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Qwen/Qwen3.5-2B

Qwen3.5-2B is a compact yet capable model from Alibaba's Qwen3.5 series. It features a 262K token context window, support for 201 languages, thinking/reasoning mode, and tool calling for agentic workflows. A strong choice for prototyping, fine-tuning, and efficient multilingual deployments.

VisionReasoningTool callingJSON schema
Try Qwen/Qwen3.5-2BCompareDocs

Specifications

Context window262K tokens
Max outputβ€”
API typechat
AddedMay 27, 2026
Model IDdeepinfra/Qwen/Qwen3.5-2B
Data retentionNo
Used for trainingNo
Provider locationπŸ‡ΊπŸ‡Έ US
Privacy policyDeepInfra Privacy Policy→

Benchmarks

Released 2026-03-02
Coding Indexcoding
3.5%

Artificial Analysis Coding Index β€” a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
45.6%

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

Intelligence Indexreasoning
16.3%

Artificial Analysis Intelligence Index β€” 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 β€” always test on your own workload.

Pricing

Input / 1M
$0.02
Output / 1M
$0.10
Cache write
β€”
Cache read
β€”
Estimated cost
100K input + 10K output$0.0030
1M input + 100K output$0.0300
10M input + 1M output$0.30

Requesty charges exactly what the upstream provider charges β€” 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 deepinfra/Qwen/Qwen3.5-2B.

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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="deepinfra/Qwen/Qwen3.5-2B",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

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Coding 43
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Frequently asked questions

How much does Qwen/Qwen3.5-2B cost?
Qwen/Qwen3.5-2B is priced at $0.02 per million input tokens and $0.10 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges β€” we don't add markup.
What is the context window of Qwen/Qwen3.5-2B?
Qwen/Qwen3.5-2B has a context window of 262K tokens. That's roughly 350 words of input you can fit in a single prompt.
How does Qwen/Qwen3.5-2B perform on benchmarks?
Qwen/Qwen3.5-2B scores 69.0% on τ²-Bench, 45.6% on GPQA Diamond, 16.3% on Intelligence Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can Qwen/Qwen3.5-2B do?
Qwen/Qwen3.5-2B supports vision input, tool calling, extended reasoning, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use Qwen/Qwen3.5-2B 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 "deepinfra/Qwen/Qwen3.5-2B". The Quickstart above shows Python, JavaScript and cURL snippets.

Access Qwen/Qwen3.5-2B through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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