun Jul 19 2026
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DeepSeek R1 Distill Qwen 14B model size

DeepSeek R1 Distill Qwen 14B has 14.8 billion parameters and was trained on 14.8 trillion tokens. See how it compares to other models in the same parameter range.

ParametersTraining tokens
14.8B
14.8Ttokens
1000× tokens-to-params ratio
Medium (10–30B)
14.8B
1B7B70B405B

DeepSeek R1 Distill Qwen 14B API

Available from the model provider

DeepSeek R1 Distill Qwen 14B has an official provider API. It is not currently routed through the LLM Stats gateway.

Read the official API documentation

DeepSeek R1 Distill Qwen 14B latency

DeepSeek R1 Distill Qwen 14B time to first token, sustained output throughput, and failed-request rate from live API traffic over the trailing 7 days.

DeepSeek R1 Distill Qwen 14B examples

Recent arena outputs from DeepSeek R1 Distill Qwen 14B, picked from the highest-ranked matchups.

DeepSeek R1 Distill Qwen 14B license

DeepSeek R1 Distill Qwen 14B is released under the MIT license, which permits commercial use, has 14.8B parameters.

License
MIT
Commercial use allowed
Parameters
14.8B

MIT License - allows commercial use

DeepSeek R1 Distill Qwen 14B resources

Official sources for DeepSeek R1 Distill Qwen 14B: api documentation, official playground, paper or system card, source repository, model weights.

DeepSeek R1 Distill Qwen 14B vs other models

The most-compared alternatives to DeepSeek R1 Distill Qwen 14B are Claude 3.5 Sonnet, Phi 4 Reasoning Plus, Gemini 1.5 Pro. Open any pair side-by-side for benchmarks, pricing, context, and latency.

Models like DeepSeek R1 Distill Qwen 14B

Models ranked just above and below DeepSeek R1 Distill Qwen 14B by LLM Stats score.

 

Claude 3.5 Sonnet

Score pending
 

Phi 4 Reasoning Plus

Score pending
 

Gemini 1.5 Pro

Score pending
 

QwQ-32B

Score pending
 

DeepSeek R1 Distill Qwen 32B

Score pending
 

Claude 3.7 Sonnet

Score pending

FAQ

Common questions about DeepSeek R1 Distill Qwen 14B.

When was DeepSeek R1 Distill Qwen 14B released?

DeepSeek R1 Distill Qwen 14B was released on January 20, 2025 by DeepSeek. This is the official DeepSeek R1 Distill Qwen 14B release date tracked on LLM Stats.

Is DeepSeek R1 Distill Qwen 14B available via API?

Yes, DeepSeek R1 Distill Qwen 14B is available via API. See the official documentation for authentication and endpoint details.

How big is DeepSeek R1 Distill Qwen 14B?

DeepSeek R1 Distill Qwen 14B has 14.8 billion parameters. It was trained on 14.8 trillion tokens. It ships as an open-weight model, so you can download and run it on your own hardware.

Who created DeepSeek R1 Distill Qwen 14B?

DeepSeek R1 Distill Qwen 14B was created by DeepSeek.

What is the license for DeepSeek R1 Distill Qwen 14B?

DeepSeek R1 Distill Qwen 14B is released under the MIT license. This is an open-source / open-weight license that permits self-hosting.

Where is the DeepSeek R1 Distill Qwen 14B paper or technical report?

DeepSeek R1 Distill Qwen 14B has a paper or technical report available at https://arxiv.org/pdf/2501.12948. Use that source for architecture, training, release and evaluation details.

What models should I compare DeepSeek R1 Distill Qwen 14B against?

Common DeepSeek R1 Distill Qwen 14B comparisons include DeepSeek R1 Distill Qwen 14B vs Claude 3.5 Sonnet, DeepSeek R1 Distill Qwen 14B vs Phi 4 Reasoning Plus, DeepSeek R1 Distill Qwen 14B vs Gemini 1.5 Pro. Compare them side by side for benchmark scores, pricing, context window, latency and API availability.