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GPT-5.4 vs Qwen2.5-72B

GPT-5.4 (2026) and Qwen2.5-72B (2025) are frontier reasoning models from OpenAI and Alibaba. GPT-5.4 ships a not-yet-sourced context window, while Qwen2.5-72B ships a 128k-token context window. On MMLU PRO, GPT-5.4 leads by 15.5 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

GPT-5.4 is safer overall; choose Qwen2.5-72B when provider fit matters.

Specs

Released2026-03-052025-10-10
Context window128k
Parameters72B
Architecturedecoder only-
LicenseProprietaryOpen Source
Knowledge cutoff2025-082024-09

Pricing and availability

GPT-5.4Qwen2.5-72B
Input price$2.5/1M tokens-
Output price$15/1M tokens-
Providers-

Capabilities

GPT-5.4Qwen2.5-72B
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

BenchmarkGPT-5.4Qwen2.5-72B
MMLU PRO87.572.0

Deep dive

On shared benchmark coverage, MMLU PRO has GPT-5.4 at 87.5 and Qwen2.5-72B at 72, with GPT-5.4 ahead by 15.5 points. The largest visible gap is 15.5 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on multimodal input: GPT-5.4, reasoning mode: GPT-5.4, structured outputs: GPT-5.4, and code execution: GPT-5.4. Both models share function calling and tool use, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: GPT-5.4 has $2.5/1M input tokens and Qwen2.5-72B has no token price sourced yet. Provider availability is 2 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose GPT-5.4 when coding workflow support and broader provider choice are central to the workload. Choose Qwen2.5-72B when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Is GPT-5.4 or Qwen2.5-72B open source?

GPT-5.4 is listed under Proprietary. Qwen2.5-72B is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for multimodal input, GPT-5.4 or Qwen2.5-72B?

GPT-5.4 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for reasoning mode, GPT-5.4 or Qwen2.5-72B?

GPT-5.4 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, GPT-5.4 or Qwen2.5-72B?

Both GPT-5.4 and Qwen2.5-72B expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for tool use, GPT-5.4 or Qwen2.5-72B?

Both GPT-5.4 and Qwen2.5-72B expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run GPT-5.4 and Qwen2.5-72B?

GPT-5.4 is available on OpenAI API and OpenRouter. Qwen2.5-72B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.