Atlas / Models / Qwen / Qwen: Qwen2.5 Coder 7B Instruct

Qwen: Qwen2.5 Coder 7B Instruct✓ Catalog verified

qwen/qwen2.5-coder-7b-instruct

Qwen2.5-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enhancements like RoPE, SwiGLU, RMSNorm, and GQA attention with support for up to 128K tokens using YaRN-based extrapolation. It is trained on a large corpus of source code, synthetic data, and text-code grounding, providing robust performance across programming languages and agentic coding workflows. This model is part of the Qwen2.5-Coder family and offers strong compatibility with tools like vLLM for efficient deployment. Released under the Apache 2.0 license.

Input price
$0.03 /1M
Output price
$0.09 /1M
Context
33K
Modalities
text
Released
Apr 15, 2025
Tool calling
Atlas signal
79/100
01

Overview

Qwen2.5-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enhancements like RoPE, SwiGLU, RMSNorm, and GQA attention with support for up to 128K tokens using YaRN-based extrapolation. It is trained on a large corpus of source code, synthetic data, and text-code grounding, providing robust performance across programming languages and agentic coding workflows. This model is part of the Qwen2.5-Coder family and offers strong compatibility with tools like vLLM for efficient deployment. Released under the Apache 2.0 license.

Access: available through the official Qwen API. Context window: 33K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Aug 5, 2026
02

Specifications

API identifierqwen/qwen2.5-coder-7b-instruct
ProviderQwen
Model typeText LLM
Context window33K catalog
Input modalitiestext
Output modalitiestext
ReleasedApr 15, 2025
TokenizerQwen
ModeratedNo
Architecture modalitytext->text
Supported parameters
frequency_penaltymax_tokenspresence_penaltyrepetition_penaltyresponse_formatstructured_outputstemperaturetop_ktop_p
Source: provider documentation + catalog feedMethodology →
03

Pricing

Live pricing components for qwen/qwen2.5-coder-7b-instruct as published in the catalog.

$0.03
Input /1M
$0.09
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$3e-8$0.03 / 1MPer input token
Completion tokens$9e-8$0.09 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.03Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool CallingNot advertisedSupports tools / function calling
Self-Hosting✓ SupportedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

Qwen: Qwen2.5 Coder 7B Instruct
MMLU Signal (Reasoning)
80signal
Coding Signal (HumanEval proxy)
87signal
Math Signal (GSM8K proxy)
74signal
Science Signal (GPQA proxy)
74signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call Qwen: Qwen2.5 Coder 7B Instruct through an OpenAI-compatible client.

from openai import OpenAI

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

response = client.chat.completions.create(
    model="qwen/qwen2.5-coder-7b-instruct",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does Qwen: Qwen2.5 Coder 7B Instruct cost?

$0.03 per 1M input tokens and $0.09 per 1M output tokens on the official Qwen API.

What is the context window of Qwen: Qwen2.5 Coder 7B Instruct?

Qwen: Qwen2.5 Coder 7B Instruct supports up to 33K tokens of context.

Does Qwen: Qwen2.5 Coder 7B Instruct support tool / function calling?

Qwen: Qwen2.5 Coder 7B Instruct does not advertise first-class tool/function calling. Check vendor docs for the latest capabilities.

How do I access Qwen: Qwen2.5 Coder 7B Instruct?

Use the official Qwen API with the model id `qwen/qwen2.5-coder-7b-instruct`. See the Quick start section above for code examples.