Which is cheaper, Phi-4-multimodal-instruct or Qwen2.5-Coder 32B Instruct?
As of August 25, 2026, Phi-4-multimodal-instruct is 17% cheaper on blended LLM API pricing. Phi-4-multimodal-instruct costs $0.05 per million input tokens and $0.10 per million output tokens ($0.15 blended 1M-in + 1M-out). Qwen2.5-Coder 32B Instruct costs $0.09 / $0.09 per million tokens ($0.18 blended). Sources: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/ and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Phi-4-multimodal-instruct vs Qwen2.5-Coder 32B Instruct cost per million tokens?
Phi-4-multimodal-instruct Microsoft API pricing is $0.05 input and $0.10 output per million tokens via Microsoft. Qwen2.5-Coder 32B Instruct Qwen API pricing is $0.09 input and $0.09 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Phi-4-multimodal-instruct or Qwen2.5-Coder 32B Instruct?
Qwen2.5-Coder 32B Instruct has a published SWE-bench Verified score of 9%. Phi-4-multimodal-instruct does not have that eval on this page yet.
What is the context window for Phi-4-multimodal-instruct vs Qwen2.5-Coder 32B Instruct?
Phi-4-multimodal-instruct supports a 128K token context window, while Qwen2.5-Coder 32B Instruct supports 128K tokens. Both models have the same context window size. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, Phi-4-multimodal-instruct or Qwen2.5-Coder 32B Instruct?
Shared benchmark scores for Phi-4-multimodal-instruct and Qwen2.5-Coder 32B Instruct are still limited. Check the comparison table for the evals each model has published. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is Phi-4-multimodal-instruct or Qwen2.5-Coder 32B Instruct better for production use?
Both Phi-4-multimodal-instruct and Qwen2.5-Coder 32B Instruct are production API models. For cost-sensitive production traffic, Phi-4-multimodal-instruct has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between Phi-4-multimodal-instruct and Qwen2.5-Coder 32B Instruct in my app?
Yes. Call Phi-4-multimodal-instruct through Microsoft and Qwen2.5-Coder 32B Instruct through Qwen with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this Phi-4-multimodal-instruct vs Qwen2.5-Coder 32B Instruct pricing data?
List rates are the latest published Microsoft API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/ and https://bailian.console.aliyun.com/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for Phi-4-multimodal-instruct and Qwen2.5-Coder 32B Instruct?
Phi-4-multimodal-instruct supports up to 128K output tokens per request, while Qwen2.5-Coder 32B Instruct supports up to 128K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, Phi-4-multimodal-instruct or Qwen2.5-Coder 32B Instruct?
Phi-4-multimodal-instruct runs at approximately 25 tokens/second while Qwen2.5-Coder 32B Instruct runs at 42 tokens/second. Qwen2.5-Coder 32B Instruct is faster in raw throughput. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this Phi-4-multimodal-instruct vs Qwen2.5-Coder 32B Instruct comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Phi-4-multimodal-instruct or Qwen2.5-Coder 32B Instruct from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
