Devstral Compare DeepSeek R1 Distill Qwen 32B

Devstral
vs
DeepSeek R1 Distill Qwen 32B

Comparing Devstral and DeepSeek R1 Distill Qwen 32B, which one is better? We will compare Devstral and DeepSeek R1 Distill Qwen 32B, including model features, token pricing, API costs, performance benchmarks, and actual capabilities to help you choose the LLM that suits your needs

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Devstral

DeepSeek R1 Distill Qwen 32B

Devstral

Mistral AI's coding agent base model designed specifically for software engineering tasks. Features 24B parameters and 128K context window, optimized for multi-file editing, codebase exploration, and GitHub issue resolution. Supports deep integration with agent frameworks like OpenHands and SWE-Agent, understands complex relationships in large codebases, suitable for automated software development and code maintenance.

DeepSeek R1 Distill Qwen 32B

DeepSeek-R1 is the first-generation inference model built on DeepSeek-V3 (with a total of 671 billion parameters and 37 billion activated parameters per token). It combines large-scale reinforcement learning (RL) to enhance chain-of-thought and reasoning abilities, and performs excellently in mathematics, code, and multi-step reasoning tasks.

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Input and output token cost comparison

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Performance metrics from various standardized tests and evaluations

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DevstralvsDeepSeek R1 Distill Qwen 32B

Basic ParametersCompare

PricingCompare

Benchmark ScoresCompare

Devstral
vs
DeepSeek R1 Distill Qwen 32B