LLM Reference

Qwen2.5-7B-Instruct

Released
2024-06-07
Last refreshed
2026-06-29
Status
Researched 90d ago
Open sourceCommercial use: permittedCodingRAGLong contextClassificationJSON / Tool use

Qwen2.5-7B-Instruct is worth evaluating for coding, rag, and long context when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding, rag, and long context
  • Workloads that can use a 128k context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
Specifications
Family
Qwen2.5
Released
2024-06-07
Context
128k
Parameters
7.61B
Architecture
Decoder Only
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Weights
Available
Code
Unknown
Training
Fine-tuned
Created by

AI research institute of Alibaba Group.

Hangzhou, Zhejiang, China
Founded 2017
Website
Pricing
Output / 1M
$0.030
Input / 1M
$0.030

Cheapest of 7 routes · DeepInfra

About

Instruction-tuned 7B variant combining strong reasoning with real-time inference on single GPUs, ideal for developer tools and vision applications.

Qwen2.5-7B-Instruct is an open-source model in the Qwen2.5 family. The structured metadata tracks a 128k-token context window and structured outputs. This page tracks provider routes through DeepInfra, OpenRouter, Fireworks AI, and 4 more, with the cheapest tracked route listed at $0.03 input and $0.03 output per 1M tokens. Headline tracked benchmarks include Google-Proof Q&A 45.2, HellaSwag 89.3, and HumanEval 68.4.

Top use-case fit: coding, agents, and build tasks

Coding

Q/$ A

1 relevant benchmark in the decision map.

RAG

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Capabilities

Structured Outputs

Benchmark peer barsfor Coding

Benchmark scores(4)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
Google-Proof Q&A45.2diamondObserved 2026-03-06Source
HellaSwag89.310-shotObserved 2026-03-06Source
HumanEval68.4pass@1Observed 2026-03-06Source
Massive Multitask Language Understanding81.25-shotObserved 2026-03-06Source

Migration checks

No linked migration route is available for this model yet.

Compare Qwen2.5-7B-Instruct with other models

Frequently asked questions

What is the context window of Qwen2.5-7B-Instruct?

Qwen2.5-7B-Instruct has a context window of 128k tokens.

How much does Qwen2.5-7B-Instruct cost?

Qwen2.5-7B-Instruct pricing ranges from $0.03/1M to $0.2/1M input tokens depending on the provider.

When was Qwen2.5-7B-Instruct released?

Qwen2.5-7B-Instruct was released on 2024-06-07.

Which providers offer Qwen2.5-7B-Instruct?

Qwen2.5-7B-Instruct is available from 7 providers: DeepInfra, OpenRouter, Fireworks AI, NVIDIA NIM, Together AI, SiliconFlow, Novita AI.

What benchmarks has Qwen2.5-7B-Instruct been tested on?

Qwen2.5-7B-Instruct has been evaluated on 4 benchmarks, including Google-Proof Q&A, HellaSwag, HumanEval, Massive Multitask Language Understanding.