Requesty

Qwen/Qwen3.5-35B-A3B

Qwen3.5-35B-A3B is an efficient Mixture-of-Experts model from Alibaba's Qwen3.5 series with 35B total parameters and only 3B activated per token. It features a 262K token context window (extensible to 1M with YaRN), thinking/reasoning mode, tool calling, and support for 201 languages. Delivers strong performance on reasoning, coding, and vision-language tasks at a fraction of the compute cost.

VisionReasoningTool callingCachingJSON schema

Specifications

Context window262K tokens
Max outputβ€”
API typechat
AddedMay 27, 2026
Model IDdeepinfra/Qwen/Qwen3.5-35B-A3B
Data retentionNo
Used for trainingNo
Provider locationπŸ‡ΊπŸ‡Έ US

Benchmarks

Released 2026-02-24
Coding Indexcoding
30.3%

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

GPQA Diamondreasoning
84.5%

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

Intelligence Indexreasoning
37.1%

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
$0.14
Output / 1M
$1.00
Cache write
β€”
Cache read / 1M
$0.05
Estimated cost
100K input + 10K output$0.0240
1M input + 100K output$0.24
10M input + 1M output$2.40

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/Qwen3.5-35B-A3B.

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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/Qwen3.5-35B-A3B", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Other DeepInfra Inc. models

Frequently asked questions

How much does Qwen/Qwen3.5-35B-A3B cost?
Qwen/Qwen3.5-35B-A3B is priced at $0.14 per million input tokens and $1.00 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges β€” we don't add markup.
What is the context window of Qwen/Qwen3.5-35B-A3B?
Qwen/Qwen3.5-35B-A3B has a context window of 262K tokens. That's roughly 350 words of input you can fit in a single prompt.
How does Qwen/Qwen3.5-35B-A3B perform on benchmarks?
Qwen/Qwen3.5-35B-A3B scores 89.2% on τ²-Bench, 84.5% on GPQA Diamond, 37.7% on SciCode. 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/Qwen3.5-35B-A3B do?
Qwen/Qwen3.5-35B-A3B supports vision input, tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use Qwen/Qwen3.5-35B-A3B 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/Qwen3.5-35B-A3B". The Quickstart above shows Python, JavaScript and cURL snippets.

Access Qwen/Qwen3.5-35B-A3B through Requesty

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