GPT-5.4 vs Qwen3.6-Max
GPT-5.4 (2026) and Qwen3.6-Max (2026) are frontier reasoning models from OpenAI and Alibaba. GPT-5.4 ships a 1.1M-token context window, while Qwen3.6-Max ships a 262K-token context window. 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 fits 4x more tokens; pick it for long-context work and Qwen3.6-Max for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-5.4 | Qwen3.6-Max |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | Long context and Vision |
| Context window | 1.1M | 262K |
| Cheapest output | $20/1M tokens | - |
| Provider routes | 2 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.4 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.4 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GPT-5.4 for Coding, RAG, and Agents.
- Local decision data tags Qwen3.6-Max for Long context and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GPT-5.4
$7,000
Cheapest tracked route: OpenAI API
Qwen3.6-Max
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.4 and Qwen3.6-Max; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Qwen3.6-Max and GPT-5.4; plan for SDK, billing, or endpoint changes.
- GPT-5.4 adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-05 | 2026-04-13 |
| Context window | 1.1M | 262K |
| Parameters | — | — |
| Architecture | decoder only | - |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | GPT-5.4 | Qwen3.6-Max |
|---|---|---|
| Input price | $2.5/1M tokens | - |
| Output price | $20/1M tokens | - |
| Providers |
Capabilities
| Capability | GPT-5.4 | Qwen3.6-Max |
|---|---|---|
| Vision | No | No |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: GPT-5.4, function calling: GPT-5.4, tool use: GPT-5.4, structured outputs: GPT-5.4, and code execution: GPT-5.4. Both models share multimodal input, 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 Qwen3.6-Max has no token price sourced yet. Provider availability is 2 tracked routes versus 1. 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, larger context windows, and broader provider choice are central to the workload. Choose Qwen3.6-Max when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, GPT-5.4 or Qwen3.6-Max?
GPT-5.4 supports 1.1M tokens, while Qwen3.6-Max supports 262K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Is GPT-5.4 or Qwen3.6-Max open source?
GPT-5.4 is listed under Proprietary. Qwen3.6-Max is listed under Proprietary. 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 Qwen3.6-Max?
Both GPT-5.4 and Qwen3.6-Max expose multimodal input. 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 reasoning mode, GPT-5.4 or Qwen3.6-Max?
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 Qwen3.6-Max?
GPT-5.4 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.4 and Qwen3.6-Max?
GPT-5.4 is available on OpenAI API and OpenRouter. Qwen3.6-Max is available on Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.