Qwen3 32B

Qwen3 32B on Zumik: live pricing, context, and caching, routable by id or alias through one OpenAI-compatible endpoint.

$0.70
Input / 1M tokens
$2.80
Output / 1M tokens
$0.70
Cache read
131K
Context window

At a glance.

ProviderFireworks AI
Familyqwen3
Released2025-04
LicenseOpen weights
Context window131K tokens
Max output16K tokens
Parameters33B
Modalitiestext
Tool callingYes
Reasoning modeYes
Cachingnone
Batch discountNo batch tier

What reuse looks like here.

Not yet profiled

Pricing, context, and capabilities for Qwen3 32B are live, but it is outside the flagship set Zumik benchmarks in depth, so measured reuse, capture, and warm TTFT are not shown yet. Run a workload estimate or route it by id to start collecting traces.

Reuse economics

What you actually pay once caching works.

At a typical 55% prefix reuse, a million input tokens on Qwen3 32B effectively costs $0.70 instead of $0.70 - blending to roughly $1.22 with a 25% output share. There is no batch tier, so cost control here leans on caching and routing.

Estimate it for your workload
Best for
text

Route it directly by id, or let an alias pick it when it wins under policy.

Same OpenAI client, this model.

python
from openai import OpenAI

client = OpenAI(base_url="https://api.zumik.ai/v1", api_key="zk_live_...")

r = client.responses.create(
    model="qwen3-32b",
    input="Draft a fix for the failing test.",
)
print(r.usage.input_tokens_cached)   # confirm reuse

Qwen3 32B, answered.

How much does Qwen3 32B cost?

Qwen3 32B is $0.70 per million input tokens and $2.80 per million output tokens through Zumik. Cache reads are $0.70 per million, a 0% discount on input.

What is Qwen3 32B's context window?

Qwen3 32B supports a 131K-token context window with up to 16K output tokens.

Run Qwen3 32B with reuse measured.

Point an OpenAI client at Zumik and see exactly how much of this model's input you are reusing.