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Qwen/Qwen3.5-35B-A3B

DeepInfra Inc./🇺🇸 US/chat

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.More
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Which id to call

deepinfra/Qwen/Qwen3.5-35B-A3B

This exact deployment on DeepInfra Inc., with no routing and no failover. Send it as the model field.

Input /1M

$0.14

$0.05 cached

Output /1M

$1.00

7.1x input

Context

262K

tokens

Added

Feb 2026

chat

Capabilities 5/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What Qwen/Qwen3.5-35B-A3B costs

Provider prices per 1M tokens, updated September 6, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.14

Output /1M

$1.00

Cache write /1M

-

Cache read /1M

$0.05

What a workload costs

100K input + 10K output
$0.0240
1M input + 100K output
$0.24
10M input + 1M output
$2.40

At the rates above, before caching. A cache read costs $0.05 per 1M, so repeated context lands under these figures.

model=

Which id to call

One base url, https://router.requesty.ai/v1, and one key for every id here.

deepinfra/Qwen/Qwen3.5-35B-A3B

This exact deployment on DeepInfra Inc., with no routing and no failover. Send it as the model field.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.

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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)

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window262K tokens
Max output-
API typechat
AddedFeb 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇺🇸 US
Privacy policyDeepInfra Privacy Policy →

Released 2026-02-24

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

GPQA Diamondreasoning
84.5%

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

Intelligence Indexreasoning
29.9%

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

Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.

Same provider

More from DeepInfra Inc.

Newest first, on the same provider and the same key.

glm-5.3-flash

1.0M ctx/$0.15/1M

glm-5.3

1.0M ctx/$1.20/1M

deepseek-v4-pro-0813

1.0M ctx/$1.30/1M

qwen3.8

262K ctx/$2.00/1M

deepseek-v4-flash-0731

1.0M ctx/$0.09/1M

deepseek-v4-flash-0731:flex

1.0M ctx/$0.07/1M

Reference

Qwen/Qwen3.5-35B-A3B 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. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

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.

Can I run Qwen/Qwen3.5-35B-A3B through Requesty?

Yes. Qwen/Qwen3.5-35B-A3B runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/Qwen/Qwen3.5-35B-A3B", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call Qwen/Qwen3.5-35B-A3B through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

All DeepInfra Inc. models