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Models / Qwen / Qwen2.5 Coder 32B Instruct

Qwen2.5 Coder 32B Instruct APIOPEN WEIGHTS128K context

by Qwen · text->text · released 2024-11-11

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen).

Get an API key Try in Chat https://api.datallmlab.com/v1
Input / 1M
$0.66
Output / 1M
$1.00
Context
128K
Providers
1
HF downloads · 30d
1.4M
Cheaper than
60% of catalog

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is Qwen2.5 Coder 32B Instruct?

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**...

Qwen2.5 Coder 32B Instruct on the release timeline

$0.15$0.76$3.90Qwen2.5 Coder 32B Instruct · $1.002024-112026-032026-06
Each point is a qwen release, placed at its launch date with its current output price (log scale, $/1M). Bubble size ∝ context window; Qwen2.5 Coder 32B Instruct is highlighted. Source: provider catalog, verified July 2026.

Qwen2.5 Coder 32B Instruct pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

ModelInput / 1MOutput / 1MCache readCache writeContext
Qwen2.5 Coder 32B Instruct$0.66$1.00128K

On output price, Qwen2.5 Coder 32B Instruct is cheaper than 60% of the 309 models in the catalog.

What Qwen2.5 Coder 32B Instruct costs per month

WorkloadTokens in / out (monthly)Est. cost
Support chatbot40M / 12M$38.40
RAG / knowledge base200M / 20M$152
Coding agent80M / 25M$77.80
Batch extraction150M / 8M$107
Content generation20M / 40M$53.20

Estimate your own monthly cost

= input × $0.66 + output × $1.00 per 1M · pay-as-you-go, computed in your browser.

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

Qwen2.5 Coder 32B Instruct vs alternatives

Pick Qwen2.5 Coder 32B Instruct when you want open weights you can also self-host. If price is the only priority, it is already the cheapest here.
ModelInput / 1MOutput / 1MContextOur test
Qwen2.5 Coder 32B Instruct$0.66$1.00128K
Qwen2.5 VL 72B Instruct$0.80$1.00131K
Qwen3.5-35B-A3B$0.14$1.00262K
Qwen3.6 35B A3B$0.14$1.00262K
Weaver (alpha)$0.75$1.008K
Hermes 3 405B Instruct$1.00$1.00131K

When not to use Qwen2.5 Coder 32B Instruct

Specs

Model IDqwen/qwen-2.5-coder-32b-instruct
Modalitytext->text (input: text)
Context window128,000 tokens
Max output32,768 tokens
Tool / function calling
Structured output (JSON)
Released2024-11-11
Knowledge cutoff2024-06-30
Open weightsQwen/Qwen2.5-Coder-32B-Instruct · 1.4M downloads / 2.1K likes (30d)

How to call Qwen2.5 Coder 32B Instruct

from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="qwen/qwen-2.5-coder-32b-instruct",
    messages=[{"role": "user", "content": "Hello"}],
)
print(resp.choices[0].message.content)
curl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen/qwen-2.5-coder-32b-instruct","messages":[{"role":"user","content":"Hello"}]}'
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "qwen/qwen-2.5-coder-32b-instruct",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Qwen2.5 Coder 32B Instruct and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Qwen2.5 Coder 32B Instruct

Tips are derived from Qwen2.5 Coder 32B Instruct's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Qwen2.5 Coder 32B Instruct

Popular open-source projects for running and building with Qwen2.5 Coder 32B Instruct — star counts pulled from GitHub (July 2026).

ollama/ollama★ 175.3K
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Go
langgenius/dify★ 147.5K
Production-ready platform for agentic workflow development.
TypeScript
open-webui/open-webui★ 144.0K
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Python
langchain-ai/langchain★ 140.8K
The agent engineering platform.
Python
ggml-org/llama.cpp★ 119.1K
LLM inference in C/C++
C++
vllm-project/vllm★ 85.2K
A high-throughput and memory-efficient inference and serving engine for LLMs
Python

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to Qwen2.5 Coder 32B Instruct

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → qwen/qwen-2.5-coder-32b-instruct. Messages, streaming and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

Qwen2.5 Coder 32B Instruct ships open weights (Qwen/Qwen2.5-Coder-32B-Instruct, ~1.4M downloads and 2.1K likes in the last 30 days), so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 1 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.

Related reading

Qwen API: Pricing & Keys
DataLLM Lab Blog
Qwen vs DeepSeek
DataLLM Lab Blog
How OpenAI-Compatible APIs Work
DataLLM Lab Blog

Call Qwen2.5 Coder 32B Instruct with one key

300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.

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Frequently asked questions

What is Qwen2.5 Coder 32B Instruct?

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). It accepts text input with a 128K-token context window and was released on 2024-11-11. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.

How much does Qwen2.5 Coder 32B Instruct cost?

On DataLLM Lab it is $0.66 per 1M input tokens and $1.00 per 1M output tokens — cheaper than about 60% of the 309-model catalog on output price. Pay-as-you-go, no subscription.

What is the context window of Qwen2.5 Coder 32B Instruct?

128K tokens, with up to 33K max output tokens.

Is Qwen2.5 Coder 32B Instruct open source?

Yes — open weights are published on Hugging Face (Qwen/Qwen2.5-Coder-32B-Instruct), with about 1.4M downloads and 2.1K likes in the last 30 days. You can self-host it or call it via DataLLM Lab.

How do I call the Qwen2.5 Coder 32B Instruct API?

Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "qwen/qwen-2.5-coder-32b-instruct". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.

What are good alternatives to Qwen2.5 Coder 32B Instruct?

Close options by price and capability include Qwen2.5 VL 72B Instruct, Qwen3.5-35B-A3B, Qwen3.6 35B A3B — all callable with the same DataLLM Lab key.