GPT-5.5 vs Qwen3.6-27B
GPT-5.5 (2026) and Qwen3.6-27B (2026) are agentic coding models from OpenAI and Alibaba. GPT-5.5 ships a 1.1M-token context window, while Qwen3.6-27B ships a 262K-token context window. On MMLU PRO, GPT-5.5 leads by 1.9 pts. On pricing, Qwen3.6-27B costs $0.32/1M input tokens versus $5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.6-27B is ~1462% cheaper at $0.32/1M; pay for GPT-5.5 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GPT-5.5 | Qwen3.6-27B |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1.1M | 262K |
| Cheapest output | $30/1M tokens | $3.2/1M tokens |
| Provider routes | 2 tracked | 2 tracked |
| Shared benchmarks | MMLU PRO leader | 3 rows |
Decision tradeoffs
- GPT-5.5 leads the largest shared benchmark signal on MMLU PRO by 1.9 points.
- GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.5 uniquely exposes Structured outputs and Code execution in local model data.
- Local decision data tags GPT-5.5 for Coding, RAG, and Agents.
- Qwen3.6-27B has the lower cheapest tracked output price at $3.2/1M tokens.
- Local decision data tags Qwen3.6-27B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GPT-5.5
$11,500
Cheapest tracked route: OpenAI API
Qwen3.6-27B
$1,056
Cheapest tracked route: OpenRouter
Estimated monthly gap: $10,444. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3.6-27B is $26.80/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs and Code execution before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.5 is $26.80/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 adds Structured outputs and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-23 | 2026-04-27 |
| Context window | 1.1M | 262K |
| Parameters | — | 27B |
| Architecture | decoder only | dense |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | 2025-12 | - |
Pricing and availability
| Pricing attribute | GPT-5.5 | Qwen3.6-27B |
|---|---|---|
| Input price | $5/1M tokens | $0.32/1M tokens |
| Output price | $30/1M tokens | $3.2/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.5 | Qwen3.6-27B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
Benchmarks
| Benchmark | GPT-5.5 | Qwen3.6-27B |
|---|---|---|
| MMLU PRO | 88.1 | 86.2 |
| SWE-bench Verified | 88.7 | 77.2 |
| Google-Proof Q&A | 93.6 | 87.8 |
Deep dive
On shared benchmark coverage, MMLU PRO has GPT-5.5 at 88.1 and Qwen3.6-27B at 86.2, with GPT-5.5 ahead by 1.9 points; SWE-bench Verified has GPT-5.5 at 88.7 and Qwen3.6-27B at 77.2, with GPT-5.5 ahead by 11.5 points; Google-Proof Q&A has GPT-5.5 at 93.6 and Qwen3.6-27B at 87.8, with GPT-5.5 ahead by 5.8 points. The largest visible gap is 11.5 points on SWE-bench Verified, 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 structured outputs: GPT-5.5 and code execution: GPT-5.5. Both models share vision, multimodal input, reasoning mode, and function calling, 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.
For cost, GPT-5.5 lists $5/1M input and $30/1M output tokens, while Qwen3.6-27B lists $0.32/1M input and $3.2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.6-27B lower by about $11.32 per million blended tokens. Availability is 2 providers versus 2, so concentration risk also matters.
Choose GPT-5.5 when coding workflow support and larger context windows are central to the workload. Choose Qwen3.6-27B when coding workflow support and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-5.5 or Qwen3.6-27B?
GPT-5.5 supports 1.1M tokens, while Qwen3.6-27B 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.
Which is cheaper, GPT-5.5 or Qwen3.6-27B?
Qwen3.6-27B is cheaper on tracked token pricing. GPT-5.5 costs $5/1M input and $30/1M output tokens. Qwen3.6-27B costs $0.32/1M input and $3.2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.5 or Qwen3.6-27B open source?
GPT-5.5 is listed under Proprietary. Qwen3.6-27B is listed under Apache 2.0. 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 vision, GPT-5.5 or Qwen3.6-27B?
Both GPT-5.5 and Qwen3.6-27B expose vision. 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 multimodal input, GPT-5.5 or Qwen3.6-27B?
Both GPT-5.5 and Qwen3.6-27B 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.
Where can I run GPT-5.5 and Qwen3.6-27B?
GPT-5.5 is available on OpenAI API and OpenRouter. Qwen3.6-27B is available on OpenRouter and 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: 2026-05-14. Data sourced from public model cards and provider documentation.