Workload fit
Qwen2.5 Coder 32B Instruct is categorized for Text-to-text AI models. Its current record accepts text and produces text. Confirm file formats, preprocessing, and provider-specific request schemas before implementation.
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique ability to switch seamlessly between a thinking mode for complex reasoning and a non-thinking mode for efficient dialogue ensures versatile, high-quality performance. Significantly outperforming prior models like QwQ and Qwen2.5, Qwen3 delivers superior mathematics, coding, commonsense reasoning, creative writing, and interactive dialogue capabilities. The Qwen3-30B-A3B variant includes 30.5 billion parameters (3.3 billion activated), 48 layers, 128 experts (8 activated per task), and supports up to 131K token contexts with YaRN, setting a new standard among open-source models.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Qwen2.5 Coder 32B Instruct is listed in Requesty’s public model catalogue under the exact routing identifier deepinfra/Qwen/Qwen2.5-Coder-32B-Instruct. Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique ability to switch seamlessly between a thinking mode for complex reasoning and a non-thinking mode for efficient dialogue ensures versatile, high-quality performance.
Significantly outperforming prior models like QwQ and Qwen2.5, Qwen3 delivers superior mathematics, coding, commonsense reasoning, creative writing, and interactive dialogue capabilities. The Qwen3-30B-A3B variant includes 30.5 billion parameters (3.3 billion activated), 48 layers, 128 experts (8 activated per task), and supports up to 131K token contexts with YaRN, setting a new standard among open-source models.
At the time this draft was collected, the catalogue records a context window of 16,384 tokens and a maximum output of 40,960 tokens. It records no reasoning-support flag, no vision-input flag, tool-calling support, and no image-generation flag. These fields describe the routing catalogue entry and should be rechecked against the current provider documentation before production use.
The source catalogue reports input and output prices when available. Pricing can depend on the route, region, token tier, cache use, account, and date, so this record does not infer a commercial commitment from a single snapshot. Confirm current pricing, data handling, regional controls, rate limits, and availability with the current upstream documentation.
This is a source-backed draft imported from Requesty’s public catalogue. It is not published automatically. An editor must verify the exact model identifier, the material claims, and the chosen deployment path before approving it for public discovery or sitemap inclusion.
Use the recorded facts as a shortlist, then validate the model against representative inputs and production constraints.
Qwen2.5 Coder 32B Instruct is categorized for Text-to-text AI models. Its current record accepts text and produces text. Confirm file formats, preprocessing, and provider-specific request schemas before implementation.
The directory records 16.4K context and 41.0K maximum output. Listed token prices are $0.07 input and $0.16 output per 1M tokens. Treat missing values as unknown and recheck current commercial terms.
Recorded output speed is — and time to first token is —. Hosting route, region, prompt length, concurrency, and provider load can materially change both measurements.
This page separates sourced model facts from incomplete fields. Benchmark evidence is displayed only when its source is linked and verified. Before choosing Qwen2.5 Coder 32B Instruct, test task quality, tool reliability, safety behavior, data controls, rate limits, and total cost on the exact route you intend to use.
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