Qwen2.5 Coder 32B Instruct

Text input Text output Free Option
Author's Description

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** and **code fixing**. - A more comprehensive foundation for real-world applications such as **Code Agents**. Not only enhancing coding capabilities but also maintaining its strengths in mathematics and general competencies. To read more about its evaluation results, check out [Qwen 2.5 Coder's blog](https://qwenlm.github.io/blog/qwen2.5-coder-family/).

Key Specifications
Cost
$
Context
32K
Parameters
500B (Rumoured)
Released
Nov 11, 2024
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Stop Presence Penalty Top P Temperature Seed Min P Response Format Frequency Penalty Max Tokens
Features

This model supports the following features:

Response Format
Performance Summary

Qwen2.5 Coder 32B Instruct, a recent iteration in the Qwen series, demonstrates a strong overall performance profile. It consistently performs among the fastest models, ranking in the 77th percentile for speed across various benchmarks. Furthermore, its pricing is highly competitive, placing it in the 87th percentile for cost-effectiveness. The model exhibits exceptional reliability, achieving a 100% success rate across all evaluated benchmarks, indicating minimal technical failures. In terms of specific capabilities, Qwen2.5 Coder 32B Instruct excels in Instruction Following, achieving perfect accuracy in one instance and demonstrating strong performance in another. It also shows impressive accuracy in Ethics (99.0%) and General Knowledge (96.2%). While its Email Classification accuracy is solid at 96.0%, its performance in the Coding (Baseline) benchmark is moderate at 77.0% accuracy, placing it in the 44th percentile. Similarly, its Reasoning capabilities are respectable at 72.0% accuracy. The model's key strengths lie in its robust instruction following, high reliability, and competitive pricing, making it a versatile option for tasks requiring precise adherence to directives and consistent operation. Its primary area for potential improvement appears to be in the core coding benchmark, despite its description as a code-specific model with significant improvements in code generation and reasoning.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.06
Completion $0.15

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
DeepInfra
DeepInfra | qwen/qwen-2.5-coder-32b-instruct 32K $0.06 / 1M tokens $0.15 / 1M tokens
Nebius
Nebius | qwen/qwen-2.5-coder-32b-instruct 131K $0.06 / 1M tokens $0.18 / 1M tokens
Lambda
Lambda | qwen/qwen-2.5-coder-32b-instruct 32K $0.07 / 1M tokens $0.16 / 1M tokens
Hyperbolic
Hyperbolic | qwen/qwen-2.5-coder-32b-instruct 32K $0.2 / 1M tokens $0.2 / 1M tokens
Cloudflare
Cloudflare | qwen/qwen-2.5-coder-32b-instruct 32K $0.66 / 1M tokens $1 / 1M tokens
Together
Together | qwen/qwen-2.5-coder-32b-instruct 32K $0.8 / 1M tokens $0.8 / 1M tokens
Featherless
Featherless | qwen/qwen-2.5-coder-32b-instruct 16K $0.05 / 1M tokens $0.2 / 1M tokens
Chutes
Chutes | qwen/qwen-2.5-coder-32b-instruct 32K $0.05 / 1M tokens $0.2 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Free Executions Accuracy Cost Duration
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