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deepseek-r1-distill-qwen-32b

DeepSeek R1 Distill Qwen 32B is a distilled large language model based on Qwen 2.5 32B, using outputs from 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: 72.6 MATH-500 pass@1: 94.3 CodeForces Rating: 1691 The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.

Tool calling
Try deepseek-r1-distill-qwen-32bCompareDocs

Specifications

Context window13K tokens
Max output—
API typechat
AddedJan 30, 2025
Model IDnovita/deepseek/deepseek-r1-distill-qwen-32b
Data retentionYes
Used for trainingUnknown
Provider location🇺🇸 US
Privacy policyNovita AI Privacy Policy→

Benchmarks

Released 2025-01-20
GPQA Diamondreasoning
61.5%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
17.2%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality — always test on your own workload.

Pricing

Input / 1M
$0.30
Output / 1M
$0.30
Cache write
—
Cache read
—
Estimated cost
100K input + 10K output$0.0330
1M input + 100K output$0.33
10M input + 1M output$3.30

Requesty charges exactly what the upstream provider charges — no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to novita/deepseek/deepseek-r1-distill-qwen-32b.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="novita/deepseek/deepseek-r1-distill-qwen-32b",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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Frequently asked questions

How much does deepseek-r1-distill-qwen-32b cost?
deepseek-r1-distill-qwen-32b is priced at $0.30 per million input tokens and $0.30 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges — we don't add markup.
What is the context window of deepseek-r1-distill-qwen-32b?
deepseek-r1-distill-qwen-32b has a context window of 13K tokens. That's roughly 17 words of input you can fit in a single prompt.
How does deepseek-r1-distill-qwen-32b perform on benchmarks?
deepseek-r1-distill-qwen-32b scores 73.9% on MMLU Pro, 63.0% on Math Index, 63.0% on AIME 2025. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can deepseek-r1-distill-qwen-32b do?
deepseek-r1-distill-qwen-32b supports tool calling. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use deepseek-r1-distill-qwen-32b with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "novita/deepseek/deepseek-r1-distill-qwen-32b". The Quickstart above shows Python, JavaScript and cURL snippets.

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